What's New In Python 3.2
************************

Author:
   Raymond Hettinger

This article explains the new features in Python 3.2 as compared to
3.1. Python 3.2 was released on February 20, 2011. It focuses on a few
highlights and gives a few examples.  For full details, see the
Misc/NEWS file.

See also: **PEP 392** - Python 3.2 Release Schedule


PEP 384: Defining a Stable ABI
==============================

In the past, extension modules built for one Python version were often
not usable with other Python versions. Particularly on Windows, every
feature release of Python required rebuilding all extension modules
that one wanted to use. This requirement was the result of the free
access to Python interpreter internals that extension modules could
use.

With Python 3.2, an alternative approach becomes available: extension
modules which restrict themselves to a limited API (by defining
Py_LIMITED_API) cannot use many of the internals, but are constrained
to a set of API functions that are promised to be stable for several
releases. As a consequence, extension modules built for 3.2 in that
mode will also work with 3.3, 3.4, and so on. Extension modules that
make use of details of memory structures can still be built, but will
need to be recompiled for every feature release.

See also:

  **PEP 384** - Defining a Stable ABI
     PEP written by Martin von Löwis.


PEP 389: Argparse Command Line Parsing Module
=============================================

A new module for command line parsing, "argparse", was introduced to
overcome the limitations of "optparse" which did not provide support
for positional arguments (not just options), subcommands, required
options and other common patterns of specifying and validating
options.

This module has already had widespread success in the community as a
third-party module.  Being more fully featured than its predecessor,
the "argparse" module is now the preferred module for command-line
processing. The older module is still being kept available because of
the substantial amount of legacy code that depends on it.

Here's an annotated example parser showing features like limiting
results to a set of choices, specifying a *metavar* in the help
screen, validating that one or more positional arguments is present,
and making a required option:

   import argparse
   parser = argparse.ArgumentParser(
               description = 'Manage servers',         # main description for help
               epilog = 'Tested on Solaris and Linux') # displayed after help
   parser.add_argument('action',                       # argument name
               choices = ['deploy', 'start', 'stop'],  # three allowed values
               help = 'action on each target')         # help msg
   parser.add_argument('targets',
               metavar = 'HOSTNAME',                   # var name used in help msg
               nargs = '+',                            # require one or more targets
               help = 'url for target machines')       # help msg explanation
   parser.add_argument('-u', '--user',                 # -u or --user option
               required = True,                        # make it a required argument
               help = 'login as user')

Example of calling the parser on a command string:

   >>> cmd = 'deploy sneezy.example.com sleepy.example.com -u skycaptain'
   >>> result = parser.parse_args(cmd.split())
   >>> result.action
   'deploy'
   >>> result.targets
   ['sneezy.example.com', 'sleepy.example.com']
   >>> result.user
   'skycaptain'

Example of the parser's automatically generated help:

   >>> parser.parse_args('-h'.split())

   usage: manage_cloud.py [-h] -u USER
                          {deploy,start,stop} HOSTNAME [HOSTNAME ...]

   Manage servers

   positional arguments:
     {deploy,start,stop}   action on each target
     HOSTNAME              url for target machines

   optional arguments:
     -h, --help            show this help message and exit
     -u USER, --user USER  login as user

   Tested on Solaris and Linux

An especially nice "argparse" feature is the ability to define
subparsers, each with their own argument patterns and help displays:

   import argparse
   parser = argparse.ArgumentParser(prog='HELM')
   subparsers = parser.add_subparsers()

   parser_l = subparsers.add_parser('launch', help='Launch Control')   # first subgroup
   parser_l.add_argument('-m', '--missiles', action='store_true')
   parser_l.add_argument('-t', '--torpedos', action='store_true')

   parser_m = subparsers.add_parser('move', help='Move Vessel',        # second subgroup
                                    aliases=('steer', 'turn'))         # equivalent names
   parser_m.add_argument('-c', '--course', type=int, required=True)
   parser_m.add_argument('-s', '--speed', type=int, default=0)

   $ ./helm.py --help                         # top level help (launch and move)
   $ ./helm.py launch --help                  # help for launch options
   $ ./helm.py launch --missiles              # set missiles=True and torpedos=False
   $ ./helm.py steer --course 180 --speed 5   # set movement parameters

See also:

  **PEP 389** - New Command Line Parsing Module
     PEP written by Steven Bethard.

  Upgrading optparse code for details on the differences from
  "optparse".


PEP 391:  Dictionary Based Configuration for Logging
====================================================

The "logging" module provided two kinds of configuration, one style
with function calls for each option or another style driven by an
external file saved in a "ConfigParser" format.  Those options did not
provide the flexibility to create configurations from JSON or YAML
files, nor did they support incremental configuration, which is needed
for specifying logger options from a command line.

To support a more flexible style, the module now offers
"logging.config.dictConfig()" for specifying logging configuration
with plain Python dictionaries.  The configuration options include
formatters, handlers, filters, and loggers.  Here's a working example
of a configuration dictionary:

   {"version": 1,
    "formatters": {"brief": {"format": "%(levelname)-8s: %(name)-15s: %(message)s"},
                   "full": {"format": "%(asctime)s %(name)-15s %(levelname)-8s %(message)s"}
                   },
    "handlers": {"console": {
                      "class": "logging.StreamHandler",
                      "formatter": "brief",
                      "level": "INFO",
                      "stream": "ext://sys.stdout"},
                 "console_priority": {
                      "class": "logging.StreamHandler",
                      "formatter": "full",
                      "level": "ERROR",
                      "stream": "ext://sys.stderr"}
                 },
    "root": {"level": "DEBUG", "handlers": ["console", "console_priority"]}}

If that dictionary is stored in a file called "conf.json", it can be
loaded and called with code like this:

   >>> import json, logging.config
   >>> with open('conf.json') as f:
   ...     conf = json.load(f)
   ...
   >>> logging.config.dictConfig(conf)
   >>> logging.info("Transaction completed normally")
   INFO    : root           : Transaction completed normally
   >>> logging.critical("Abnormal termination")
   2011-02-17 11:14:36,694 root            CRITICAL Abnormal termination

See also:

  **PEP 391** - Dictionary Based Configuration for Logging
     PEP written by Vinay Sajip.


PEP 3148:  The "concurrent.futures" module
==========================================

Code for creating and managing concurrency is being collected in a new
top-level namespace, *concurrent*.  Its first member is a *futures*
package which provides a uniform high-level interface for managing
threads and processes.

The design for "concurrent.futures" was inspired by the
*java.util.concurrent* package.  In that model, a running call and its
result are represented by a "Future" object that abstracts features
common to threads, processes, and remote procedure calls.  That object
supports status checks (running or done), timeouts, cancellations,
adding callbacks, and access to results or exceptions.

The primary offering of the new module is a pair of executor classes
for launching and managing calls.  The goal of the executors is to
make it easier to use existing tools for making parallel calls. They
save the effort needed to setup a pool of resources, launch the calls,
create a results queue, add time-out handling, and limit the total
number of threads, processes, or remote procedure calls.

Ideally, each application should share a single executor across
multiple components so that process and thread limits can be centrally
managed.  This solves the design challenge that arises when each
component has its own competing strategy for resource management.

Both classes share a common interface with three methods: "submit()"
for scheduling a callable and returning a "Future" object; "map()" for
scheduling many asynchronous calls at a time, and "shutdown()" for
freeing resources.  The class is a *context manager* and can be used
in a "with" statement to assure that resources are automatically
released when currently pending futures are done executing.

A simple of example of "ThreadPoolExecutor" is a launch of four
parallel threads for copying files:

   import concurrent.futures, shutil
   with concurrent.futures.ThreadPoolExecutor(max_workers=4) as e:
       e.submit(shutil.copy, 'src1.txt', 'dest1.txt')
       e.submit(shutil.copy, 'src2.txt', 'dest2.txt')
       e.submit(shutil.copy, 'src3.txt', 'dest3.txt')
       e.submit(shutil.copy, 'src3.txt', 'dest4.txt')

See also:

  **PEP 3148** - Futures -- Execute Computations Asynchronously
     PEP written by Brian Quinlan.

  Code for Threaded Parallel URL reads, an example using threads to
  fetch multiple web pages in parallel.

  Code for computing prime numbers in parallel, an example
  demonstrating "ProcessPoolExecutor".


PEP 3147:  PYC Repository Directories
=====================================

Python's scheme for caching bytecode in *.pyc* files did not work well
in environments with multiple Python interpreters.  If one interpreter
encountered a cached file created by another interpreter, it would
recompile the source and overwrite the cached file, thus losing the
benefits of caching.

The issue of "pyc fights" has become more pronounced as it has become
commonplace for Linux distributions to ship with multiple versions of
Python. These conflicts also arise with CPython alternatives such as
Unladen Swallow.

To solve this problem, Python's import machinery has been extended to
use distinct filenames for each interpreter.  Instead of Python 3.2
and Python 3.3 and Unladen Swallow each competing for a file called
"mymodule.pyc", they will now look for "mymodule.cpython-32.pyc",
"mymodule.cpython-33.pyc", and "mymodule.unladen10.pyc".  And to
prevent all of these new files from cluttering source directories, the
*pyc* files are now collected in a "__pycache__" directory stored
under the package directory.

Aside from the filenames and target directories, the new scheme has a
few aspects that are visible to the programmer:

* Imported modules now have a "__cached__" attribute which stores the
  name of the actual file that was imported:

  >>> import collections
  >>> collections.__cached__ 
  'c:/py32/lib/__pycache__/collections.cpython-32.pyc'

* The tag that is unique to each interpreter is accessible from the
  "imp" module:

  >>> import imp
  >>> imp.get_tag() 
  'cpython-32'

* Scripts that try to deduce source filename from the imported file
  now need to be smarter.  It is no longer sufficient to simply strip
  the "c" from a ".pyc" filename.  Instead, use the new functions in
  the "imp" module:

  >>> imp.source_from_cache('c:/py32/lib/__pycache__/collections.cpython-32.pyc')
  'c:/py32/lib/collections.py'
  >>> imp.cache_from_source('c:/py32/lib/collections.py') 
  'c:/py32/lib/__pycache__/collections.cpython-32.pyc'

* The "py_compile" and "compileall" modules have been updated to
  reflect the new naming convention and target directory.  The
  command-line invocation of *compileall* has new options: "-i" for
  specifying a list of files and directories to compile and "-b" which
  causes bytecode files to be written to their legacy location rather
  than *__pycache__*.

* The "importlib.abc" module has been updated with new *abstract base
  classes* for loading bytecode files.  The obsolete ABCs, "PyLoader"
  and "PyPycLoader", have been deprecated (instructions on how to stay
  Python 3.1 compatible are included with the documentation).

See also:

  **PEP 3147** - PYC Repository Directories
     PEP written by Barry Warsaw.


PEP 3149: ABI Version Tagged .so Files
======================================

The PYC repository directory allows multiple bytecode cache files to
be co-located.  This PEP implements a similar mechanism for shared
object files by giving them a common directory and distinct names for
each version.

The common directory is "pyshared" and the file names are made
distinct by identifying the Python implementation (such as CPython,
PyPy, Jython, etc.), the major and minor version numbers, and optional
build flags (such as "d" for debug, "m" for pymalloc, "u" for wide-
unicode).  For an arbitrary package "foo", you may see these files
when the distribution package is installed:

   /usr/share/pyshared/foo.cpython-32m.so
   /usr/share/pyshared/foo.cpython-33md.so

In Python itself, the tags are accessible from functions in the
"sysconfig" module:

   >>> import sysconfig
   >>> sysconfig.get_config_var('SOABI')       # find the version tag
   'cpython-32mu'
   >>> sysconfig.get_config_var('EXT_SUFFIX')  # find the full filename extension
   '.cpython-32mu.so'

See also:

  **PEP 3149** - ABI Version Tagged .so Files
     PEP written by Barry Warsaw.


PEP 3333: Python Web Server Gateway Interface v1.0.1
====================================================

This informational PEP clarifies how bytes/text issues are to be
handled by the WSGI protocol.  The challenge is that string handling
in Python 3 is most conveniently handled with the "str" type even
though the HTTP protocol is itself bytes oriented.

The PEP differentiates so-called *native strings* that are used for
request/response headers and metadata versus *byte strings* which are
used for the bodies of requests and responses.

The *native strings* are always of type "str" but are restricted to
code points between *U+0000* through *U+00FF* which are translatable
to bytes using *Latin-1* encoding.  These strings are used for the
keys and values in the environment dictionary and for response headers
and statuses in the "start_response()" function.  They must follow
**RFC 2616** with respect to encoding. That is, they must either be
*ISO-8859-1* characters or use **RFC 2047** MIME encoding.

For developers porting WSGI applications from Python 2, here are the
salient points:

* If the app already used strings for headers in Python 2, no change
  is needed.

* If instead, the app encoded output headers or decoded input headers,
  then the headers will need to be re-encoded to Latin-1.  For
  example, an output header encoded in utf-8 was using
  "h.encode('utf-8')" now needs to convert from bytes to native
  strings using "h.encode('utf-8').decode('latin-1')".

* Values yielded by an application or sent using the "write()" method
  must be byte strings.  The "start_response()" function and environ
  must use native strings.  The two cannot be mixed.

For server implementers writing CGI-to-WSGI pathways or other CGI-
style protocols, the users must to be able access the environment
using native strings even though the underlying platform may have a
different convention.  To bridge this gap, the "wsgiref" module has a
new function, "wsgiref.handlers.read_environ()" for transcoding CGI
variables from "os.environ" into native strings and returning a new
dictionary.

See also:

  **PEP 3333** - Python Web Server Gateway Interface v1.0.1
     PEP written by Phillip Eby.


Other Language Changes
======================

Some smaller changes made to the core Python language are:

* String formatting for "format()" and "str.format()" gained new
  capabilities for the format character **#**.  Previously, for
  integers in binary, octal, or hexadecimal, it caused the output to
  be prefixed with '0b', '0o', or '0x' respectively.  Now it can also
  handle floats, complex, and Decimal, causing the output to always
  have a decimal point even when no digits follow it.

  >>> format(20, '#o')
  '0o24'
  >>> format(12.34, '#5.0f')
  '  12.'

  (Suggested by Mark Dickinson and implemented by Eric Smith in
  bpo-7094.)

* There is also a new "str.format_map()" method that extends the
  capabilities of the existing "str.format()" method by accepting
  arbitrary *mapping* objects.  This new method makes it possible to
  use string formatting with any of Python's many dictionary-like
  objects such as "defaultdict", "Shelf", "ConfigParser", or "dbm".
  It is also useful with custom "dict" subclasses that normalize keys
  before look-up or that supply a "__missing__()" method for unknown
  keys:

     >>> import shelve
     >>> d = shelve.open('tmp.shl')
     >>> 'The {project_name} status is {status} as of {date}'.format_map(d)
     'The testing project status is green as of February 15, 2011'

     >>> class LowerCasedDict(dict):
     ...     def __getitem__(self, key):
     ...         return dict.__getitem__(self, key.lower())
     >>> lcd = LowerCasedDict(part='widgets', quantity=10)
     >>> 'There are {QUANTITY} {Part} in stock'.format_map(lcd)
     'There are 10 widgets in stock'

     >>> class PlaceholderDict(dict):
     ...     def __missing__(self, key):
     ...         return '<{}>'.format(key)
     >>> 'Hello {name}, welcome to {location}'.format_map(PlaceholderDict())
     'Hello <name>, welcome to <location>'

   (Suggested by Raymond Hettinger and implemented by Eric Smith in
   bpo-6081.)

* The interpreter can now be started with a quiet option, "-q", to
  prevent the copyright and version information from being displayed
  in the interactive mode.  The option can be introspected using the
  "sys.flags" attribute:

     $ python -q
     >>> sys.flags
     sys.flags(debug=0, division_warning=0, inspect=0, interactive=0,
     optimize=0, dont_write_bytecode=0, no_user_site=0, no_site=0,
     ignore_environment=0, verbose=0, bytes_warning=0, quiet=1)

  (Contributed by Marcin Wojdyr in bpo-1772833).

* The "hasattr()" function works by calling "getattr()" and detecting
  whether an exception is raised.  This technique allows it to detect
  methods created dynamically by "__getattr__()" or
  "__getattribute__()" which would otherwise be absent from the class
  dictionary.  Formerly, *hasattr* would catch any exception, possibly
  masking genuine errors.  Now, *hasattr* has been tightened to only
  catch "AttributeError" and let other exceptions pass through:

     >>> class A:
     ...     @property
     ...     def f(self):
     ...         return 1 // 0
     ...
     >>> a = A()
     >>> hasattr(a, 'f')
     Traceback (most recent call last):
       ...
     ZeroDivisionError: integer division or modulo by zero

  (Discovered by Yury Selivanov and fixed by Benjamin Peterson;
  bpo-9666.)

* The "str()" of a float or complex number is now the same as its
  "repr()". Previously, the "str()" form was shorter but that just
  caused confusion and is no longer needed now that the shortest
  possible "repr()" is displayed by default:

  >>> import math
  >>> repr(math.pi)
  '3.141592653589793'
  >>> str(math.pi)
  '3.141592653589793'

  (Proposed and implemented by Mark Dickinson; bpo-9337.)

* "memoryview" objects now have a "release()" method and they also now
  support the context management protocol.  This allows timely release
  of any resources that were acquired when requesting a buffer from
  the original object.

  >>> with memoryview(b'abcdefgh') as v:
  ...     print(v.tolist())
  [97, 98, 99, 100, 101, 102, 103, 104]

  (Added by Antoine Pitrou; bpo-9757.)

* Previously it was illegal to delete a name from the local namespace
  if it occurs as a free variable in a nested block:

     def outer(x):
         def inner():
             return x
         inner()
         del x

  This is now allowed.  Remember that the target of an "except" clause
  is cleared, so this code which used to work with Python 2.6, raised
  a "SyntaxError" with Python 3.1 and now works again:

     def f():
         def print_error():
             print(e)
         try:
             something
         except Exception as e:
             print_error()
             # implicit "del e" here

  (See bpo-4617.)

* Struct sequence types are now subclasses of tuple. This means that C
  structures like those returned by "os.stat()", "time.gmtime()", and
  "sys.version_info" now work like a *named tuple* and now work with
  functions and methods that expect a tuple as an argument.  This is a
  big step forward in making the C structures as flexible as their
  pure Python counterparts:

  >>> import sys
  >>> isinstance(sys.version_info, tuple)
  True
  >>> 'Version %d.%d.%d %s(%d)' % sys.version_info 
  'Version 3.2.0 final(0)'

  (Suggested by Arfrever Frehtes Taifersar Arahesis and implemented by
  Benjamin Peterson in bpo-8413.)

* Warnings are now easier to control using the "PYTHONWARNINGS"
  environment variable as an alternative to using "-W" at the command
  line:

     $ export PYTHONWARNINGS='ignore::RuntimeWarning::,once::UnicodeWarning::'

  (Suggested by Barry Warsaw and implemented by Philip Jenvey in
  bpo-7301.)

* A new warning category, "ResourceWarning", has been added.  It is
  emitted when potential issues with resource consumption or cleanup
  are detected.  It is silenced by default in normal release builds
  but can be enabled through the means provided by the "warnings"
  module, or on the command line.

  A "ResourceWarning" is issued at interpreter shutdown if the
  "gc.garbage" list isn't empty, and if "gc.DEBUG_UNCOLLECTABLE" is
  set, all uncollectable objects are printed.  This is meant to make
  the programmer aware that their code contains object finalization
  issues.

  A "ResourceWarning" is also issued when a *file object* is destroyed
  without having been explicitly closed.  While the deallocator for
  such object ensures it closes the underlying operating system
  resource (usually, a file descriptor), the delay in deallocating the
  object could produce various issues, especially under Windows.  Here
  is an example of enabling the warning from the command line:

     $ python -q -Wdefault
     >>> f = open("foo", "wb")
     >>> del f
     __main__:1: ResourceWarning: unclosed file <_io.BufferedWriter name='foo'>

  (Added by Antoine Pitrou and Georg Brandl in bpo-10093 and
  bpo-477863.)

* "range" objects now support *index* and *count* methods. This is
  part of an effort to make more objects fully implement the
  "collections.Sequence" *abstract base class*.  As a result, the
  language will have a more uniform API.  In addition, "range" objects
  now support slicing and negative indices, even with values larger
  than "sys.maxsize".  This makes *range* more interoperable with
  lists:

     >>> range(0, 100, 2).count(10)
     1
     >>> range(0, 100, 2).index(10)
     5
     >>> range(0, 100, 2)[5]
     10
     >>> range(0, 100, 2)[0:5]
     range(0, 10, 2)

  (Contributed by Daniel Stutzbach in bpo-9213, by Alexander
  Belopolsky in bpo-2690, and by Nick Coghlan in bpo-10889.)

* The "callable()" builtin function from Py2.x was resurrected.  It
  provides a concise, readable alternative to using an *abstract base
  class* in an expression like "isinstance(x, collections.Callable)":

  >>> callable(max)
  True
  >>> callable(20)
  False

  (See bpo-10518.)

* Python's import mechanism can now load modules installed in
  directories with non-ASCII characters in the path name.  This solved
  an aggravating problem with home directories for users with non-
  ASCII characters in their usernames.

   (Required extensive work by Victor Stinner in bpo-9425.)


New, Improved, and Deprecated Modules
=====================================

Python's standard library has undergone significant maintenance
efforts and quality improvements.

The biggest news for Python 3.2 is that the "email" package, "mailbox"
module, and "nntplib" modules now work correctly with the bytes/text
model in Python 3.  For the first time, there is correct handling of
messages with mixed encodings.

Throughout the standard library, there has been more careful attention
to encodings and text versus bytes issues.  In particular,
interactions with the operating system are now better able to exchange
non-ASCII data using the Windows MBCS encoding, locale-aware
encodings, or UTF-8.

Another significant win is the addition of substantially better
support for *SSL* connections and security certificates.

In addition, more classes now implement a *context manager* to support
convenient and reliable resource clean-up using a "with" statement.


email
-----

The usability of the "email" package in Python 3 has been mostly fixed
by the extensive efforts of R. David Murray.  The problem was that
emails are typically read and stored in the form of "bytes" rather
than "str" text, and they may contain multiple encodings within a
single email.  So, the email package had to be extended to parse and
generate email messages in bytes format.

* New functions "message_from_bytes()" and
  "message_from_binary_file()", and new classes "BytesFeedParser" and
  "BytesParser" allow binary message data to be parsed into model
  objects.

* Given bytes input to the model, "get_payload()" will by default
  decode a message body that has a *Content-Transfer-Encoding* of
  *8bit* using the charset specified in the MIME headers and return
  the resulting string.

* Given bytes input to the model, "Generator" will convert message
  bodies that have a *Content-Transfer-Encoding* of *8bit* to instead
  have a *7bit* *Content-Transfer-Encoding*.

  Headers with unencoded non-ASCII bytes are deemed to be **RFC
  2047**-encoded using the *unknown-8bit* character set.

* A new class "BytesGenerator" produces bytes as output, preserving
  any unchanged non-ASCII data that was present in the input used to
  build the model, including message bodies with a *Content-Transfer-
  Encoding* of *8bit*.

* The "smtplib" "SMTP" class now accepts a byte string for the *msg*
  argument to the "sendmail()" method, and a new method,
  "send_message()" accepts a "Message" object and can optionally
  obtain the *from_addr* and *to_addrs* addresses directly from the
  object.

(Proposed and implemented by R. David Murray, bpo-4661 and bpo-10321.)


elementtree
-----------

The "xml.etree.ElementTree" package and its "xml.etree.cElementTree"
counterpart have been updated to version 1.3.

Several new and useful functions and methods have been added:

* "xml.etree.ElementTree.fromstringlist()" which builds an XML
  document from a sequence of fragments

* "xml.etree.ElementTree.register_namespace()" for registering a
  global namespace prefix

* "xml.etree.ElementTree.tostringlist()" for string representation
  including all sublists

* "xml.etree.ElementTree.Element.extend()" for appending a sequence of
  zero or more elements

* "xml.etree.ElementTree.Element.iterfind()" searches an element and
  subelements

* "xml.etree.ElementTree.Element.itertext()" creates a text iterator
  over an element and its subelements

* "xml.etree.ElementTree.TreeBuilder.end()" closes the current element

* "xml.etree.ElementTree.TreeBuilder.doctype()" handles a doctype
  declaration

Two methods have been deprecated:

* "xml.etree.ElementTree.getchildren()" use "list(elem)" instead.

* "xml.etree.ElementTree.getiterator()" use "Element.iter" instead.

For details of the update, see Introducing ElementTree on Fredrik
Lundh's website.

(Contributed by Florent Xicluna and Fredrik Lundh, bpo-6472.)


functools
---------

* The "functools" module includes a new decorator for caching function
  calls.  "functools.lru_cache()" can save repeated queries to an
  external resource whenever the results are expected to be the same.

  For example, adding a caching decorator to a database query function
  can save database accesses for popular searches:

  >>> import functools
  >>> @functools.lru_cache(maxsize=300)
  ... def get_phone_number(name):
  ...     c = conn.cursor()
  ...     c.execute('SELECT phonenumber FROM phonelist WHERE name=?', (name,))
  ...     return c.fetchone()[0]

  >>> for name in user_requests:        
  ...     get_phone_number(name)        # cached lookup

  To help with choosing an effective cache size, the wrapped function
  is instrumented for tracking cache statistics:

  >>> get_phone_number.cache_info()     
  CacheInfo(hits=4805, misses=980, maxsize=300, currsize=300)

  If the phonelist table gets updated, the outdated contents of the
  cache can be cleared with:

  >>> get_phone_number.cache_clear()

  (Contributed by Raymond Hettinger and incorporating design ideas
  from Jim Baker, Miki Tebeka, and Nick Coghlan; see recipe 498245,
  recipe 577479, bpo-10586, and bpo-10593.)

* The "functools.wraps()" decorator now adds a "__wrapped__" attribute
  pointing to the original callable function.  This allows wrapped
  functions to be introspected.  It also copies "__annotations__" if
  defined.  And now it also gracefully skips over missing attributes
  such as "__doc__" which might not be defined for the wrapped
  callable.

  In the above example, the cache can be removed by recovering the
  original function:

  >>> get_phone_number = get_phone_number.__wrapped__    # uncached function

  (By Nick Coghlan and Terrence Cole; bpo-9567, bpo-3445, and
  bpo-8814.)

* To help write classes with rich comparison methods, a new decorator
  "functools.total_ordering()" will use existing equality and
  inequality methods to fill in the remaining methods.

  For example, supplying *__eq__* and *__lt__* will enable
  "total_ordering()" to fill-in *__le__*, *__gt__* and *__ge__*:

     @total_ordering
     class Student:
         def __eq__(self, other):
             return ((self.lastname.lower(), self.firstname.lower()) ==
                     (other.lastname.lower(), other.firstname.lower()))

         def __lt__(self, other):
             return ((self.lastname.lower(), self.firstname.lower()) <
                     (other.lastname.lower(), other.firstname.lower()))

  With the *total_ordering* decorator, the remaining comparison
  methods are filled in automatically.

  (Contributed by Raymond Hettinger.)

* To aid in porting programs from Python 2, the
  "functools.cmp_to_key()" function converts an old-style comparison
  function to modern *key function*:

  >>> # locale-aware sort order
  >>> sorted(iterable, key=cmp_to_key(locale.strcoll)) 

  For sorting examples and a brief sorting tutorial, see the Sorting
  HowTo tutorial.

  (Contributed by Raymond Hettinger.)


itertools
---------

* The "itertools" module has a new "accumulate()" function modeled on
  APL's *scan* operator and Numpy's *accumulate* function:

  >>> from itertools import accumulate
  >>> list(accumulate([8, 2, 50]))
  [8, 10, 60]

  >>> prob_dist = [0.1, 0.4, 0.2, 0.3]
  >>> list(accumulate(prob_dist))      # cumulative probability distribution
  [0.1, 0.5, 0.7, 1.0]

  For an example using "accumulate()", see the examples for the random
  module.

  (Contributed by Raymond Hettinger and incorporating design
  suggestions from Mark Dickinson.)


collections
-----------

* The "collections.Counter" class now has two forms of in-place
  subtraction, the existing *-=* operator for saturating subtraction
  and the new "subtract()" method for regular subtraction.  The former
  is suitable for multisets which only have positive counts, and the
  latter is more suitable for use cases that allow negative counts:

  >>> from collections import Counter
  >>> tally = Counter(dogs=5, cats=3)
  >>> tally -= Counter(dogs=2, cats=8)    # saturating subtraction
  >>> tally
  Counter({'dogs': 3})

  >>> tally = Counter(dogs=5, cats=3)
  >>> tally.subtract(dogs=2, cats=8)      # regular subtraction
  >>> tally
  Counter({'dogs': 3, 'cats': -5})

  (Contributed by Raymond Hettinger.)

* The "collections.OrderedDict" class has a new method "move_to_end()"
  which takes an existing key and moves it to either the first or last
  position in the ordered sequence.

  The default is to move an item to the last position.  This is
  equivalent of renewing an entry with "od[k] = od.pop(k)".

  A fast move-to-end operation is useful for resequencing entries.
  For example, an ordered dictionary can be used to track order of
  access by aging entries from the oldest to the most recently
  accessed.

  >>> from collections import OrderedDict
  >>> d = OrderedDict.fromkeys(['a', 'b', 'X', 'd', 'e'])
  >>> list(d)
  ['a', 'b', 'X', 'd', 'e']
  >>> d.move_to_end('X')
  >>> list(d)
  ['a', 'b', 'd', 'e', 'X']

  (Contributed by Raymond Hettinger.)

* The "collections.deque" class grew two new methods "count()" and
  "reverse()" that make them more substitutable for "list" objects:

  >>> from collections import deque
  >>> d = deque('simsalabim')
  >>> d.count('s')
  2
  >>> d.reverse()
  >>> d
  deque(['m', 'i', 'b', 'a', 'l', 'a', 's', 'm', 'i', 's'])

  (Contributed by Raymond Hettinger.)


threading
---------

The "threading" module has a new "Barrier" synchronization class for
making multiple threads wait until all of them have reached a common
barrier point.  Barriers are useful for making sure that a task with
multiple preconditions does not run until all of the predecessor tasks
are complete.

Barriers can work with an arbitrary number of threads.  This is a
generalization of a Rendezvous which is defined for only two threads.

Implemented as a two-phase cyclic barrier, "Barrier" objects are
suitable for use in loops.  The separate *filling* and *draining*
phases assure that all threads get released (drained) before any one
of them can loop back and re-enter the barrier.  The barrier fully
resets after each cycle.

Example of using barriers:

   from threading import Barrier, Thread

   def get_votes(site):
       ballots = conduct_election(site)
       all_polls_closed.wait()        # do not count until all polls are closed
       totals = summarize(ballots)
       publish(site, totals)

   all_polls_closed = Barrier(len(sites))
   for site in sites:
       Thread(target=get_votes, args=(site,)).start()

In this example, the barrier enforces a rule that votes cannot be
counted at any polling site until all polls are closed.  Notice how a
solution with a barrier is similar to one with
"threading.Thread.join()", but the threads stay alive and continue to
do work (summarizing ballots) after the barrier point is crossed.

If any of the predecessor tasks can hang or be delayed, a barrier can
be created with an optional *timeout* parameter.  Then if the timeout
period elapses before all the predecessor tasks reach the barrier
point, all waiting threads are released and a "BrokenBarrierError"
exception is raised:

   def get_votes(site):
       ballots = conduct_election(site)
       try:
           all_polls_closed.wait(timeout=midnight - time.now())
       except BrokenBarrierError:
           lockbox = seal_ballots(ballots)
           queue.put(lockbox)
       else:
           totals = summarize(ballots)
           publish(site, totals)

In this example, the barrier enforces a more robust rule.  If some
election sites do not finish before midnight, the barrier times-out
and the ballots are sealed and deposited in a queue for later
handling.

See Barrier Synchronization Patterns for more examples of how barriers
can be used in parallel computing.  Also, there is a simple but
thorough explanation of barriers in The Little Book of Semaphores,
*section 3.6*.

(Contributed by Kristján Valur Jónsson with an API review by Jeffrey
Yasskin in bpo-8777.)


datetime and time
-----------------

* The "datetime" module has a new type "timezone" that implements the
  "tzinfo" interface by returning a fixed UTC offset and timezone
  name. This makes it easier to create timezone-aware datetime
  objects:

     >>> from datetime import datetime, timezone

     >>> datetime.now(timezone.utc)
     datetime.datetime(2010, 12, 8, 21, 4, 2, 923754, tzinfo=datetime.timezone.utc)

     >>> datetime.strptime("01/01/2000 12:00 +0000", "%m/%d/%Y %H:%M %z")
     datetime.datetime(2000, 1, 1, 12, 0, tzinfo=datetime.timezone.utc)

* Also, "timedelta" objects can now be multiplied by "float" and
  divided by "float" and "int" objects. And "timedelta" objects can
  now divide one another.

* The "datetime.date.strftime()" method is no longer restricted to
  years after 1900.  The new supported year range is from 1000 to 9999
  inclusive.

* Whenever a two-digit year is used in a time tuple, the
  interpretation has been governed by "time.accept2dyear".  The
  default is "True" which means that for a two-digit year, the century
  is guessed according to the POSIX rules governing the "%y" strptime
  format.

  Starting with Py3.2, use of the century guessing heuristic will emit
  a "DeprecationWarning".  Instead, it is recommended that
  "time.accept2dyear" be set to "False" so that large date ranges can
  be used without guesswork:

     >>> import time, warnings
     >>> warnings.resetwarnings()      # remove the default warning filters

     >>> time.accept2dyear = True      # guess whether 11 means 11 or 2011
     >>> time.asctime((11, 1, 1, 12, 34, 56, 4, 1, 0))
     Warning (from warnings module):
       ...
     DeprecationWarning: Century info guessed for a 2-digit year.
     'Fri Jan  1 12:34:56 2011'

     >>> time.accept2dyear = False     # use the full range of allowable dates
     >>> time.asctime((11, 1, 1, 12, 34, 56, 4, 1, 0))
     'Fri Jan  1 12:34:56 11'

  Several functions now have significantly expanded date ranges.  When
  "time.accept2dyear" is false, the "time.asctime()" function will
  accept any year that fits in a C int, while the "time.mktime()" and
  "time.strftime()" functions will accept the full range supported by
  the corresponding operating system functions.

(Contributed by Alexander Belopolsky and Victor Stinner in
bpo-1289118, bpo-5094, bpo-6641, bpo-2706, bpo-1777412, bpo-8013, and
bpo-10827.)


math
----

The "math" module has been updated with six new functions inspired by
the C99 standard.

The "isfinite()" function provides a reliable and fast way to detect
special values.  It returns "True" for regular numbers and "False" for
*Nan* or *Infinity*:

>>> from math import isfinite
>>> [isfinite(x) for x in (123, 4.56, float('Nan'), float('Inf'))]
[True, True, False, False]

The "expm1()" function computes "e**x-1" for small values of *x*
without incurring the loss of precision that usually accompanies the
subtraction of nearly equal quantities:

>>> from math import expm1
>>> expm1(0.013671875)   # more accurate way to compute e**x-1 for a small x
0.013765762467652909

The "erf()" function computes a probability integral or Gaussian error
function.  The complementary error function, "erfc()", is "1 -
erf(x)":

   >>> from math import erf, erfc, sqrt
   >>> erf(1.0/sqrt(2.0))   # portion of normal distribution within 1 standard deviation
   0.682689492137086
   >>> erfc(1.0/sqrt(2.0))  # portion of normal distribution outside 1 standard deviation
   0.31731050786291404
   >>> erf(1.0/sqrt(2.0)) + erfc(1.0/sqrt(2.0))
   1.0

The "gamma()" function is a continuous extension of the factorial
function.  See https://en.wikipedia.org/wiki/Gamma_function for
details.  Because the function is related to factorials, it grows
large even for small values of *x*, so there is also a "lgamma()"
function for computing the natural logarithm of the gamma function:

>>> from math import gamma, lgamma
>>> gamma(7.0)           # six factorial
720.0
>>> lgamma(801.0)        # log(800 factorial)
4551.950730698041

(Contributed by Mark Dickinson.)


abc
---

The "abc" module now supports "abstractclassmethod()" and
"abstractstaticmethod()".

These tools make it possible to define an *abstract base class* that
requires a particular "classmethod()" or "staticmethod()" to be
implemented:

   class Temperature(metaclass=abc.ABCMeta):
       @abc.abstractclassmethod
       def from_fahrenheit(cls, t):
           ...
       @abc.abstractclassmethod
       def from_celsius(cls, t):
           ...

(Patch submitted by Daniel Urban; bpo-5867.)


io
--

The "io.BytesIO" has a new method, "getbuffer()", which provides
functionality similar to "memoryview()".  It creates an editable view
of the data without making a copy.  The buffer's random access and
support for slice notation are well-suited to in-place editing:

   >>> REC_LEN, LOC_START, LOC_LEN = 34, 7, 11

   >>> def change_location(buffer, record_number, location):
   ...     start = record_number * REC_LEN + LOC_START
   ...     buffer[start: start+LOC_LEN] = location

   >>> import io

   >>> byte_stream = io.BytesIO(
   ...     b'G3805  storeroom  Main chassis    '
   ...     b'X7899  shipping   Reserve cog     '
   ...     b'L6988  receiving  Primary sprocket'
   ... )
   >>> buffer = byte_stream.getbuffer()
   >>> change_location(buffer, 1, b'warehouse  ')
   >>> change_location(buffer, 0, b'showroom   ')
   >>> print(byte_stream.getvalue())
   b'G3805  showroom   Main chassis    '
   b'X7899  warehouse  Reserve cog     '
   b'L6988  receiving  Primary sprocket'

(Contributed by Antoine Pitrou in bpo-5506.)


reprlib
-------

When writing a "__repr__()" method for a custom container, it is easy
to forget to handle the case where a member refers back to the
container itself. Python's builtin objects such as "list" and "set"
handle self-reference by displaying "..." in the recursive part of the
representation string.

To help write such "__repr__()" methods, the "reprlib" module has a
new decorator, "recursive_repr()", for detecting recursive calls to
"__repr__()" and substituting a placeholder string instead:

   >>> class MyList(list):
   ...     @recursive_repr()
   ...     def __repr__(self):
   ...         return '<' + '|'.join(map(repr, self)) + '>'
   ...
   >>> m = MyList('abc')
   >>> m.append(m)
   >>> m.append('x')
   >>> print(m)
   <'a'|'b'|'c'|...|'x'>

(Contributed by Raymond Hettinger in bpo-9826 and bpo-9840.)


logging
-------

In addition to dictionary-based configuration described above, the
"logging" package has many other improvements.

The logging documentation has been augmented by a basic tutorial, an
advanced tutorial, and a cookbook of logging recipes.  These documents
are the fastest way to learn about logging.

The "logging.basicConfig()" set-up function gained a *style* argument
to support three different types of string formatting.  It defaults to
"%" for traditional %-formatting, can be set to "{" for the new
"str.format()" style, or can be set to "$" for the shell-style
formatting provided by "string.Template".  The following three
configurations are equivalent:

   >>> from logging import basicConfig
   >>> basicConfig(style='%', format="%(name)s -> %(levelname)s: %(message)s")
   >>> basicConfig(style='{', format="{name} -> {levelname} {message}")
   >>> basicConfig(style='$', format="$name -> $levelname: $message")

If no configuration is set-up before a logging event occurs, there is
now a default configuration using a "StreamHandler" directed to
"sys.stderr" for events of "WARNING" level or higher.  Formerly, an
event occurring before a configuration was set-up would either raise
an exception or silently drop the event depending on the value of
"logging.raiseExceptions".  The new default handler is stored in
"logging.lastResort".

The use of filters has been simplified.  Instead of creating a
"Filter" object, the predicate can be any Python callable that returns
"True" or "False".

There were a number of other improvements that add flexibility and
simplify configuration.  See the module documentation for a full
listing of changes in Python 3.2.


csv
---

The "csv" module now supports a new dialect, "unix_dialect", which
applies quoting for all fields and a traditional Unix style with
"'\n'" as the line terminator.  The registered dialect name is "unix".

The "csv.DictWriter" has a new method, "writeheader()" for writing-out
an initial row to document the field names:

   >>> import csv, sys
   >>> w = csv.DictWriter(sys.stdout, ['name', 'dept'], dialect='unix')
   >>> w.writeheader()
   "name","dept"
   >>> w.writerows([
   ...     {'name': 'tom', 'dept': 'accounting'},
   ...     {'name': 'susan', 'dept': 'Salesl'}])
   "tom","accounting"
   "susan","sales"

(New dialect suggested by Jay Talbot in bpo-5975, and the new method
suggested by Ed Abraham in bpo-1537721.)


contextlib
----------

There is a new and slightly mind-blowing tool "ContextDecorator" that
is helpful for creating a *context manager* that does double duty as a
function decorator.

As a convenience, this new functionality is used by "contextmanager()"
so that no extra effort is needed to support both roles.

The basic idea is that both context managers and function decorators
can be used for pre-action and post-action wrappers.  Context managers
wrap a group of statements using a "with" statement, and function
decorators wrap a group of statements enclosed in a function.  So,
occasionally there is a need to write a pre-action or post-action
wrapper that can be used in either role.

For example, it is sometimes useful to wrap functions or groups of
statements with a logger that can track the time of entry and time of
exit.  Rather than writing both a function decorator and a context
manager for the task, the "contextmanager()" provides both
capabilities in a single definition:

   from contextlib import contextmanager
   import logging

   logging.basicConfig(level=logging.INFO)

   @contextmanager
   def track_entry_and_exit(name):
       logging.info('Entering: %s', name)
       yield
       logging.info('Exiting: %s', name)

Formerly, this would have only been usable as a context manager:

   with track_entry_and_exit('widget loader'):
       print('Some time consuming activity goes here')
       load_widget()

Now, it can be used as a decorator as well:

   @track_entry_and_exit('widget loader')
   def activity():
       print('Some time consuming activity goes here')
       load_widget()

Trying to fulfill two roles at once places some limitations on the
technique. Context managers normally have the flexibility to return an
argument usable by a "with" statement, but there is no parallel for
function decorators.

In the above example, there is not a clean way for the
*track_entry_and_exit* context manager to return a logging instance
for use in the body of enclosed statements.

(Contributed by Michael Foord in bpo-9110.)


decimal and fractions
---------------------

Mark Dickinson crafted an elegant and efficient scheme for assuring
that different numeric datatypes will have the same hash value
whenever their actual values are equal (bpo-8188):

   assert hash(Fraction(3, 2)) == hash(1.5) == \
          hash(Decimal("1.5")) == hash(complex(1.5, 0))

Some of the hashing details are exposed through a new attribute,
"sys.hash_info", which describes the bit width of the hash value, the
prime modulus, the hash values for *infinity* and *nan*, and the
multiplier used for the imaginary part of a number:

>>> sys.hash_info 
sys.hash_info(width=64, modulus=2305843009213693951, inf=314159, nan=0, imag=1000003)

An early decision to limit the inter-operability of various numeric
types has been relaxed.  It is still unsupported (and ill-advised) to
have implicit mixing in arithmetic expressions such as "Decimal('1.1')
+ float('1.1')" because the latter loses information in the process of
constructing the binary float.  However, since existing floating point
value can be converted losslessly to either a decimal or rational
representation, it makes sense to add them to the constructor and to
support mixed-type comparisons.

* The "decimal.Decimal" constructor now accepts "float" objects
  directly so there in no longer a need to use the "from_float()"
  method (bpo-8257).

* Mixed type comparisons are now fully supported so that "Decimal"
  objects can be directly compared with "float" and
  "fractions.Fraction" (bpo-2531 and bpo-8188).

Similar changes were made to "fractions.Fraction" so that the
"from_float()" and "from_decimal()" methods are no longer needed
(bpo-8294):

>>> from decimal import Decimal
>>> from fractions import Fraction
>>> Decimal(1.1)
Decimal('1.100000000000000088817841970012523233890533447265625')
>>> Fraction(1.1)
Fraction(2476979795053773, 2251799813685248)

Another useful change for the "decimal" module is that the
"Context.clamp" attribute is now public.  This is useful in creating
contexts that correspond to the decimal interchange formats specified
in IEEE 754 (see bpo-8540).

(Contributed by Mark Dickinson and Raymond Hettinger.)


ftp
---

The "ftplib.FTP" class now supports the context management protocol to
unconditionally consume "socket.error" exceptions and to close the FTP
connection when done:

   >>> from ftplib import FTP
   >>> with FTP("ftp1.at.proftpd.org") as ftp:
           ftp.login()
           ftp.dir()

   '230 Anonymous login ok, restrictions apply.'
   dr-xr-xr-x   9 ftp      ftp           154 May  6 10:43 .
   dr-xr-xr-x   9 ftp      ftp           154 May  6 10:43 ..
   dr-xr-xr-x   5 ftp      ftp          4096 May  6 10:43 CentOS
   dr-xr-xr-x   3 ftp      ftp            18 Jul 10  2008 Fedora

Other file-like objects such as "mmap.mmap" and "fileinput.input()"
also grew auto-closing context managers:

   with fileinput.input(files=('log1.txt', 'log2.txt')) as f:
       for line in f:
           process(line)

(Contributed by Tarek Ziadé and Giampaolo Rodolà in bpo-4972, and by
Georg Brandl in bpo-8046 and bpo-1286.)

The "FTP_TLS" class now accepts a *context* parameter, which is a
"ssl.SSLContext" object allowing bundling SSL configuration options,
certificates and private keys into a single (potentially long-lived)
structure.

(Contributed by Giampaolo Rodolà; bpo-8806.)


popen
-----

The "os.popen()" and "subprocess.Popen()" functions now support "with"
statements for auto-closing of the file descriptors.

(Contributed by Antoine Pitrou and Brian Curtin in bpo-7461 and
bpo-10554.)


select
------

The "select" module now exposes a new, constant attribute, "PIPE_BUF",
which gives the minimum number of bytes which are guaranteed not to
block when "select.select()" says a pipe is ready for writing.

>>> import select
>>> select.PIPE_BUF  
512

(Available on Unix systems. Patch by Sébastien Sablé in bpo-9862)


gzip and zipfile
----------------

"gzip.GzipFile" now implements the "io.BufferedIOBase" *abstract base
class* (except for "truncate()").  It also has a "peek()" method and
supports unseekable as well as zero-padded file objects.

The "gzip" module also gains the "compress()" and "decompress()"
functions for easier in-memory compression and decompression.  Keep in
mind that text needs to be encoded as "bytes" before compressing and
decompressing:

>>> import gzip
>>> s = 'Three shall be the number thou shalt count, '
>>> s += 'and the number of the counting shall be three'
>>> b = s.encode()                        # convert to utf-8
>>> len(b)
89
>>> c = gzip.compress(b)
>>> len(c)
77
>>> gzip.decompress(c).decode()[:42]      # decompress and convert to text
'Three shall be the number thou shalt count'

(Contributed by Anand B. Pillai in bpo-3488; and by Antoine Pitrou,
Nir Aides and Brian Curtin in bpo-9962, bpo-1675951, bpo-7471 and
bpo-2846.)

Also, the "zipfile.ZipExtFile" class was reworked internally to
represent files stored inside an archive.  The new implementation is
significantly faster and can be wrapped in an "io.BufferedReader"
object for more speedups.  It also solves an issue where interleaved
calls to *read* and *readline* gave the wrong results.

(Patch submitted by Nir Aides in bpo-7610.)


tarfile
-------

The "TarFile" class can now be used as a context manager.  In
addition, its "add()" method has a new option, *filter*, that controls
which files are added to the archive and allows the file metadata to
be edited.

The new *filter* option replaces the older, less flexible *exclude*
parameter which is now deprecated.  If specified, the optional
*filter* parameter needs to be a *keyword argument*.  The user-
supplied filter function accepts a "TarInfo" object and returns an
updated "TarInfo" object, or if it wants the file to be excluded, the
function can return "None":

   >>> import tarfile, glob

   >>> def myfilter(tarinfo):
   ...     if tarinfo.isfile():             # only save real files
   ...         tarinfo.uname = 'monty'      # redact the user name
   ...         return tarinfo

   >>> with tarfile.open(name='myarchive.tar.gz', mode='w:gz') as tf:
   ...     for filename in glob.glob('*.txt'):
   ...         tf.add(filename, filter=myfilter)
   ...     tf.list()
   -rw-r--r-- monty/501        902 2011-01-26 17:59:11 annotations.txt
   -rw-r--r-- monty/501        123 2011-01-26 17:59:11 general_questions.txt
   -rw-r--r-- monty/501       3514 2011-01-26 17:59:11 prion.txt
   -rw-r--r-- monty/501        124 2011-01-26 17:59:11 py_todo.txt
   -rw-r--r-- monty/501       1399 2011-01-26 17:59:11 semaphore_notes.txt

(Proposed by Tarek Ziadé and implemented by Lars Gustäbel in
bpo-6856.)


hashlib
-------

The "hashlib" module has two new constant attributes listing the
hashing algorithms guaranteed to be present in all implementations and
those available on the current implementation:

   >>> import hashlib

   >>> hashlib.algorithms_guaranteed
   {'sha1', 'sha224', 'sha384', 'sha256', 'sha512', 'md5'}

   >>> hashlib.algorithms_available
   {'md2', 'SHA256', 'SHA512', 'dsaWithSHA', 'mdc2', 'SHA224', 'MD4', 'sha256',
   'sha512', 'ripemd160', 'SHA1', 'MDC2', 'SHA', 'SHA384', 'MD2',
   'ecdsa-with-SHA1','md4', 'md5', 'sha1', 'DSA-SHA', 'sha224',
   'dsaEncryption', 'DSA', 'RIPEMD160', 'sha', 'MD5', 'sha384'}

(Suggested by Carl Chenet in bpo-7418.)


ast
---

The "ast" module has a wonderful a general-purpose tool for safely
evaluating expression strings using the Python literal syntax.  The
"ast.literal_eval()" function serves as a secure alternative to the
builtin "eval()" function which is easily abused.  Python 3.2 adds
"bytes" and "set" literals to the list of supported types: strings,
bytes, numbers, tuples, lists, dicts, sets, booleans, and "None".

   >>> from ast import literal_eval

   >>> request = "{'req': 3, 'func': 'pow', 'args': (2, 0.5)}"
   >>> literal_eval(request)
   {'args': (2, 0.5), 'req': 3, 'func': 'pow'}

   >>> request = "os.system('do something harmful')"
   >>> literal_eval(request)
   Traceback (most recent call last):
     ...
   ValueError: malformed node or string: <_ast.Call object at 0x101739a10>

(Implemented by Benjamin Peterson and Georg Brandl.)


os
--

Different operating systems use various encodings for filenames and
environment variables.  The "os" module provides two new functions,
"fsencode()" and "fsdecode()", for encoding and decoding filenames:

>>> import os
>>> filename = 'Sehenswürdigkeiten'
>>> os.fsencode(filename)
b'Sehensw\xc3\xbcrdigkeiten'

Some operating systems allow direct access to encoded bytes in the
environment.  If so, the "os.supports_bytes_environ" constant will be
true.

For direct access to encoded environment variables (if available), use
the new "os.getenvb()" function or use "os.environb" which is a bytes
version of "os.environ".

(Contributed by Victor Stinner.)


shutil
------

The "shutil.copytree()" function has two new options:

* *ignore_dangling_symlinks*: when "symlinks=False" so that the
  function copies a file pointed to by a symlink, not the symlink
  itself. This option will silence the error raised if the file
  doesn't exist.

* *copy_function*: is a callable that will be used to copy files.
  "shutil.copy2()" is used by default.

(Contributed by Tarek Ziadé.)

In addition, the "shutil" module now supports archiving operations for
zipfiles, uncompressed tarfiles, gzipped tarfiles, and bzipped
tarfiles.  And there are functions for registering additional
archiving file formats (such as xz compressed tarfiles or custom
formats).

The principal functions are "make_archive()" and "unpack_archive()".
By default, both operate on the current directory (which can be set by
"os.chdir()") and on any sub-directories. The archive filename needs
to be specified with a full pathname.  The archiving step is non-
destructive (the original files are left unchanged).

   >>> import shutil, pprint

   >>> os.chdir('mydata')  # change to the source directory
   >>> f = shutil.make_archive('/var/backup/mydata',
   ...                         'zip')      # archive the current directory
   >>> f                                   # show the name of archive
   '/var/backup/mydata.zip'
   >>> os.chdir('tmp')                     # change to an unpacking
   >>> shutil.unpack_archive('/var/backup/mydata.zip')  # recover the data

   >>> pprint.pprint(shutil.get_archive_formats())  # display known formats
   [('bztar', "bzip2'ed tar-file"),
    ('gztar', "gzip'ed tar-file"),
    ('tar', 'uncompressed tar file'),
    ('zip', 'ZIP file')]

   >>> shutil.register_archive_format(     # register a new archive format
   ...     name='xz',
   ...     function=xz.compress,           # callable archiving function
   ...     extra_args=[('level', 8)],      # arguments to the function
   ...     description='xz compression'
   ... )

(Contributed by Tarek Ziadé.)


sqlite3
-------

The "sqlite3" module was updated to pysqlite version 2.6.0.  It has
two new capabilities.

* The "sqlite3.Connection.in_transit" attribute is true if there is an
  active transaction for uncommitted changes.

* The "sqlite3.Connection.enable_load_extension()" and
  "sqlite3.Connection.load_extension()" methods allows you to load
  SQLite extensions from ".so" files.  One well-known extension is the
  fulltext-search extension distributed with SQLite.

(Contributed by R. David Murray and Shashwat Anand; bpo-8845.)


html
----

A new "html" module was introduced with only a single function,
"escape()", which is used for escaping reserved characters from HTML
markup:

>>> import html
>>> html.escape('x > 2 && x < 7')
'x &gt; 2 &amp;&amp; x &lt; 7'


socket
------

The "socket" module has two new improvements.

* Socket objects now have a "detach()" method which puts the socket
  into closed state without actually closing the underlying file
  descriptor.  The latter can then be reused for other purposes.
  (Added by Antoine Pitrou; bpo-8524.)

* "socket.create_connection()" now supports the context management
  protocol to unconditionally consume "socket.error" exceptions and to
  close the socket when done. (Contributed by Giampaolo Rodolà;
  bpo-9794.)


ssl
---

The "ssl" module added a number of features to satisfy common
requirements for secure (encrypted, authenticated) internet
connections:

* A new class, "SSLContext", serves as a container for persistent SSL
  data, such as protocol settings, certificates, private keys, and
  various other options. It includes a "wrap_socket()" for creating an
  SSL socket from an SSL context.

* A new function, "ssl.match_hostname()", supports server identity
  verification for higher-level protocols by implementing the rules of
  HTTPS (from **RFC 2818**) which are also suitable for other
  protocols.

* The "ssl.wrap_socket()" constructor function now takes a *ciphers*
  argument.  The *ciphers* string lists the allowed encryption
  algorithms using the format described in the OpenSSL documentation.

* When linked against recent versions of OpenSSL, the "ssl" module now
  supports the Server Name Indication extension to the TLS protocol,
  allowing multiple "virtual hosts" using different certificates on a
  single IP port. This extension is only supported in client mode, and
  is activated by passing the *server_hostname* argument to
  "ssl.SSLContext.wrap_socket()".

* Various options have been added to the "ssl" module, such as
  "OP_NO_SSLv2" which disables the insecure and obsolete SSLv2
  protocol.

* The extension now loads all the OpenSSL ciphers and digest
  algorithms.  If some SSL certificates cannot be verified, they are
  reported as an "unknown algorithm" error.

* The version of OpenSSL being used is now accessible using the module
  attributes "ssl.OPENSSL_VERSION" (a string),
  "ssl.OPENSSL_VERSION_INFO" (a 5-tuple), and
  "ssl.OPENSSL_VERSION_NUMBER" (an integer).

(Contributed by Antoine Pitrou in bpo-8850, bpo-1589, bpo-8322,
bpo-5639, bpo-4870, bpo-8484, and bpo-8321.)


nntp
----

The "nntplib" module has a revamped implementation with better bytes
and text semantics as well as more practical APIs.  These improvements
break compatibility with the nntplib version in Python 3.1, which was
partly dysfunctional in itself.

Support for secure connections through both implicit (using
"nntplib.NNTP_SSL") and explicit (using "nntplib.NNTP.starttls()") TLS
has also been added.

(Contributed by Antoine Pitrou in bpo-9360 and Andrew Vant in
bpo-1926.)


certificates
------------

"http.client.HTTPSConnection", "urllib.request.HTTPSHandler" and
"urllib.request.urlopen()" now take optional arguments to allow for
server certificate checking against a set of Certificate Authorities,
as recommended in public uses of HTTPS.

(Added by Antoine Pitrou, bpo-9003.)


imaplib
-------

Support for explicit TLS on standard IMAP4 connections has been added
through the new "imaplib.IMAP4.starttls" method.

(Contributed by Lorenzo M. Catucci and Antoine Pitrou, bpo-4471.)


http.client
-----------

There were a number of small API improvements in the "http.client"
module. The old-style HTTP 0.9 simple responses are no longer
supported and the *strict* parameter is deprecated in all classes.

The "HTTPConnection" and "HTTPSConnection" classes now have a
*source_address* parameter for a (host, port) tuple indicating where
the HTTP connection is made from.

Support for certificate checking and HTTPS virtual hosts were added to
"HTTPSConnection".

The "request()" method on connection objects allowed an optional
*body* argument so that a *file object* could be used to supply the
content of the request.  Conveniently, the *body* argument now also
accepts an *iterable* object so long as it includes an explicit
"Content-Length" header.  This extended interface is much more
flexible than before.

To establish an HTTPS connection through a proxy server, there is a
new "set_tunnel()" method that sets the host and port for HTTP Connect
tunneling.

To match the behavior of "http.server", the HTTP client library now
also encodes headers with ISO-8859-1 (Latin-1) encoding.  It was
already doing that for incoming headers, so now the behavior is
consistent for both incoming and outgoing traffic. (See work by Armin
Ronacher in bpo-10980.)


unittest
--------

The unittest module has a number of improvements supporting test
discovery for packages, easier experimentation at the interactive
prompt, new testcase methods, improved diagnostic messages for test
failures, and better method names.

* The command-line call "python -m unittest" can now accept file paths
  instead of module names for running specific tests (bpo-10620).  The
  new test discovery can find tests within packages, locating any test
  importable from the top-level directory.  The top-level directory
  can be specified with the "-t" option, a pattern for matching files
  with "-p", and a directory to start discovery with "-s":

     $ python -m unittest discover -s my_proj_dir -p _test.py

  (Contributed by Michael Foord.)

* Experimentation at the interactive prompt is now easier because the
  "unittest.case.TestCase" class can now be instantiated without
  arguments:

  >>> from unittest import TestCase
  >>> TestCase().assertEqual(pow(2, 3), 8)

  (Contributed by Michael Foord.)

* The "unittest" module has two new methods, "assertWarns()" and
  "assertWarnsRegex()" to verify that a given warning type is
  triggered by the code under test:

     with self.assertWarns(DeprecationWarning):
         legacy_function('XYZ')

  (Contributed by Antoine Pitrou, bpo-9754.)

  Another new method, "assertCountEqual()" is used to compare two
  iterables to determine if their element counts are equal (whether
  the same elements are present with the same number of occurrences
  regardless of order):

     def test_anagram(self):
         self.assertCountEqual('algorithm', 'logarithm')

  (Contributed by Raymond Hettinger.)

* A principal feature of the unittest module is an effort to produce
  meaningful diagnostics when a test fails.  When possible, the
  failure is recorded along with a diff of the output.  This is
  especially helpful for analyzing log files of failed test runs.
  However, since diffs can sometime be voluminous, there is a new
  "maxDiff" attribute that sets maximum length of diffs displayed.

* In addition, the method names in the module have undergone a number
  of clean-ups.

  For example, "assertRegex()" is the new name for
  "assertRegexpMatches()" which was misnamed because the test uses
  "re.search()", not "re.match()".  Other methods using regular
  expressions are now named using short form "Regex" in preference to
  "Regexp" -- this matches the names used in other unittest
  implementations, matches Python's old name for the "re" module, and
  it has unambiguous camel-casing.

  (Contributed by Raymond Hettinger and implemented by Ezio Melotti.)

* To improve consistency, some long-standing method aliases are being
  deprecated in favor of the preferred names:

     +---------------------------------+--------------------------------+
     | Old Name                        | Preferred Name                 |
     |=================================|================================|
     | "assert_()"                     | "assertTrue()"                 |
     +---------------------------------+--------------------------------+
     | "assertEquals()"                | "assertEqual()"                |
     +---------------------------------+--------------------------------+
     | "assertNotEquals()"             | "assertNotEqual()"             |
     +---------------------------------+--------------------------------+
     | "assertAlmostEquals()"          | "assertAlmostEqual()"          |
     +---------------------------------+--------------------------------+
     | "assertNotAlmostEquals()"       | "assertNotAlmostEqual()"       |
     +---------------------------------+--------------------------------+

  Likewise, the "TestCase.fail*" methods deprecated in Python 3.1 are
  expected to be removed in Python 3.3.  Also see the Deprecated
  aliases section in the "unittest" documentation.

  (Contributed by Ezio Melotti; bpo-9424.)

* The "assertDictContainsSubset()" method was deprecated because it
  was misimplemented with the arguments in the wrong order.  This
  created hard-to-debug optical illusions where tests like
  "TestCase().assertDictContainsSubset({'a':1, 'b':2}, {'a':1})" would
  fail.

  (Contributed by Raymond Hettinger.)


random
------

The integer methods in the "random" module now do a better job of
producing uniform distributions.  Previously, they computed selections
with "int(n*random())" which had a slight bias whenever *n* was not a
power of two. Now, multiple selections are made from a range up to the
next power of two and a selection is kept only when it falls within
the range "0 <= x < n".  The functions and methods affected are
"randrange()", "randint()", "choice()", "shuffle()" and "sample()".

(Contributed by Raymond Hettinger; bpo-9025.)


poplib
------

"POP3_SSL" class now accepts a *context* parameter, which is a
"ssl.SSLContext" object allowing bundling SSL configuration options,
certificates and private keys into a single (potentially long-lived)
structure.

(Contributed by Giampaolo Rodolà; bpo-8807.)


asyncore
--------

"asyncore.dispatcher" now provides a "handle_accepted()" method
returning a "(sock, addr)" pair which is called when a connection has
actually been established with a new remote endpoint. This is supposed
to be used as a replacement for old "handle_accept()" and avoids the
user  to call "accept()" directly.

(Contributed by Giampaolo Rodolà; bpo-6706.)


tempfile
--------

The "tempfile" module has a new context manager, "TemporaryDirectory"
which provides easy deterministic cleanup of temporary directories:

   with tempfile.TemporaryDirectory() as tmpdirname:
       print('created temporary dir:', tmpdirname)

(Contributed by Neil Schemenauer and Nick Coghlan; bpo-5178.)


inspect
-------

* The "inspect" module has a new function "getgeneratorstate()" to
  easily identify the current state of a generator-iterator:

     >>> from inspect import getgeneratorstate
     >>> def gen():
     ...     yield 'demo'
     >>> g = gen()
     >>> getgeneratorstate(g)
     'GEN_CREATED'
     >>> next(g)
     'demo'
     >>> getgeneratorstate(g)
     'GEN_SUSPENDED'
     >>> next(g, None)
     >>> getgeneratorstate(g)
     'GEN_CLOSED'

  (Contributed by Rodolpho Eckhardt and Nick Coghlan, bpo-10220.)

* To support lookups without the possibility of activating a dynamic
  attribute, the "inspect" module has a new function,
  "getattr_static()". Unlike "hasattr()", this is a true read-only
  search, guaranteed not to change state while it is searching:

     >>> class A:
     ...     @property
     ...     def f(self):
     ...         print('Running')
     ...         return 10
     ...
     >>> a = A()
     >>> getattr(a, 'f')
     Running
     10
     >>> inspect.getattr_static(a, 'f')
     <property object at 0x1022bd788>

   (Contributed by Michael Foord.)


pydoc
-----

The "pydoc" module now provides a much-improved web server interface,
as well as a new command-line option "-b" to automatically open a
browser window to display that server:

   $ pydoc3.2 -b

(Contributed by Ron Adam; bpo-2001.)


dis
---

The "dis" module gained two new functions for inspecting code,
"code_info()" and "show_code()".  Both provide detailed code object
information for the supplied function, method, source code string or
code object.  The former returns a string and the latter prints it:

   >>> import dis, random
   >>> dis.show_code(random.choice)
   Name:              choice
   Filename:          /Library/Frameworks/Python.framework/Versions/3.2/lib/python3.2/random.py
   Argument count:    2
   Kw-only arguments: 0
   Number of locals:  3
   Stack size:        11
   Flags:             OPTIMIZED, NEWLOCALS, NOFREE
   Constants:
      0: 'Choose a random element from a non-empty sequence.'
      1: 'Cannot choose from an empty sequence'
   Names:
      0: _randbelow
      1: len
      2: ValueError
      3: IndexError
   Variable names:
      0: self
      1: seq
      2: i

In addition, the "dis()" function now accepts string arguments so that
the common idiom "dis(compile(s, '', 'eval'))" can be shortened to
"dis(s)":

   >>> dis('3*x+1 if x%2==1 else x//2')
     1           0 LOAD_NAME                0 (x)
                 3 LOAD_CONST               0 (2)
                 6 BINARY_MODULO
                 7 LOAD_CONST               1 (1)
                10 COMPARE_OP               2 (==)
                13 POP_JUMP_IF_FALSE       28
                16 LOAD_CONST               2 (3)
                19 LOAD_NAME                0 (x)
                22 BINARY_MULTIPLY
                23 LOAD_CONST               1 (1)
                26 BINARY_ADD
                27 RETURN_VALUE
           >>   28 LOAD_NAME                0 (x)
                31 LOAD_CONST               0 (2)
                34 BINARY_FLOOR_DIVIDE
                35 RETURN_VALUE

Taken together, these improvements make it easier to explore how
CPython is implemented and to see for yourself what the language
syntax does under-the-hood.

(Contributed by Nick Coghlan in bpo-9147.)


dbm
---

All database modules now support the "get()" and "setdefault()"
methods.

(Suggested by Ray Allen in bpo-9523.)


ctypes
------

A new type, "ctypes.c_ssize_t" represents the C "ssize_t" datatype.


site
----

The "site" module has three new functions useful for reporting on the
details of a given Python installation.

* "getsitepackages()" lists all global site-packages directories.

* "getuserbase()" reports on the user's base directory where data can
  be stored.

* "getusersitepackages()" reveals the user-specific site-packages
  directory path.

   >>> import site
   >>> site.getsitepackages()
   ['/Library/Frameworks/Python.framework/Versions/3.2/lib/python3.2/site-packages',
    '/Library/Frameworks/Python.framework/Versions/3.2/lib/site-python',
    '/Library/Python/3.2/site-packages']
   >>> site.getuserbase()
   '/Users/raymondhettinger/Library/Python/3.2'
   >>> site.getusersitepackages()
   '/Users/raymondhettinger/Library/Python/3.2/lib/python/site-packages'

Conveniently, some of site's functionality is accessible directly from
the command-line:

   $ python -m site --user-base
   /Users/raymondhettinger/.local
   $ python -m site --user-site
   /Users/raymondhettinger/.local/lib/python3.2/site-packages

(Contributed by Tarek Ziadé in bpo-6693.)


sysconfig
---------

The new "sysconfig" module makes it straightforward to discover
installation paths and configuration variables that vary across
platforms and installations.

The module offers access simple access functions for platform and
version information:

* "get_platform()" returning values like *linux-i586* or
  *macosx-10.6-ppc*.

* "get_python_version()" returns a Python version string such as
  "3.2".

It also provides access to the paths and variables corresponding to
one of seven named schemes used by "distutils".  Those include
*posix_prefix*, *posix_home*, *posix_user*, *nt*, *nt_user*, *os2*,
*os2_home*:

* "get_paths()" makes a dictionary containing installation paths for
  the current installation scheme.

* "get_config_vars()" returns a dictionary of platform specific
  variables.

There is also a convenient command-line interface:

   C:\Python32>python -m sysconfig
   Platform: "win32"
   Python version: "3.2"
   Current installation scheme: "nt"

   Paths:
           data = "C:\Python32"
           include = "C:\Python32\Include"
           platinclude = "C:\Python32\Include"
           platlib = "C:\Python32\Lib\site-packages"
           platstdlib = "C:\Python32\Lib"
           purelib = "C:\Python32\Lib\site-packages"
           scripts = "C:\Python32\Scripts"
           stdlib = "C:\Python32\Lib"

   Variables:
           BINDIR = "C:\Python32"
           BINLIBDEST = "C:\Python32\Lib"
           EXE = ".exe"
           INCLUDEPY = "C:\Python32\Include"
           LIBDEST = "C:\Python32\Lib"
           SO = ".pyd"
           VERSION = "32"
           abiflags = ""
           base = "C:\Python32"
           exec_prefix = "C:\Python32"
           platbase = "C:\Python32"
           prefix = "C:\Python32"
           projectbase = "C:\Python32"
           py_version = "3.2"
           py_version_nodot = "32"
           py_version_short = "3.2"
           srcdir = "C:\Python32"
           userbase = "C:\Documents and Settings\Raymond\Application Data\Python"

(Moved out of Distutils by Tarek Ziadé.)


pdb
---

The "pdb" debugger module gained a number of usability improvements:

* "pdb.py" now has a "-c" option that executes commands as given in a
  ".pdbrc" script file.

* A ".pdbrc" script file can contain "continue" and "next" commands
  that continue debugging.

* The "Pdb" class constructor now accepts a *nosigint* argument.

* New commands: "l(list)", "ll(long list)" and "source" for listing
  source code.

* New commands: "display" and "undisplay" for showing or hiding the
  value of an expression if it has changed.

* New command: "interact" for starting an interactive interpreter
  containing the global and local  names found in the current scope.

* Breakpoints can be cleared by breakpoint number.

(Contributed by Georg Brandl, Antonio Cuni and Ilya Sandler.)


configparser
------------

The "configparser" module was modified to improve usability and
predictability of the default parser and its supported INI syntax.
The old "ConfigParser" class was removed in favor of
"SafeConfigParser" which has in turn been renamed to "ConfigParser".
Support for inline comments is now turned off by default and section
or option duplicates are not allowed in a single configuration source.

Config parsers gained a new API based on the mapping protocol:

   >>> parser = ConfigParser()
   >>> parser.read_string("""
   ... [DEFAULT]
   ... location = upper left
   ... visible = yes
   ... editable = no
   ... color = blue
   ...
   ... [main]
   ... title = Main Menu
   ... color = green
   ...
   ... [options]
   ... title = Options
   ... """)
   >>> parser['main']['color']
   'green'
   >>> parser['main']['editable']
   'no'
   >>> section = parser['options']
   >>> section['title']
   'Options'
   >>> section['title'] = 'Options (editable: %(editable)s)'
   >>> section['title']
   'Options (editable: no)'

The new API is implemented on top of the classical API, so custom
parser subclasses should be able to use it without modifications.

The INI file structure accepted by config parsers can now be
customized. Users can specify alternative option/value delimiters and
comment prefixes, change the name of the *DEFAULT* section or switch
the interpolation syntax.

There is support for pluggable interpolation including an additional
interpolation handler "ExtendedInterpolation":

   >>> parser = ConfigParser(interpolation=ExtendedInterpolation())
   >>> parser.read_dict({'buildout': {'directory': '/home/ambv/zope9'},
   ...                   'custom': {'prefix': '/usr/local'}})
   >>> parser.read_string("""
   ... [buildout]
   ... parts =
   ...   zope9
   ...   instance
   ... find-links =
   ...   ${buildout:directory}/downloads/dist
   ...
   ... [zope9]
   ... recipe = plone.recipe.zope9install
   ... location = /opt/zope
   ...
   ... [instance]
   ... recipe = plone.recipe.zope9instance
   ... zope9-location = ${zope9:location}
   ... zope-conf = ${custom:prefix}/etc/zope.conf
   ... """)
   >>> parser['buildout']['find-links']
   '\n/home/ambv/zope9/downloads/dist'
   >>> parser['instance']['zope-conf']
   '/usr/local/etc/zope.conf'
   >>> instance = parser['instance']
   >>> instance['zope-conf']
   '/usr/local/etc/zope.conf'
   >>> instance['zope9-location']
   '/opt/zope'

A number of smaller features were also introduced, like support for
specifying encoding in read operations, specifying fallback values for
get-functions, or reading directly from dictionaries and strings.

(All changes contributed by Łukasz Langa.)


urllib.parse
------------

A number of usability improvements were made for the "urllib.parse"
module.

The "urlparse()" function now supports IPv6 addresses as described in
**RFC 2732**:

>>> import urllib.parse
>>> urllib.parse.urlparse('http://[dead:beef:cafe:5417:affe:8FA3:deaf:feed]/foo/') 
ParseResult(scheme='http',
            netloc='[dead:beef:cafe:5417:affe:8FA3:deaf:feed]',
            path='/foo/',
            params='',
            query='',
            fragment='')

The "urldefrag()" function now returns a *named tuple*:

   >>> r = urllib.parse.urldefrag('http://python.org/about/#target')
   >>> r
   DefragResult(url='http://python.org/about/', fragment='target')
   >>> r[0]
   'http://python.org/about/'
   >>> r.fragment
   'target'

And, the "urlencode()" function is now much more flexible, accepting
either a string or bytes type for the *query* argument.  If it is a
string, then the *safe*, *encoding*, and *error* parameters are sent
to "quote_plus()" for encoding:

   >>> urllib.parse.urlencode([
   ...      ('type', 'telenovela'),
   ...      ('name', '¿Dónde Está Elisa?')],
   ...      encoding='latin-1')
   'type=telenovela&name=%BFD%F3nde+Est%E1+Elisa%3F'

As detailed in Parsing ASCII Encoded Bytes, all the "urllib.parse"
functions now accept ASCII-encoded byte strings as input, so long as
they are not mixed with regular strings.  If ASCII-encoded byte
strings are given as parameters, the return types will also be an
ASCII-encoded byte strings:

>>> urllib.parse.urlparse(b'http://www.python.org:80/about/') 
ParseResultBytes(scheme=b'http', netloc=b'www.python.org:80',
                 path=b'/about/', params=b'', query=b'', fragment=b'')

(Work by Nick Coghlan, Dan Mahn, and Senthil Kumaran in bpo-2987,
bpo-5468, and bpo-9873.)


mailbox
-------

Thanks to a concerted effort by R. David Murray, the "mailbox" module
has been fixed for Python 3.2.  The challenge was that mailbox had
been originally designed with a text interface, but email messages are
best represented with "bytes" because various parts of a message may
have different encodings.

The solution harnessed the "email" package's binary support for
parsing arbitrary email messages.  In addition, the solution required
a number of API changes.

As expected, the "add()" method for "mailbox.Mailbox" objects now
accepts binary input.

"StringIO" and text file input are deprecated.  Also, string input
will fail early if non-ASCII characters are used.  Previously it would
fail when the email was processed in a later step.

There is also support for binary output.  The "get_file()" method now
returns a file in the binary mode (where it used to incorrectly set
the file to text-mode).  There is also a new "get_bytes()" method that
returns a "bytes" representation of a message corresponding to a given
*key*.

It is still possible to get non-binary output using the old API's
"get_string()" method, but that approach is not very useful.  Instead,
it is best to extract messages from a "Message" object or to load them
from binary input.

(Contributed by R. David Murray, with efforts from Steffen Daode
Nurpmeso and an initial patch by Victor Stinner in bpo-9124.)


turtledemo
----------

The demonstration code for the "turtle" module was moved from the
*Demo* directory to main library.  It includes over a dozen sample
scripts with lively displays.  Being on "sys.path", it can now be run
directly from the command-line:

   $ python -m turtledemo

(Moved from the Demo directory by Alexander Belopolsky in bpo-10199.)


Multi-threading
===============

* The mechanism for serializing execution of concurrently running
  Python threads (generally known as the *GIL* or Global Interpreter
  Lock) has been rewritten.  Among the objectives were more
  predictable switching intervals and reduced overhead due to lock
  contention and the number of ensuing system calls.  The notion of a
  "check interval" to allow thread switches has been abandoned and
  replaced by an absolute duration expressed in seconds.  This
  parameter is tunable through "sys.setswitchinterval()". It currently
  defaults to 5 milliseconds.

  Additional details about the implementation can be read from a
  python-dev mailing-list message (however, "priority requests" as
  exposed in this message have not been kept for inclusion).

  (Contributed by Antoine Pitrou.)

* Regular and recursive locks now accept an optional *timeout*
  argument to their "acquire()" method.  (Contributed by Antoine
  Pitrou; bpo-7316.)

* Similarly, "threading.Semaphore.acquire()" also gained a *timeout*
  argument.  (Contributed by Torsten Landschoff; bpo-850728.)

* Regular and recursive lock acquisitions can now be interrupted by
  signals on platforms using Pthreads.  This means that Python
  programs that deadlock while acquiring locks can be successfully
  killed by repeatedly sending SIGINT to the process (by pressing
  "Ctrl+C" in most shells). (Contributed by Reid Kleckner; bpo-8844.)


Optimizations
=============

A number of small performance enhancements have been added:

* Python's peephole optimizer now recognizes patterns such "x in {1,
  2, 3}" as being a test for membership in a set of constants.  The
  optimizer recasts the "set" as a "frozenset" and stores the pre-
  built constant.

  Now that the speed penalty is gone, it is practical to start writing
  membership tests using set-notation.  This style is both
  semantically clear and operationally fast:

     extension = name.rpartition('.')[2]
     if extension in {'xml', 'html', 'xhtml', 'css'}:
         handle(name)

  (Patch and additional tests contributed by Dave Malcolm; bpo-6690).

* Serializing and unserializing data using the "pickle" module is now
  several times faster.

  (Contributed by Alexandre Vassalotti, Antoine Pitrou and the Unladen
  Swallow team in bpo-9410 and bpo-3873.)

* The Timsort algorithm used in "list.sort()" and "sorted()" now runs
  faster and uses less memory when called with a *key function*.
  Previously, every element of a list was wrapped with a temporary
  object that remembered the key value associated with each element.
  Now, two arrays of keys and values are sorted in parallel.  This
  saves the memory consumed by the sort wrappers, and it saves time
  lost to delegating comparisons.

  (Patch by Daniel Stutzbach in bpo-9915.)

* JSON decoding performance is improved and memory consumption is
  reduced whenever the same string is repeated for multiple keys.
  Also, JSON encoding now uses the C speedups when the "sort_keys"
  argument is true.

  (Contributed by Antoine Pitrou in bpo-7451 and by Raymond Hettinger
  and Antoine Pitrou in bpo-10314.)

* Recursive locks (created with the "threading.RLock()" API) now
  benefit from a C implementation which makes them as fast as regular
  locks, and between 10x and 15x faster than their previous pure
  Python implementation.

  (Contributed by Antoine Pitrou; bpo-3001.)

* The fast-search algorithm in stringlib is now used by the "split()",
  "rsplit()", "splitlines()" and "replace()" methods on "bytes",
  "bytearray" and "str" objects. Likewise, the algorithm is also used
  by "rfind()", "rindex()", "rsplit()" and "rpartition()".

  (Patch by Florent Xicluna in bpo-7622 and bpo-7462.)

* Integer to string conversions now work two "digits" at a time,
  reducing the number of division and modulo operations.

  (bpo-6713 by Gawain Bolton, Mark Dickinson, and Victor Stinner.)

There were several other minor optimizations. Set differencing now
runs faster when one operand is much larger than the other (patch by
Andress Bennetts in bpo-8685).  The "array.repeat()" method has a
faster implementation (bpo-1569291 by Alexander Belopolsky). The
"BaseHTTPRequestHandler" has more efficient buffering (bpo-3709 by
Andrew Schaaf).  The "operator.attrgetter()" function has been sped-up
(bpo-10160 by Christos Georgiou).  And "ConfigParser" loads multi-line
arguments a bit faster (bpo-7113 by Łukasz Langa).


Unicode
=======

Python has been updated to Unicode 6.0.0.  The update to the standard
adds over 2,000 new characters including emoji symbols which are
important for mobile phones.

In addition, the updated standard has altered the character properties
for two Kannada characters (U+0CF1, U+0CF2) and one New Tai Lue
numeric character (U+19DA), making the former eligible for use in
identifiers while disqualifying the latter.  For more information, see
Unicode Character Database Changes.


Codecs
======

Support was added for *cp720* Arabic DOS encoding (bpo-1616979).

MBCS encoding no longer ignores the error handler argument. In the
default strict mode, it raises an "UnicodeDecodeError" when it
encounters an undecodable byte sequence and an "UnicodeEncodeError"
for an unencodable character.

The MBCS codec supports "'strict'" and "'ignore'" error handlers for
decoding, and "'strict'" and "'replace'" for encoding.

To emulate Python3.1 MBCS encoding, select the "'ignore'" handler for
decoding and the "'replace'" handler for encoding.

On Mac OS X, Python decodes command line arguments with "'utf-8'"
rather than the locale encoding.

By default, "tarfile" uses "'utf-8'" encoding on Windows (instead of
"'mbcs'") and the "'surrogateescape'" error handler on all operating
systems.


Documentation
=============

The documentation continues to be improved.

* A table of quick links has been added to the top of lengthy sections
  such as Built-in Functions.  In the case of "itertools", the links
  are accompanied by tables of cheatsheet-style summaries to provide
  an overview and memory jog without having to read all of the docs.

* In some cases, the pure Python source code can be a helpful adjunct
  to the documentation, so now many modules now feature quick links to
  the latest version of the source code.  For example, the "functools"
  module documentation has a quick link at the top labeled:

     **Source code** Lib/functools.py.

  (Contributed by Raymond Hettinger; see rationale.)

* The docs now contain more examples and recipes.  In particular, "re"
  module has an extensive section, Regular Expression Examples.
  Likewise, the "itertools" module continues to be updated with new
  Itertools Recipes.

* The "datetime" module now has an auxiliary implementation in pure
  Python. No functionality was changed.  This just provides an easier-
  to-read alternate implementation.

  (Contributed by Alexander Belopolsky in bpo-9528.)

* The unmaintained "Demo" directory has been removed.  Some demos were
  integrated into the documentation, some were moved to the
  "Tools/demo" directory, and others were removed altogether.

  (Contributed by Georg Brandl in bpo-7962.)


IDLE
====

* The format menu now has an option to clean source files by stripping
  trailing whitespace.

  (Contributed by Raymond Hettinger; bpo-5150.)

* IDLE on Mac OS X now works with both Carbon AquaTk and Cocoa AquaTk.

  (Contributed by Kevin Walzer, Ned Deily, and Ronald Oussoren;
  bpo-6075.)


Code Repository
===============

In addition to the existing Subversion code repository at
https://svn.python.org there is now a Mercurial repository at
https://hg.python.org/.

After the 3.2 release, there are plans to switch to Mercurial as the
primary repository.  This distributed version control system should
make it easier for members of the community to create and share
external changesets.  See **PEP 385** for details.

To learn to use the new version control system, see the Quick Start or
the Guide to Mercurial Workflows.


Build and C API Changes
=======================

Changes to Python's build process and to the C API include:

* The *idle*, *pydoc* and *2to3* scripts are now installed with a
  version-specific suffix on "make altinstall" (bpo-10679).

* The C functions that access the Unicode Database now accept and
  return characters from the full Unicode range, even on narrow
  unicode builds (Py_UNICODE_TOLOWER, Py_UNICODE_ISDECIMAL, and
  others).  A visible difference in Python is that
  "unicodedata.numeric()" now returns the correct value for large code
  points, and "repr()" may consider more characters as printable.

  (Reported by Bupjoe Lee and fixed by Amaury Forgeot D'Arc;
  bpo-5127.)

* Computed gotos are now enabled by default on supported compilers
  (which are detected by the configure script).  They can still be
  disabled selectively by specifying "--without-computed-gotos".

  (Contributed by Antoine Pitrou; bpo-9203.)

* The option "--with-wctype-functions" was removed.  The built-in
  unicode database is now used for all functions.

  (Contributed by Amaury Forgeot D'Arc; bpo-9210.)

* Hash values are now values of a new type, "Py_hash_t", which is
  defined to be the same size as a pointer.  Previously they were of
  type long, which on some 64-bit operating systems is still only 32
  bits long.  As a result of this fix, "set" and "dict" can now hold
  more than "2**32" entries on builds with 64-bit pointers
  (previously, they could grow to that size but their performance
  degraded catastrophically).

  (Suggested by Raymond Hettinger and implemented by Benjamin
  Peterson; bpo-9778.)

* A new macro "Py_VA_COPY" copies the state of the variable argument
  list.  It is equivalent to C99 *va_copy* but available on all Python
  platforms (bpo-2443).

* A new C API function "PySys_SetArgvEx()" allows an embedded
  interpreter to set "sys.argv" without also modifying "sys.path"
  (bpo-5753).

* "PyEval_CallObject()" is now only available in macro form.  The
  function declaration, which was kept for backwards compatibility
  reasons, is now removed -- the macro was introduced in 1997
  (bpo-8276).

* There is a new function "PyLong_AsLongLongAndOverflow()" which is
  analogous to "PyLong_AsLongAndOverflow()".  They both serve to
  convert Python "int" into a native fixed-width type while providing
  detection of cases where the conversion won't fit (bpo-7767).

* The "PyUnicode_CompareWithASCIIString()" function now returns *not
  equal* if the Python string is *NUL* terminated.

* There is a new function "PyErr_NewExceptionWithDoc()" that is like
  "PyErr_NewException()" but allows a docstring to be specified. This
  lets C exceptions have the same self-documenting capabilities as
  their pure Python counterparts (bpo-7033).

* When compiled with the "--with-valgrind" option, the pymalloc
  allocator will be automatically disabled when running under
  Valgrind.  This gives improved memory leak detection when running
  under Valgrind, while taking advantage of pymalloc at other times
  (bpo-2422).

* Removed the "O?" format from the *PyArg_Parse* functions.  The
  format is no longer used and it had never been documented
  (bpo-8837).

There were a number of other small changes to the C-API.  See the
Misc/NEWS file for a complete list.

Also, there were a number of updates to the Mac OS X build, see
Mac/BuildScript/README.txt for details.  For users running a 32/64-bit
build, there is a known problem with the default Tcl/Tk on Mac OS X
10.6. Accordingly, we recommend installing an updated alternative such
as ActiveState Tcl/Tk 8.5.9. See
https://www.python.org/download/mac/tcltk/ for additional details.


Porting to Python 3.2
=====================

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

* The "configparser" module has a number of clean-ups.  The major
  change is to replace the old "ConfigParser" class with long-standing
  preferred alternative "SafeConfigParser".  In addition there are a
  number of smaller incompatibilities:

  * The interpolation syntax is now validated on "get()" and "set()"
    operations. In the default interpolation scheme, only two tokens
    with percent signs are valid: "%(name)s" and "%%", the latter
    being an escaped percent sign.

  * The "set()" and "add_section()" methods now verify that values are
    actual strings.  Formerly, unsupported types could be introduced
    unintentionally.

  * Duplicate sections or options from a single source now raise
    either "DuplicateSectionError" or "DuplicateOptionError".
    Formerly, duplicates would silently overwrite a previous entry.

  * Inline comments are now disabled by default so now the **;**
    character can be safely used in values.

  * Comments now can be indented.  Consequently, for **;** or **#** to
    appear at the start of a line in multiline values, it has to be
    interpolated.  This keeps comment prefix characters in values from
    being mistaken as comments.

  * """" is now a valid value and is no longer automatically converted
    to an empty string. For empty strings, use ""option ="" in a line.

* The "nntplib" module was reworked extensively, meaning that its APIs
  are often incompatible with the 3.1 APIs.

* "bytearray" objects can no longer be used as filenames; instead,
  they should be converted to "bytes".

* The "array.tostring()" and "array.fromstring()" have been renamed to
  "array.tobytes()" and "array.frombytes()" for clarity.  The old
  names have been deprecated. (See bpo-8990.)

* "PyArg_Parse*()" functions:

  * "t#" format has been removed: use "s#" or "s*" instead

  * "w" and "w#" formats has been removed: use "w*" instead

* The "PyCObject" type, deprecated in 3.1, has been removed.  To wrap
  opaque C pointers in Python objects, the "PyCapsule" API should be
  used instead; the new type has a well-defined interface for passing
  typing safety information and a less complicated signature for
  calling a destructor.

* The "sys.setfilesystemencoding()" function was removed because it
  had a flawed design.

* The "random.seed()" function and method now salt string seeds with
  an sha512 hash function.  To access the previous version of *seed*
  in order to reproduce Python 3.1 sequences, set the *version*
  argument to *1*, "random.seed(s, version=1)".

* The previously deprecated "string.maketrans()" function has been
  removed in favor of the static methods "bytes.maketrans()" and
  "bytearray.maketrans()".  This change solves the confusion around
  which types were supported by the "string" module.  Now, "str",
  "bytes", and "bytearray" each have their own **maketrans** and
  **translate** methods with intermediate translation tables of the
  appropriate type.

  (Contributed by Georg Brandl; bpo-5675.)

* The previously deprecated "contextlib.nested()" function has been
  removed in favor of a plain "with" statement which can accept
  multiple context managers.  The latter technique is faster (because
  it is built-in), and it does a better job finalizing multiple
  context managers when one of them raises an exception:

     with open('mylog.txt') as infile, open('a.out', 'w') as outfile:
         for line in infile:
             if '<critical>' in line:
                 outfile.write(line)

  (Contributed by Georg Brandl and Mattias Brändström; appspot issue
  53094.)

* "struct.pack()" now only allows bytes for the "s" string pack code.
  Formerly, it would accept text arguments and implicitly encode them
  to bytes using UTF-8.  This was problematic because it made
  assumptions about the correct encoding and because a variable-length
  encoding can fail when writing to fixed length segment of a
  structure.

  Code such as "struct.pack('<6sHHBBB', 'GIF87a', x, y)" should be
  rewritten with to use bytes instead of text,
  "struct.pack('<6sHHBBB', b'GIF87a', x, y)".

  (Discovered by David Beazley and fixed by Victor Stinner;
  bpo-10783.)

* The "xml.etree.ElementTree" class now raises an
  "xml.etree.ElementTree.ParseError" when a parse fails. Previously it
  raised an "xml.parsers.expat.ExpatError".

* The new, longer "str()" value on floats may break doctests which
  rely on the old output format.

* In "subprocess.Popen", the default value for *close_fds* is now
  "True" under Unix; under Windows, it is "True" if the three standard
  streams are set to "None", "False" otherwise.  Previously,
  *close_fds* was always "False" by default, which produced difficult
  to solve bugs or race conditions when open file descriptors would
  leak into the child process.

* Support for legacy HTTP 0.9 has been removed from "urllib.request"
  and "http.client".  Such support is still present on the server side
  (in "http.server").

  (Contributed by Antoine Pitrou, bpo-10711.)

* SSL sockets in timeout mode now raise "socket.timeout" when a
  timeout occurs, rather than a generic "SSLError".

  (Contributed by Antoine Pitrou, bpo-10272.)

* The misleading functions "PyEval_AcquireLock()" and
  "PyEval_ReleaseLock()" have been officially deprecated.  The thread-
  state aware APIs (such as "PyEval_SaveThread()" and
  "PyEval_RestoreThread()") should be used instead.

* Due to security risks, "asyncore.handle_accept()" has been
  deprecated, and a new function, "asyncore.handle_accepted()", was
  added to replace it.

  (Contributed by Giampaolo Rodola in bpo-6706.)

* Due to the new *GIL* implementation, "PyEval_InitThreads()" cannot
  be called before "Py_Initialize()" anymore.
