annotationlib
--- Functionality for introspecting annotations¶
Source code: Lib/annotationlib.py
The annotationlib
module provides tools for introspecting
annotations on modules, classes, and functions.
Annotations are lazily evaluated and often contain forward references to objects that are not yet defined when the annotation is created. This module provides a set of low-level tools that can be used to retrieve annotations in a reliable way, even in the presence of forward references and other edge cases.
This module supports retrieving annotations in three main formats
(see Format
), each of which works best for different use cases:
VALUE
evaluates the annotations and returns their value. This is most straightforward to work with, but it may raise errors, for example if the annotations contain references to undefined names.FORWARDREF
returnsForwardRef
objects for annotations that cannot be resolved, allowing you to inspect the annotations without evaluating them. This is useful when you need to work with annotations that may contain unresolved forward references.STRING
returns the annotations as a string, similar to how it would appear in the source file. This is useful for documentation generators that want to display annotations in a readable way.
The get_annotations()
function is the main entry point for
retrieving annotations. Given a function, class, or module, it returns
an annotations dictionary in the requested format. This module also provides
functionality for working directly with the annotate function
that is used to evaluate annotations, such as get_annotate_function()
and call_annotate_function()
, as well as the
call_evaluate_function()
function for working with
evaluate functions.
也參考
PEP 649 proposed the current model for how annotations work in Python.
PEP 749 expanded on various aspects of PEP 649 and introduced the
annotationlib
module.
註釋 (annotation) 最佳實踐 provides best practices for working with annotations.
typing-extensions provides a backport of get_annotations()
that works on earlier versions of Python.
Annotation semantics¶
The way annotations are evaluated has changed over the history of Python 3, and currently still depends on a future import. There have been execution models for annotations:
Stock semantics (default in Python 3.0 through 3.13; see PEP 3107 and PEP 526): Annotations are evaluated eagerly, as they are encountered in the source code.
Stringified annotations (used with
from __future__ import annotations
in Python 3.7 and newer; see PEP 563): Annotations are stored as strings only.Deferred evaluation (default in Python 3.14 and newer; see PEP 649 and PEP 749): Annotations are evaluated lazily, only when they are accessed.
As an example, consider the following program:
def func(a: Cls) -> None:
print(a)
class Cls: pass
print(func.__annotations__)
This will behave as follows:
Under stock semantics (Python 3.13 and earlier), it will throw a
NameError
at the line wherefunc
is defined, becauseCls
is an undefined name at that point.Under stringified annotations (if
from __future__ import annotations
is used), it will print{'a': 'Cls', 'return': 'None'}
.Under deferred evaluation (Python 3.14 and later), it will print
{'a': <class 'Cls'>, 'return': None}
.
Stock semantics were used when function annotations were first introduced
in Python 3.0 (by PEP 3107) because this was the simplest, most obvious
way to implement annotations. The same execution model was used when variable
annotations were introduced in Python 3.6 (by PEP 526). However,
stock semantics caused problems when using annotations as type hints,
such as a need to refer to names that are not yet defined when the
annotation is encountered. In addition, there were performance problems
with executing annotations at module import time. Therefore, in Python 3.7,
PEP 563 introduced the ability to store annotations as strings using the
from __future__ import annotations
syntax. The plan at the time was to
eventually make this behavior the default, but a problem appeared:
stringified annotations are more difficult to process for those who
introspect annotations at runtime. An alternative proposal, PEP 649,
introduced the third execution model, deferred evaluation, and was implemented
in Python 3.14. Stringified annotations are still used if
from __future__ import annotations
is present, but this behavior will
eventually be removed.
Classes¶
- class annotationlib.Format¶
An
IntEnum
describing the formats in which annotations can be returned. Members of the enum, or their equivalent integer values, can be passed toget_annotations()
and other functions in this module, as well as to__annotate__
functions.- VALUE = 1¶
Values are the result of evaluating the annotation expressions.
- FORWARDREF = 2¶
Values are real annotation values (as per
Format.VALUE
format) for defined values, andForwardRef
proxies for undefined values. Real objects may contain references to,ForwardRef
proxy objects.
- STRING = 3¶
Values are the text string of the annotation as it appears in the source code, up to modifications including, but not restricted to, whitespace normalizations and constant values optimizations.
The exact values of these strings may change in future versions of Python.
- VALUE_WITH_FAKE_GLOBALS = 4¶
Special value used to signal that an annotate function is being evaluated in a special environment with fake globals. When passed this value, annotate functions should either return the same value as for the
Format.VALUE
format, or raiseNotImplementedError
to signal that they do not support execution in this environment. This format is only used internally and should not be passed to the functions in this module.
在 3.14 版被加入.
- class annotationlib.ForwardRef¶
A proxy object for forward references in annotations.
Instances of this class are returned when the
FORWARDREF
format is used and annotations contain a name that cannot be resolved. This can happen when a forward reference is used in an annotation, such as when a class is referenced before it is defined.- __forward_arg__¶
A string containing the code that was evaluated to produce the
ForwardRef
. The string may not be exactly equivalent to the original source.
- evaluate(*, globals=None, locals=None, type_params=None, owner=None)¶
Evaluate the forward reference, returning its value.
This may throw an exception, such as
NameError
, if the forward reference refers to names that do not exist. The arguments to this method can be used to provide bindings for names that would otherwise be undefined.ForwardRef
instances returned byget_annotations()
retain references to information about the scope they originated from, so calling this method with no further arguments may be sufficient to evaluate such objects.ForwardRef
instances created by other means may not have any information about their scope, so passing arguments to this method may be necessary to evaluate them successfully.globals and locals are passed to
eval()
, representing the global and local namespaces in which the name is evaluated. type_params, if given, must be a tuple of type parameters that are in scope while the forward reference is being evaluated. owner is the object that owns the annotation from which the forward reference derives, usually a function, class, or module.重要
Once a
ForwardRef
instance has been evaluated, it caches the evaluated value, and future calls toevaluate()
will return the cached value, regardless of the parameters passed in.
在 3.14 版被加入.
Functions¶
- annotationlib.annotations_to_string(annotations)¶
Convert an annotations dict containing runtime values to a dict containing only strings. If the values are not already strings, they are converted using
value_to_string()
. This is meant as a helper for user-provided annotate functions that support theSTRING
format but do not have access to the code creating the annotations.For example, this is used to implement the
STRING
fortyping.TypedDict
classes created through the functional syntax:>>> from typing import TypedDict >>> Movie = TypedDict("movie", {"name": str, "year": int}) >>> get_annotations(Movie, format=Format.STRING) {'name': 'str', 'year': 'int'}
在 3.14 版被加入.
- annotationlib.call_annotate_function(annotate, format, *, owner=None)¶
Call the annotate function annotate with the given format, a member of the
Format
enum, and return the annotations dictionary produced by the function.This helper function is required because annotate functions generated by the compiler for functions, classes, and modules only support the
VALUE
format when called directly. To support other formats, this function calls the annotate function in a special environment that allows it to produce annotations in the other formats. This is a useful building block when implementing functionality that needs to partially evaluate annotations while a class is being constructed.owner is the object that owns the annotation function, usually a function, class, or module. If provided, it is used in the
FORWARDREF
format to produce aForwardRef
object that carries more information.也參考
PEP 649 contains an explanation of the implementation technique used by this function.
在 3.14 版被加入.
- annotationlib.call_evaluate_function(evaluate, format, *, owner=None)¶
Call the evaluate function evaluate with the given format, a member of the
Format
enum, and return the value produced by the function. This is similar tocall_annotate_function()
, but the latter always returns a dictionary mapping strings to annotations, while this function returns a single value.This is intended for use with the evaluate functions generated for lazily evaluated elements related to type aliases and type parameters:
typing.TypeAliasType.evaluate_value()
, the value of type aliasestyping.TypeVar.evaluate_bound()
, the bound of type variablestyping.TypeVar.evaluate_constraints()
, the constraints of type variablestyping.TypeVar.evaluate_default()
, the default value of type variablestyping.ParamSpec.evaluate_default()
, the default value of parameter specificationstyping.TypeVarTuple.evaluate_default()
, the default value of type variable tuples
owner is the object that owns the evaluate function, such as the type alias or type variable object.
format can be used to control the format in which the value is returned:
>>> type Alias = undefined >>> call_evaluate_function(Alias.evaluate_value, Format.VALUE) Traceback (most recent call last): ... NameError: name 'undefined' is not defined >>> call_evaluate_function(Alias.evaluate_value, Format.FORWARDREF) ForwardRef('undefined') >>> call_evaluate_function(Alias.evaluate_value, Format.STRING) 'undefined'
在 3.14 版被加入.
- annotationlib.get_annotate_function(obj)¶
Retrieve the annotate function for obj. Return
None
if obj does not have an annotate function.This is usually equivalent to accessing the
__annotate__
attribute of obj, but direct access to the attribute may return the wrong object in certain situations involving metaclasses. This function should be used instead of accessing the attribute directly.在 3.14 版被加入.
- annotationlib.get_annotations(obj, *, globals=None, locals=None, eval_str=False, format=Format.VALUE)¶
Compute the annotations dict for an object.
obj may be a callable, class, module, or other object with
__annotate__
and__annotations__
attributes. Passing in an object of any other type raisesTypeError
.The format parameter controls the format in which annotations are returned, and must be a member of the
Format
enum or its integer equivalent.Returns a dict.
get_annotations()
returns a new dict every time it's called; calling it twice on the same object will return two different but equivalent dicts.This function handles several details for you:
If eval_str is true, values of type
str
will be un-stringized usingeval()
. This is intended for use with stringized annotations (from __future__ import annotations
). It is an error to set eval_str to true with formats other thanFormat.VALUE
.If obj doesn't have an annotations dict, returns an empty dict. (Functions and methods always have an annotations dict; classes, modules, and other types of callables may not.)
Ignores inherited annotations on classes, as well as annotations on metaclasses. If a class doesn't have its own annotations dict, returns an empty dict.
All accesses to object members and dict values are done using
getattr()
anddict.get()
for safety.
eval_str controls whether or not values of type
str
are replaced with the result of callingeval()
on those values:If eval_str is true,
eval()
is called on values of typestr
. (Note thatget_annotations()
doesn't catch exceptions; ifeval()
raises an exception, it will unwind the stack past theget_annotations()
call.)If eval_str is false (the default), values of type
str
are unchanged.
globals and locals are passed in to
eval()
; see the documentation foreval()
for more information. If globals or locals isNone
, this function may replace that value with a context-specific default, contingent ontype(obj)
:If obj is a module, globals defaults to
obj.__dict__
.If obj is a class, globals defaults to
sys.modules[obj.__module__].__dict__
and locals defaults to the obj class namespace.If obj is a callable, globals defaults to
obj.__globals__
, although if obj is a wrapped function (usingfunctools.update_wrapper()
) or afunctools.partial
object, it is unwrapped until a non-wrapped function is found.
Calling
get_annotations()
is best practice for accessing the annotations dict of any object. See 註釋 (annotation) 最佳實踐 for more information on annotations best practices.>>> def f(a: int, b: str) -> float: ... pass >>> get_annotations(f) {'a': <class 'int'>, 'b': <class 'str'>, 'return': <class 'float'>}
在 3.14 版被加入.
- annotationlib.value_to_string(value)¶
Convert an arbitrary Python value to a format suitable for use by the
STRING
format. This callsrepr()
for most objects, but has special handling for some objects, such as type objects.This is meant as a helper for user-provided annotate functions that support the
STRING
format but do not have access to the code creating the annotations. It can also be used to provide a user-friendly string representation for other objects that contain values that are commonly encountered in annotations.在 3.14 版被加入.