"annotationlib" --- Functionality for introspecting annotations
***************************************************************

Added in version 3.14.

**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" returns "ForwardRef" 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_from_class_namespace()" and "call_annotate_function()",
as well as the "call_evaluate_function()" function for working with
*evaluate functions*.

注意:

  Most functionality in this module can execute arbitrary code; see
  the security section for more information.

参考:

  **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.

  アノテーションのベストプラクティス 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 where "func" is defined, because "Cls" 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.


クラス
======

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 to "get_annotations()" and other functions in this
   module, as well as to "__annotate__" functions.

   VALUE = 1

      Values are the result of evaluating the annotation expressions.

   VALUE_WITH_FAKE_GLOBALS = 2

      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 raise
      "NotImplementedError" 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.

   FORWARDREF = 3

      Values are real annotation values (as per "Format.VALUE" format)
      for defined values, and "ForwardRef" proxies for undefined
      values. Real objects may contain references to "ForwardRef"
      proxy objects.

   STRING = 4

      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.

   Added in version 3.14.

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(*, owner=None, globals=None, locals=None, type_params=None, format=Format.VALUE)

      Evaluate the forward reference, returning its value.

      If the *format* argument is "VALUE" (the default), this method
      may throw an exception, such as "NameError", if the forward
      reference refers to a name that cannot be resolved. The
      arguments to this method can be used to provide bindings for
      names that would otherwise be undefined. If the *format*
      argument is "FORWARDREF", the method will never throw an
      exception, but may return a "ForwardRef" instance. For example,
      if the forward reference object contains the code
      "list[undefined]", where "undefined" is a name that is not
      defined, evaluating it with the "FORWARDREF" format will return
      "list[ForwardRef('undefined')]". If the *format* argument is
      "STRING", the method will return "__forward_arg__".

      The *owner* parameter provides the preferred mechanism for
      passing scope information to this method. The owner of a
      "ForwardRef" is the object that contains the annotation from
      which the "ForwardRef" derives, such as a module object, type
      object, or function object.

      The *globals*, *locals*, and *type_params* parameters provide a
      more precise mechanism for influencing the names that are
      available when the "ForwardRef" is evaluated. *globals* and
      *locals* are passed to "eval()", representing the global and
      local namespaces in which the name is evaluated. The
      *type_params* parameter is relevant for objects created using
      the native syntax for generic classes and functions. It is a
      tuple of type parameters that are in scope while the forward
      reference is being evaluated. For example, if evaluating a
      "ForwardRef" retrieved from an annotation found in the class
      namespace of a generic class "C", *type_params* should be set to
      "C.__type_params__".

      "ForwardRef" instances returned by "get_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.

      If no *owner*, *globals*, *locals*, or *type_params* are
      provided and the "ForwardRef" does not contain information about
      its origin, empty globals and locals dictionaries are used.

   Added in version 3.14.


関数
====

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 "type_repr()". 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.

   For example, this is used to implement the "STRING" for
   "typing.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'}

   Added in version 3.14.

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 a "ForwardRef" object that carries
   more information.

   参考:

     **PEP 649** contains an explanation of the implementation
     technique used by this function.

   Added in version 3.14.

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 to "call_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
     aliases

   * "typing.TypeVar.evaluate_bound()", the bound of type variables

   * "typing.TypeVar.evaluate_constraints()", the constraints of type
     variables

   * "typing.TypeVar.evaluate_default()", the default value of type
     variables

   * "typing.ParamSpec.evaluate_default()", the default value of
     parameter specifications

   * "typing.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'

   Added in version 3.14.

annotationlib.get_annotate_from_class_namespace(namespace)

   Retrieve the *annotate function* from a class namespace dictionary
   *namespace*. Return "None" if the namespace does not contain an
   annotate function. This is primarily useful before the class has
   been fully created (e.g., in a metaclass); after the class exists,
   the annotate function can be retrieved with "cls.__annotate__". See
   below for an example using this function in a metaclass.

   Added in version 3.14.

annotationlib.get_annotations(obj, *, globals=None, locals=None, eval_str=False, format=Format.VALUE)

   オブジェクトに対するアノテーション辞書を計算します。

   *obj* may be a callable, class, module, or other object with
   "__annotate__" or "__annotations__" attributes. Passing any other
   object raises "TypeError".

   The *format* parameter controls the format in which annotations are
   returned, and must be a member of the "Format" enum or its integer
   equivalent. The different formats work as follows:

   * VALUE: "object.__annotations__" is tried first; if that does not
     exist, the "object.__annotate__" function is called if it exists.

   * FORWARDREF: If "object.__annotations__" exists and can be
     evaluated successfully, it is used; otherwise, the
     "object.__annotate__" function is called. If it does not exist
     either, "object.__annotations__" is tried again and any error
     from accessing it is re-raised.

     * When calling "object.__annotate__" it is first called with
       "FORWARDREF". If this is not implemented, it will then check if
       "VALUE_WITH_FAKE_GLOBALS" is supported and use that in the fake
       globals environment. If neither of these formats are supported,
       it will fall back to using "VALUE". If "VALUE" fails, the error
       from this call will be raised.

   * STRING: If "object.__annotate__" exists, it is called first;
     otherwise, "object.__annotations__" is used and stringified using
     "annotations_to_string()".

     * When calling "object.__annotate__" it is first called with
       "STRING". If this is not implemented, it will then check if
       "VALUE_WITH_FAKE_GLOBALS" is supported and use that in the fake
       globals environment. If neither of these formats are supported,
       it will fall back to using "VALUE" with the result converted
       using "annotations_to_string()". If "VALUE" fails, the error
       from this call will be raised.

   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
     using "eval()". 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 than
     "Format.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()" and "dict.get()" for safety.

   *eval_str* controls whether or not values of type "str" are
   replaced with the result of calling "eval()" on those values:

   * If eval_str is true, "eval()" is called on values of type "str".
     (Note that "get_annotations()" doesn't catch exceptions; if
     "eval()" raises an exception, it will unwind the stack past the
     "get_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 for "eval()" for more information. If *globals* or
   *locals* is "None", this function may replace that value with a
   context-specific default, contingent on "type(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 (using
     "functools.update_wrapper()") or a "functools.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 アノテーションのベストプラクテ
   ィス 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'>}

   Added in version 3.14.

annotationlib.type_repr(value)

   Convert an arbitrary Python value to a format suitable for use by
   the "STRING" format. This calls "repr()" 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.

   Added in version 3.14.


レシピ
======


Using annotations in a metaclass
--------------------------------

A metaclass may want to inspect or even modify the annotations in a
class body during class creation. Doing so requires retrieving
annotations from the class namespace dictionary. For classes created
with "from __future__ import annotations", the annotations will be in
the "__annotations__" key of the dictionary. For other classes with
annotations, "get_annotate_from_class_namespace()" can be used to get
the annotate function, and "call_annotate_function()" can be used to
call it and retrieve the annotations. Using the "FORWARDREF" format
will usually be best, because this allows the annotations to refer to
names that cannot yet be resolved when the class is created.

To modify the annotations, it is best to create a wrapper annotate
function that calls the original annotate function, makes any
necessary adjustments, and returns the result.

Below is an example of a metaclass that filters out all
"typing.ClassVar" annotations from the class and puts them in a
separate attribute:

   import annotationlib
   import typing

   class ClassVarSeparator(type):
      def __new__(mcls, name, bases, ns):
         if "__annotations__" in ns:  # from __future__ import annotations
            annotations = ns["__annotations__"]
            classvar_keys = {
               key for key, value in annotations.items()
               # Use string comparison for simplicity; a more robust solution
               # could use annotationlib.ForwardRef.evaluate
               if value.startswith("ClassVar")
            }
            classvars = {key: annotations[key] for key in classvar_keys}
            ns["__annotations__"] = {
               key: value for key, value in annotations.items()
               if key not in classvar_keys
            }
            wrapped_annotate = None
         elif annotate := annotationlib.get_annotate_from_class_namespace(ns):
            annotations = annotationlib.call_annotate_function(
               annotate, format=annotationlib.Format.FORWARDREF
            )
            classvar_keys = {
               key for key, value in annotations.items()
               if typing.get_origin(value) is typing.ClassVar
            }
            classvars = {key: annotations[key] for key in classvar_keys}

            def wrapped_annotate(format):
               annos = annotationlib.call_annotate_function(annotate, format, owner=typ)
               return {key: value for key, value in annos.items() if key not in classvar_keys}

         else:  # no annotations
            classvars = {}
            wrapped_annotate = None
         typ = super().__new__(mcls, name, bases, ns)

         if wrapped_annotate is not None:
            # Wrap the original __annotate__ with a wrapper that removes ClassVars
            typ.__annotate__ = wrapped_annotate
         typ.classvars = classvars  # Store the ClassVars in a separate attribute
         return typ


Limitations of the "STRING" format
==================================

The "STRING" format is meant to approximate the source code of the
annotation, but the implementation strategy used means that it is not
always possible to recover the exact source code.

First, the stringifier of course cannot recover any information that
is not present in the compiled code, including comments, whitespace,
parenthesization, and operations that get simplified by the compiler.

Second, the stringifier can intercept almost all operations that
involve names looked up in some scope, but it cannot intercept
operations that operate fully on constants. As a corollary, this also
means it is not safe to request the "STRING" format on untrusted code:
Python is powerful enough that it is possible to achieve arbitrary
code execution even with no access to any globals or builtins. For
example:

   >>> def f(x: (1).__class__.__base__.__subclasses__()[-1].__init__.__builtins__["print"]("Hello world")): pass
   ...
   >>> annotationlib.get_annotations(f, format=annotationlib.Format.STRING)
   Hello world
   {'x': 'None'}

注釈:

  This particular example works as of the time of writing, but it
  relies on implementation details and is not guaranteed to work in
  the future.

Among the different kinds of expressions that exist in Python, as
represented by the "ast" module, some expressions are supported,
meaning that the "STRING" format can generally recover the original
source code; others are unsupported, meaning that they may result in
incorrect output or an error.

The following are supported (sometimes with caveats):

* "ast.BinOp"

* "ast.UnaryOp"

  * "ast.Invert" ("~"), "ast.UAdd" ("+"), and "ast.USub" ("-") are
    supported

  * "ast.Not" ("not") is not supported

* "ast.Dict" (except when using "**" unpacking)

* "ast.Set"

* "ast.Compare"

  * "ast.Eq" and "ast.NotEq" are supported

  * "ast.Lt", "ast.LtE", "ast.Gt", and "ast.GtE" are supported, but
    the operand may be flipped

  * "ast.Is", "ast.IsNot", "ast.In", and "ast.NotIn" are not supported

* "ast.Call" (except when using "**" unpacking)

* "ast.Constant" (though not the exact representation of the constant;
  for example, escape sequences in strings are lost; hexadecimal
  numbers are converted to decimal)

* "ast.Attribute" (assuming the value is not a constant)

* "ast.Subscript" (assuming the value is not a constant)

* "ast.Starred" ("*" unpacking)

* "ast.Name"

* "ast.List"

* "ast.Tuple"

* "ast.Slice"

The following are unsupported, but throw an informative error when
encountered by the stringifier:

* "ast.FormattedValue" (f-strings; error is not detected if conversion
  specifiers like "!r" are used)

* "ast.JoinedStr" (f-strings)

The following are unsupported and result in incorrect output:

* "ast.BoolOp" ("and" and "or")

* "ast.IfExp"

* "ast.Lambda"

* "ast.ListComp"

* "ast.SetComp"

* "ast.DictComp"

* "ast.GeneratorExp"

The following are disallowed in annotation scopes and therefore not
relevant:

* "ast.NamedExpr" (":=")

* "ast.Await"

* "ast.Yield"

* "ast.YieldFrom"


Limitations of the "FORWARDREF" format
======================================

The "FORWARDREF" format aims to produce real values as much as
possible, with anything that cannot be resolved replaced with
"ForwardRef" objects. It is affected by broadly the same Limitations
as the "STRING" format: annotations that perform operations on
literals or that use unsupported expression types may raise exceptions
when evaluated using the "FORWARDREF" format.

Below are a few examples of the behavior with unsupported expressions:

   >>> from annotationlib import get_annotations, Format
   >>> def zerodiv(x: 1 / 0): ...
   >>> get_annotations(zerodiv, format=Format.STRING)
   Traceback (most recent call last):
     ...
   ZeroDivisionError: division by zero
   >>> get_annotations(zerodiv, format=Format.FORWARDREF)
   Traceback (most recent call last):
     ...
   ZeroDivisionError: division by zero
   >>> def ifexp(x: 1 if y else 0): ...
   >>> get_annotations(ifexp, format=Format.STRING)
   {'x': '1'}


Security implications of introspecting annotations
==================================================

Much of the functionality in this module involves executing code
related to annotations, which can then do arbitrary things. For
example, "get_annotations()" may call an arbitrary *annotate
function*, and "ForwardRef.evaluate()" may call "eval()" on an
arbitrary string. Code contained in an annotation might make arbitrary
system calls, enter an infinite loop, or perform any other operation.
This is also true for any access of the "__annotations__" attribute,
and for various functions in the "typing" module that work with
annotations, such as "typing.get_type_hints()".

Any security issue arising from this also applies immediately after
importing code that may contain untrusted annotations: importing code
can always cause arbitrary operations to be performed. However, it is
unsafe to accept strings or other input from an untrusted source and
pass them to any of the APIs for introspecting annotations, for
example by editing an "__annotations__" dictionary or directly
creating a "ForwardRef" object.
