mirror of https://github.com/python/cpython
252 lines
10 KiB
ReStructuredText
252 lines
10 KiB
ReStructuredText
.. _annotations-howto:
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**************************
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Annotations Best Practices
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**************************
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:author: Larry Hastings
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.. topic:: Abstract
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This document is designed to encapsulate the best practices
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for working with annotations dicts. If you write Python code
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that examines ``__annotations__`` on Python objects, we
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encourage you to follow the guidelines described below.
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The document is organized into four sections:
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best practices for accessing the annotations of an object
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in Python versions 3.10 and newer,
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best practices for accessing the annotations of an object
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in Python versions 3.9 and older,
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other best practices
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for ``__annotations__`` that apply to any Python version,
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and
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quirks of ``__annotations__``.
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Note that this document is specifically about working with
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``__annotations__``, not uses *for* annotations.
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If you're looking for information on how to use "type hints"
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in your code, please see the :mod:`typing` module.
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Accessing The Annotations Dict Of An Object In Python 3.10 And Newer
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====================================================================
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Python 3.10 adds a new function to the standard library:
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:func:`inspect.get_annotations`. In Python versions 3.10
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through 3.13, calling this function is the best practice for
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accessing the annotations dict of any object that supports
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annotations. This function can also "un-stringize"
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stringized annotations for you.
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In Python 3.14, there is a new :mod:`annotationlib` module
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with functionality for working with annotations. This
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includes a :func:`annotationlib.get_annotations` function,
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which supersedes :func:`inspect.get_annotations`.
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If for some reason :func:`inspect.get_annotations` isn't
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viable for your use case, you may access the
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``__annotations__`` data member manually. Best practice
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for this changed in Python 3.10 as well: as of Python 3.10,
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``o.__annotations__`` is guaranteed to *always* work
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on Python functions, classes, and modules. If you're
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certain the object you're examining is one of these three
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*specific* objects, you may simply use ``o.__annotations__``
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to get at the object's annotations dict.
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However, other types of callables--for example,
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callables created by :func:`functools.partial`--may
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not have an ``__annotations__`` attribute defined. When
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accessing the ``__annotations__`` of a possibly unknown
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object, best practice in Python versions 3.10 and
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newer is to call :func:`getattr` with three arguments,
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for example ``getattr(o, '__annotations__', None)``.
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Before Python 3.10, accessing ``__annotations__`` on a class that
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defines no annotations but that has a parent class with
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annotations would return the parent's ``__annotations__``.
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In Python 3.10 and newer, the child class's annotations
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will be an empty dict instead.
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Accessing The Annotations Dict Of An Object In Python 3.9 And Older
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===================================================================
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In Python 3.9 and older, accessing the annotations dict
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of an object is much more complicated than in newer versions.
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The problem is a design flaw in these older versions of Python,
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specifically to do with class annotations.
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Best practice for accessing the annotations dict of other
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objects--functions, other callables, and modules--is the same
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as best practice for 3.10, assuming you aren't calling
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:func:`inspect.get_annotations`: you should use three-argument
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:func:`getattr` to access the object's ``__annotations__``
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attribute.
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Unfortunately, this isn't best practice for classes. The problem
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is that, since ``__annotations__`` is optional on classes, and
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because classes can inherit attributes from their base classes,
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accessing the ``__annotations__`` attribute of a class may
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inadvertently return the annotations dict of a *base class.*
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As an example::
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class Base:
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a: int = 3
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b: str = 'abc'
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class Derived(Base):
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pass
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print(Derived.__annotations__)
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This will print the annotations dict from ``Base``, not
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``Derived``.
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Your code will have to have a separate code path if the object
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you're examining is a class (``isinstance(o, type)``).
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In that case, best practice relies on an implementation detail
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of Python 3.9 and before: if a class has annotations defined,
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they are stored in the class's :attr:`~type.__dict__` dictionary. Since
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the class may or may not have annotations defined, best practice
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is to call the :meth:`~dict.get` method on the class dict.
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To put it all together, here is some sample code that safely
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accesses the ``__annotations__`` attribute on an arbitrary
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object in Python 3.9 and before::
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if isinstance(o, type):
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ann = o.__dict__.get('__annotations__', None)
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else:
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ann = getattr(o, '__annotations__', None)
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After running this code, ``ann`` should be either a
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dictionary or ``None``. You're encouraged to double-check
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the type of ``ann`` using :func:`isinstance` before further
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examination.
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Note that some exotic or malformed type objects may not have
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a :attr:`~type.__dict__` attribute, so for extra safety you may also wish
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to use :func:`getattr` to access :attr:`!__dict__`.
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Manually Un-Stringizing Stringized Annotations
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==============================================
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In situations where some annotations may be "stringized",
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and you wish to evaluate those strings to produce the
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Python values they represent, it really is best to
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call :func:`inspect.get_annotations` to do this work
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for you.
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If you're using Python 3.9 or older, or if for some reason
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you can't use :func:`inspect.get_annotations`, you'll need
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to duplicate its logic. You're encouraged to examine the
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implementation of :func:`inspect.get_annotations` in the
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current Python version and follow a similar approach.
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In a nutshell, if you wish to evaluate a stringized annotation
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on an arbitrary object ``o``:
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* If ``o`` is a module, use ``o.__dict__`` as the
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``globals`` when calling :func:`eval`.
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* If ``o`` is a class, use ``sys.modules[o.__module__].__dict__``
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as the ``globals``, and ``dict(vars(o))`` as the ``locals``,
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when calling :func:`eval`.
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* If ``o`` is a wrapped callable using :func:`functools.update_wrapper`,
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:func:`functools.wraps`, or :func:`functools.partial`, iteratively
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unwrap it by accessing either ``o.__wrapped__`` or ``o.func`` as
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appropriate, until you have found the root unwrapped function.
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* If ``o`` is a callable (but not a class), use
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:attr:`o.__globals__ <function.__globals__>` as the globals when calling
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:func:`eval`.
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However, not all string values used as annotations can
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be successfully turned into Python values by :func:`eval`.
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String values could theoretically contain any valid string,
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and in practice there are valid use cases for type hints that
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require annotating with string values that specifically
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*can't* be evaluated. For example:
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* :pep:`604` union types using ``|``, before support for this
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was added to Python 3.10.
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* Definitions that aren't needed at runtime, only imported
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when :const:`typing.TYPE_CHECKING` is true.
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If :func:`eval` attempts to evaluate such values, it will
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fail and raise an exception. So, when designing a library
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API that works with annotations, it's recommended to only
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attempt to evaluate string values when explicitly requested
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to by the caller.
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Best Practices For ``__annotations__`` In Any Python Version
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============================================================
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* You should avoid assigning to the ``__annotations__`` member
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of objects directly. Let Python manage setting ``__annotations__``.
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* If you do assign directly to the ``__annotations__`` member
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of an object, you should always set it to a ``dict`` object.
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* You should avoid accessing ``__annotations__`` directly on any object.
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Instead, use :func:`annotationlib.get_annotations` (Python 3.14+)
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or :func:`inspect.get_annotations` (Python 3.10+).
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* If you do directly access the ``__annotations__`` member
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of an object, you should ensure that it's a
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dictionary before attempting to examine its contents.
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* You should avoid modifying ``__annotations__`` dicts.
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* You should avoid deleting the ``__annotations__`` attribute
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of an object.
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``__annotations__`` Quirks
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==========================
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In all versions of Python 3, function
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objects lazy-create an annotations dict if no annotations
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are defined on that object. You can delete the ``__annotations__``
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attribute using ``del fn.__annotations__``, but if you then
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access ``fn.__annotations__`` the object will create a new empty dict
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that it will store and return as its annotations. Deleting the
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annotations on a function before it has lazily created its annotations
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dict will throw an ``AttributeError``; using ``del fn.__annotations__``
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twice in a row is guaranteed to always throw an ``AttributeError``.
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Everything in the above paragraph also applies to class and module
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objects in Python 3.10 and newer.
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In all versions of Python 3, you can set ``__annotations__``
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on a function object to ``None``. However, subsequently
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accessing the annotations on that object using ``fn.__annotations__``
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will lazy-create an empty dictionary as per the first paragraph of
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this section. This is *not* true of modules and classes, in any Python
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version; those objects permit setting ``__annotations__`` to any
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Python value, and will retain whatever value is set.
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If Python stringizes your annotations for you
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(using ``from __future__ import annotations``), and you
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specify a string as an annotation, the string will
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itself be quoted. In effect the annotation is quoted
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*twice.* For example::
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from __future__ import annotations
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def foo(a: "str"): pass
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print(foo.__annotations__)
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This prints ``{'a': "'str'"}``. This shouldn't really be considered
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a "quirk"; it's mentioned here simply because it might be surprising.
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If you use a class with a custom metaclass and access ``__annotations__``
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on the class, you may observe unexpected behavior; see
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:pep:`749 <749#pep749-metaclasses>` for some examples. You can avoid these
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quirks by using :func:`annotationlib.get_annotations` on Python 3.14+ or
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:func:`inspect.get_annotations` on Python 3.10+. On earlier versions of
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Python, you can avoid these bugs by accessing the annotations from the
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class's :attr:`~type.__dict__`
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(e.g., ``cls.__dict__.get('__annotations__', None)``).
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