githubmirror/cpython

Doc/howto/annotations.rst
233 строки9 KB
Alex Waygood
[3.12] gh-101100: Add a table of class attributes to the "Custom classes" section of the data model docs (#124480) (#124558)
26 сен 2024, 02:01
Не верифицирован
26 сен 2024, 02:01d2068c6
.. _annotations-howto:

**************************
Annotations Best Practices
**************************

:author: Larry Hastings

.. topic:: Abstract

  This document is designed to encapsulate the best practices
  for working with annotations dicts.  If you write Python code
  that examines ``__annotations__`` on Python objects, we
  encourage you to follow the guidelines described below.

  The document is organized into four sections:
  best practices for accessing the annotations of an object
  in Python versions 3.10 and newer,
  best practices for accessing the annotations of an object
  in Python versions 3.9 and older,
  other best practices
  for ``__annotations__`` that apply to any Python version,
  and
  quirks of ``__annotations__``.

  Note that this document is specifically about working with
  ``__annotations__``, not uses *for* annotations.
  If you're looking for information on how to use "type hints"
  in your code, please see the :mod:`typing` module.


Accessing The Annotations Dict Of An Object In Python 3.10 And Newer
====================================================================

Python 3.10 adds a new function to the standard library:
:func:`inspect.get_annotations`.  In Python versions 3.10
and newer, calling this function is the best practice for
accessing the annotations dict of any object that supports
annotations.  This function can also "un-stringize"
stringized annotations for you.

If for some reason :func:`inspect.get_annotations` isn't
viable for your use case, you may access the
``__annotations__`` data member manually.  Best practice
for this changed in Python 3.10 as well: as of Python 3.10,
``o.__annotations__`` is guaranteed to *always* work
on Python functions, classes, and modules.  If you're
certain the object you're examining is one of these three
*specific* objects, you may simply use ``o.__annotations__``
to get at the object's annotations dict.

However, other types of callables--for example,
callables created by :func:`functools.partial`--may
not have an ``__annotations__`` attribute defined.  When
accessing the ``__annotations__`` of a possibly unknown
object,  best practice in Python versions 3.10 and
newer is to call :func:`getattr` with three arguments,
for example ``getattr(o, '__annotations__', None)``.

Before Python 3.10, accessing ``__annotations__`` on a class that
defines no annotations but that has a parent class with
annotations would return the parent's ``__annotations__``.
In Python 3.10 and newer, the child class's annotations
will be an empty dict instead.


Accessing The Annotations Dict Of An Object In Python 3.9 And Older
===================================================================

In Python 3.9 and older, accessing the annotations dict
of an object is much more complicated than in newer versions.
The problem is a design flaw in these older versions of Python,
specifically to do with class annotations.

Best practice for accessing the annotations dict of other
objects--functions, other callables, and modules--is the same
as best practice for 3.10, assuming you aren't calling
:func:`inspect.get_annotations`: you should use three-argument
:func:`getattr` to access the object's ``__annotations__``
attribute.

Unfortunately, this isn't best practice for classes.  The problem
is that, since ``__annotations__`` is optional on classes, and
because classes can inherit attributes from their base classes,
accessing the ``__annotations__`` attribute of a class may
inadvertently return the annotations dict of a *base class.*
As an example::

    class Base:
        a: int = 3
        b: str = 'abc'

    class Derived(Base):
        pass

    print(Derived.__annotations__)

This will print the annotations dict from ``Base``, not
``Derived``.

Your code will have to have a separate code path if the object
you're examining is a class (``isinstance(o, type)``).
In that case, best practice relies on an implementation detail
of Python 3.9 and before: if a class has annotations defined,
they are stored in the class's :attr:`~type.__dict__` dictionary.  Since
the class may or may not have annotations defined, best practice
is to call the :meth:`~dict.get` method on the class dict.

To put it all together, here is some sample code that safely
accesses the ``__annotations__`` attribute on an arbitrary
object in Python 3.9 and before::

    if isinstance(o, type):
        ann = o.__dict__.get('__annotations__', None)
    else:
        ann = getattr(o, '__annotations__', None)

After running this code, ``ann`` should be either a
dictionary or ``None``.  You're encouraged to double-check
the type of ``ann`` using :func:`isinstance` before further
examination.

Note that some exotic or malformed type objects may not have
a :attr:`~type.__dict__` attribute, so for extra safety you may also wish
to use :func:`getattr` to access :attr:`!__dict__`.


Manually Un-Stringizing Stringized Annotations
==============================================

In situations where some annotations may be "stringized",
and you wish to evaluate those strings to produce the
Python values they represent, it really is best to
call :func:`inspect.get_annotations` to do this work
for you.

If you're using Python 3.9 or older, or if for some reason
you can't use :func:`inspect.get_annotations`, you'll need
to duplicate its logic.  You're encouraged to examine the
implementation of :func:`inspect.get_annotations` in the
current Python version and follow a similar approach.

In a nutshell, if you wish to evaluate a stringized annotation
on an arbitrary object ``o``:

* If ``o`` is a module, use ``o.__dict__`` as the
  ``globals`` when calling :func:`eval`.
* If ``o`` is a class, use ``sys.modules[o.__module__].__dict__``
  as the ``globals``, and ``dict(vars(o))`` as the ``locals``,
  when calling :func:`eval`.
* If ``o`` is a wrapped callable using :func:`functools.update_wrapper`,
  :func:`functools.wraps`, or :func:`functools.partial`, iteratively
  unwrap it by accessing either ``o.__wrapped__`` or ``o.func`` as
  appropriate, until you have found the root unwrapped function.
* If ``o`` is a callable (but not a class), use
  :attr:`o.__globals__ <function.__globals__>` as the globals when calling
  :func:`eval`.

However, not all string values used as annotations can
be successfully turned into Python values by :func:`eval`.
String values could theoretically contain any valid string,
and in practice there are valid use cases for type hints that
require annotating with string values that specifically
*can't* be evaluated.  For example:

* :pep:`604` union types using ``|``, before support for this
  was added to Python 3.10.
* Definitions that aren't needed at runtime, only imported
  when :const:`typing.TYPE_CHECKING` is true.

If :func:`eval` attempts to evaluate such values, it will
fail and raise an exception.  So, when designing a library
API that works with annotations, it's recommended to only
attempt to evaluate string values when explicitly requested
to by the caller.


Best Practices For ``__annotations__`` In Any Python Version
============================================================

* You should avoid assigning to the ``__annotations__`` member
  of objects directly.  Let Python manage setting ``__annotations__``.

* If you do assign directly to the ``__annotations__`` member
  of an object, you should always set it to a ``dict`` object.

* If you directly access the ``__annotations__`` member
  of an object, you should ensure that it's a
  dictionary before attempting to examine its contents.

* You should avoid modifying ``__annotations__`` dicts.

* You should avoid deleting the ``__annotations__`` attribute
  of an object.


``__annotations__`` Quirks
==========================

In all versions of Python 3, function
objects lazy-create an annotations dict if no annotations
are defined on that object.  You can delete the ``__annotations__``
attribute using ``del fn.__annotations__``, but if you then
access ``fn.__annotations__`` the object will create a new empty dict
that it will store and return as its annotations.  Deleting the
annotations on a function before it has lazily created its annotations
dict will throw an ``AttributeError``; using ``del fn.__annotations__``
twice in a row is guaranteed to always throw an ``AttributeError``.

Everything in the above paragraph also applies to class and module
objects in Python 3.10 and newer.

In all versions of Python 3, you can set ``__annotations__``
on a function object to ``None``.  However, subsequently
accessing the annotations on that object using ``fn.__annotations__``
will lazy-create an empty dictionary as per the first paragraph of
this section.  This is *not* true of modules and classes, in any Python
version; those objects permit setting ``__annotations__`` to any
Python value, and will retain whatever value is set.

If Python stringizes your annotations for you
(using ``from __future__ import annotations``), and you
specify a string as an annotation, the string will
itself be quoted.  In effect the annotation is quoted
*twice.*  For example::

     from __future__ import annotations
     def foo(a: "str"): pass

     print(foo.__annotations__)

This prints ``{'a': "'str'"}``.  This shouldn't really be considered
a "quirk"; it's mentioned here simply because it might be surprising.