2024-02-10 23:14:42 -05:00
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PEP: 742
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2024-02-15 20:16:03 -05:00
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Title: Narrowing types with TypeIs
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2024-02-10 23:14:42 -05:00
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Author: Jelle Zijlstra <jelle.zijlstra@gmail.com>
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2024-02-15 20:16:03 -05:00
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Discussions-To: https://discuss.python.org/t/pep-742-narrowing-types-with-typenarrower/45613
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Status: Draft
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Type: Standards Track
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Topic: Typing
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Created: 07-Feb-2024
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Python-Version: 3.13
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Post-History: `11-Feb-2024 <https://discuss.python.org/t/pep-742-narrowing-types-with-typenarrower/45613>`__
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Replaces: 724
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Abstract
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========
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This PEP proposes a new special form, ``TypeIs``, to allow annotating functions that can be used
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to narrow the type of a value, similar to the builtin :py:func:`isinstance`. Unlike the existing
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:py:data:`typing.TypeGuard` special form, ``TypeIs`` can narrow the type in both the ``if``
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and ``else`` branches of a conditional.
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Motivation
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==========
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Typed Python code often requires users to narrow the type of a variable based on a conditional.
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For example, if a function accepts a union of two types, it may use an :py:func:`isinstance` check
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to discriminate between the two types. Type checkers commonly support type narrowing based on various
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builtin function and operations, but occasionally, it is useful to use a user-defined function to
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perform type narrowing.
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To support such use cases, :pep:`647` introduced the :py:data:`typing.TypeGuard` special form, which
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allows users to define type guards::
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from typing import assert_type, TypeGuard
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def is_str(x: object) -> TypeGuard[str]:
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return isinstance(x, str)
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def f(x: object) -> None:
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if is_str(x):
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assert_type(x, str)
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else:
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assert_type(x, object)
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Unfortunately, the behavior of :py:data:`typing.TypeGuard` has some limitations that make it
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less useful for many common use cases, as explained also in the "Motivation" section of :pep:`724`.
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In particular:
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* Type checkers must use exactly the ``TypeGuard`` return type as the narrowed type if the
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type guard returns ``True``. They cannot use pre-existing knowledge about the type of the
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variable.
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* In the case where the type guard returns ``False``, the type checker cannot apply any
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additional narrowing.
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The standard library function :py:func:`inspect.isawaitable` may serve as an example. It
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returns whether the argument is an awaitable object, and
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`typeshed <https://github.com/python/typeshed/blob/a4f81a67a07c18dd184dd068c459b02e71bcac22/stdlib/inspect.pyi#L219>`__
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currently annotates it as::
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def isawaitable(object: object) -> TypeGuard[Awaitable[Any]]: ...
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A user `reported <https://github.com/python/mypy/issues/15520>`__ an issue to mypy about
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the behavior of this function. They observed the following behavior::
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import inspect
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from collections.abc import Awaitable
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from typing import reveal_type
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async def f(t: Awaitable[int] | int) -> None:
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if inspect.isawaitable(t):
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reveal_type(t) # Awaitable[Any]
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else:
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reveal_type(t) # Awaitable[int] | int
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This behavior is consistent with :pep:`647`, but it did not match the user's expectations.
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Instead, they would expect the type of ``t`` to be narrowed to ``Awaitable[int]`` in the ``if``
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branch, and to ``int`` in the ``else`` branch. This PEP proposes a new construct that does
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exactly that.
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Other examples of issues that arose out of the current behavior of ``TypeGuard`` include:
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* `Python typing issue <https://github.com/python/typing/issues/996>`__ (``numpy.isscalar``)
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* `Python typing issue <https://github.com/python/typing/issues/1351>`__ (:py:func:`dataclasses.is_dataclass`)
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* `Pyright issue <https://github.com/microsoft/pyright/issues/3450>`__ (expecting :py:data:`typing.TypeGuard` to work like :py:func:`isinstance`)
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* `Pyright issue <https://github.com/microsoft/pyright/issues/3466>`__ (expecting narrowing in the ``else`` branch)
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* `Mypy issue <https://github.com/python/mypy/issues/13957>`__ (expecting narrowing in the ``else`` branch)
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* `Mypy issue <https://github.com/python/mypy/issues/14434>`__ (combining multiple TypeGuards)
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* `Mypy issue <https://github.com/python/mypy/issues/15305>`__ (expecting narrowing in the ``else`` branch)
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* `Mypy issue <https://github.com/python/mypy/issues/11907>`__ (user-defined function similar to :py:func:`inspect.isawaitable`)
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* `Typeshed issue <https://github.com/python/typeshed/issues/8009>`__ (``asyncio.iscoroutinefunction``)
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Rationale
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=========
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The problems with the current behavior of :py:data:`typing.TypeGuard` compel us to improve
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the type system to allow a different type narrowing behavior. :pep:`724` proposed to change
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the behavior of the existing :py:data:`typing.TypeGuard` construct, but we :ref:`believe <pep-742-change-typeguard>`
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that the backwards compatibility implications of that change are too severe. Instead, we propose
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adding a new special form with the desired semantics.
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We acknowledge that this leads to an unfortunate situation where there are two constructs with
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a similar purpose and similar semantics. We believe that users are more likely to want the behavior
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of ``TypeIs``, the new form proposed in this PEP, and therefore we recommend that documentation
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emphasize ``TypeIs`` over ``TypeGuard`` as a more commonly applicable tool. However, the semantics of
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``TypeGuard`` are occasionally useful, and we do not propose to deprecate or remove it. In the long
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run, most users should use ``TypeIs``, and ``TypeGuard`` should be reserved for rare cases
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where its behavior is specifically desired.
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Specification
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=============
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A new special form, ``TypeIs``, is added to the :py:mod:`typing`
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module. Its usage, behavior, and runtime implementation are similar to
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those of :py:data:`typing.TypeGuard`.
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It accepts a single
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argument and can be used as the return type of a function. A function annotated as returning a
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``TypeIs`` is called a type narrowing function. Type narrowing functions must return ``bool``
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values, and the type checker should verify that all return paths return
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``bool``.
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Type narrowing functions must accept at least one positional argument. The type
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narrowing behavior is applied to the first positional argument passed to
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the function. The function may accept additional arguments, but they are
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not affected by type narrowing. If a type narrowing function is implemented as
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an instance method or class method, the first positional argument maps
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to the second parameter (after ``self`` or ``cls``).
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Type narrowing behavior
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-----------------------
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To specify the behavior of ``TypeIs``, we use the following terminology:
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* I = ``TypeIs`` input type
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* R = ``TypeIs`` return type
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* A = Type of argument passed to type narrowing function (pre-narrowed)
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* NP = Narrowed type (positive; used when ``TypeIs`` returned ``True``)
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* NN = Narrowed type (negative; used when ``TypeIs`` returned ``False``)
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.. code-block:: python
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def narrower(x: I) -> TypeIs[R]: ...
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def func1(val: A):
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if narrower(val):
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assert_type(val, NP)
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else:
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assert_type(val, NN)
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The return type ``R`` must be :ref:`consistent with <pep-483-gradual-typing>` ``I``. The type checker should
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emit an error if this condition is not met.
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Formally, type *NP* should be narrowed to :math:`A \land R`,
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the intersection of *A* and *R*, and type *NN* should be narrowed to
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:math:`A \land \neg R`, the intersection of *A* and the complement of *R*.
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In practice, the theoretic types for strict type guards cannot be expressed
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precisely in the Python type system. Type checkers should fall back on
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practical approximations of these types. As a rule of thumb, a type checker
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should use the same type narrowing logic -- and get results that are consistent
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with -- its handling of :py:func:`isinstance`. This guidance allows for changes and
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improvements if the type system is extended in the future.
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Examples
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--------
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Type narrowing is applied in both the positive and negative case::
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from typing import TypeIs, assert_type
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def is_str(x: object) -> TypeIs[str]:
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return isinstance(x, str)
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def f(x: str | int) -> None:
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if is_str(x):
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assert_type(x, str)
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else:
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assert_type(x, int)
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The final narrowed type may be narrower than **R**, due to the constraints of the
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argument's previously-known type::
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from collections.abc import Awaitable
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from typing import Any, TypeIs, assert_type
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import inspect
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def isawaitable(x: object) -> TypeIs[Awaitable[Any]]:
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return inspect.isawaitable(x)
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def f(x: Awaitable[int] | int) -> None:
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if isawaitable(x):
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assert_type(x, Awaitable[int])
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else:
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assert_type(x, int)
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It is an error to narrow to a type that is not consistent with the input type::
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from typing import TypeIs
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def is_str(x: int) -> TypeIs[str]: # Type checker error
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...
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Subtyping
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---------
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``TypeIs`` is not a subtype of ``bool``.
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The type ``Callable[..., TypeIs[int]]`` is not assignable to
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``Callable[..., bool]`` or ``Callable[..., TypeGuard[int]]``, and vice versa.
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This restriction is carried over from :pep:`647`. It may be possible to relax
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it in the future, but that is outside the scope of this PEP.
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Unlike ``TypeGuard``, ``TypeIs`` is invariant in its argument type:
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``TypeIs[B]`` is not a subtype of ``TypeIs[A]``,
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even if ``B`` is a subtype of ``A``.
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To see why, consider the following example::
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def takes_narrower(x: int | str, narrower: Callable[[object], TypeIs[int]]):
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if narrower(x):
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print(x + 1) # x is an int
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else:
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print("Hello " + x) # x is a str
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def is_bool(x: object) -> TypeIs[bool]:
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return isinstance(x, bool)
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takes_narrower(1, is_bool) # Error: is_bool is not a TypeIs[int]
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(Note that ``bool`` is a subtype of ``int``.)
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This code fails at runtime, because the narrower returns ``False`` (1 is not a ``bool``)
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and the ``else`` branch is taken in ``takes_narrower()``.
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If the call ``takes_narrower(1, is_bool)`` was allowed, type checkers would fail to
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detect this error.
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Backwards Compatibility
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=======================
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As this PEP only proposes a new special form, there are no implications on
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backwards compatibility.
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Security Implications
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=====================
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None known.
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How to Teach This
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=================
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Introductions to typing should cover ``TypeIs`` when discussing how to narrow types,
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along with discussion of other narrowing constructs such as :py:func:`isinstance`. The
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documentation should emphasize ``TypeIs`` over :py:data:`typing.TypeGuard`; while the
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latter is not being deprecated and its behavior is occasionally useful, we expect that the
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behavior of ``TypeIs`` is usually more intuitive, and most users should reach for
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``TypeIs`` first. The rest of this section contains some example content that could
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be used in introductory user-facing documentation.
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When to use ``TypeIs``
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----------------------
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Python code often uses functions like ``isinstance()`` to distinguish between
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different possible types of a value. Type checkers understand ``isinstance()``
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and various other checks and use them to narrow the type of a variable. However,
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sometimes you want to reuse a more complicated check in multiple places, or
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you use a check that the type checker doesn't understand. In these cases, you
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can define a ``TypeIs`` function to perform the check and allow type checkers
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to use it to narrow the type of a variable.
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A ``TypeIs`` function takes a single argument and is annotated as returning
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``TypeIs[T]``, where ``T`` is the type that you want to narrow to. The function
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must return ``True`` if the argument is of type ``T``, and ``False`` otherwise.
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The function can then be used in ``if`` checks, just like you would use ``isinstance()``.
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For example::
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from typing import TypeIs, Literal
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type Direction = Literal["N", "E", "S", "W"]
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def is_direction(x: str) -> TypeIs[Direction]:
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return x in {"N", "E", "S", "W"}
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def maybe_direction(x: str) -> None:
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if is_direction(x):
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print(f"{x} is a cardinal direction")
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else:
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print(f"{x} is not a cardinal direction")
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Writing a safe ``TypeIs`` function
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----------------------------------
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A ``TypeIs`` function allows you to override your type checker's type narrowing
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behavior. This is a powerful tool, but it can be dangerous because an incorrectly
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written ``TypeIs`` function can lead to unsound type checking, and type checkers
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cannot detect such errors.
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For a function returning ``TypeIs[T]`` to be safe, it must return ``True`` if and only if
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the argument is compatible with type ``T``, and ``False`` otherwise. If this condition is
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not met, the type checker may infer incorrect types.
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Below are some examples of correct and incorrect ``TypeIs`` functions::
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from typing import TypeIs
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# Correct
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def good_typeis(x: object) -> TypeIs[int]:
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return isinstance(x, int)
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# Incorrect: does not return True for all ints
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def bad_typeis1(x: object) -> TypeIs[int]:
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return isinstance(x, int) and x > 0
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# Incorrect: returns True for some non-ints
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def bad_typeis2(x: object) -> TypeIs[int]:
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return isinstance(x, (int, float))
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This function demonstrates some errors that can occur when using a poorly written
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``TypeIs`` function. These errors are not detected by type checkers::
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def caller(x: int | str, y: int | float) -> None:
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if bad_typeis1(x): # narrowed to int
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print(x + 1)
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else: # narrowed to str (incorrectly)
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print("Hello " + x) # runtime error if x is a negative int
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if bad_typeis2(y): # narrowed to int
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# Because of the incorrect TypeIs, this branch is taken at runtime if
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# y is a float.
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print(y.bit_count()) # runtime error: this method exists only on int, not float
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else: # narrowed to float (though never executed at runtime)
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pass
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Here is an example of a correct ``TypeIs`` function for a more complicated type::
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from typing import TypedDict, TypeIs
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class Point(TypedDict):
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x: int
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y: int
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def is_point(x: object) -> TypeIs[Point]:
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return (
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isinstance(x, dict)
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and all(isinstance(key, str) for key in x)
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and "x" in x
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and "y" in x
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and isinstance(x["x"], int)
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and isinstance(x["y"], int)
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)
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``TypeIs`` and ``TypeGuard``
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----------------------------
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``TypeIs`` and :py:data:`typing.TypeGuard` are both tools for narrowing the type of a variable
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based on a user-defined function. Both can be used to annotate functions that take an
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argument and return a boolean depending on whether the input argument is compatible with
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the narrowed type. These function can then be used in ``if`` checks to narrow the type
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of a variable.
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``TypeIs`` usually has the most intuitive behavior, but it
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introduces more restrictions. ``TypeGuard`` is the right tool to use if:
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* You want to narrow to a type that is not compatible with the input type, for example
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from ``list[object]`` to ``list[int]``. ``TypeIs`` only allows narrowing between
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compatible types.
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* Your function does not return ``True`` for all input values that are compatible with
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the narrowed type. For example, you could have a ``TypeGuard[int]`` that returns ``True``
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only for positive integers.
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``TypeIs`` and ``TypeGuard`` differ in the following ways:
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* ``TypeIs`` requires the narrowed type to be a subtype of the input type, while
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``TypeGuard`` does not.
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* When a ``TypeGuard`` function returns ``True``, type checkers narrow the type of the
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variable to exactly the ``TypeGuard`` type. When a ``TypeIs`` function returns ``True``,
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type checkers can infer a more precise type combining the previously known type of the
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variable with the ``TypeIs`` type. (Technically, this is known as an intersection type.)
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* When a ``TypeGuard`` function returns ``False``, type checkers cannot narrow the type of
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the variable at all. When a ``TypeIs`` function returns ``False``, type checkers can narrow
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the type of the variable to exclude the ``TypeIs`` type.
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This behavior can be seen in the following example::
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from typing import TypeGuard, TypeIs, reveal_type, final
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class Base: ...
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class Child(Base): ...
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@final
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class Unrelated: ...
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def is_base_typeguard(x: object) -> TypeGuard[Base]:
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return isinstance(x, Base)
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def is_base_typeis(x: object) -> TypeIs[Base]:
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return isinstance(x, Base)
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def use_typeguard(x: Child | Unrelated) -> None:
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if is_base_typeguard(x):
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reveal_type(x) # Base
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else:
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reveal_type(x) # Child | Unrelated
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def use_typeis(x: Child | Unrelated) -> None:
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if is_base_typeis(x):
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reveal_type(x) # Child
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else:
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reveal_type(x) # Unrelated
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2024-02-10 23:14:42 -05:00
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Reference Implementation
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========================
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2024-02-22 23:55:29 -05:00
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The ``TypeIs`` special form `has been implemented <https://github.com/python/typing_extensions/pull/330>`__
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in the ``typing_extensions`` module and will be released in typing_extensions 4.10.0.
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Implementations are available for several type checkers:
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2024-02-10 23:14:42 -05:00
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2024-02-22 23:55:29 -05:00
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- Mypy: `pull request open <https://github.com/python/mypy/pull/16898>`__
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- Pyanalyze: `pull request <https://github.com/quora/pyanalyze/pull/718>`__
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- Pyright: `added in version 1.1.351 <https://github.com/microsoft/pyright/releases/tag/1.1.351>`__
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2024-02-10 23:14:42 -05:00
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Rejected Ideas
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==============
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.. _pep-742-change-typeguard:
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Change the behavior of ``TypeGuard``
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------------------------------------
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:pep:`724` previously proposed changing the specified behavior of :py:data:`typing.TypeGuard` so
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that if the return type of the guard is consistent with the input type, the behavior proposed
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2024-02-15 20:16:03 -05:00
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here for ``TypeIs`` would apply. This proposal has some important advantages: because it
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2024-02-10 23:14:42 -05:00
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does not require any runtime changes, it requires changes only in type checkers, making it easier
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for users to take advantage of the new, usually more intuitive behavior.
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However, this approach has some major problems. Users who have written ``TypeGuard`` functions
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expecting the existing semantics specified in :pep:`647` would see subtle and potentially breaking
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changes in how type checkers interpret their code. The split behavior of ``TypeGuard``, where it
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works one way if the return type is consistent with the input type and another way if it is not,
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could be confusing for users. The Typing Council was unable to come to an agreement in favor of
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:pep:`724`; as a result, we are proposing this alternative PEP.
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Do nothing
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----------
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Both this PEP and the alternative proposed in :pep:`724` have shortcomings. The latter are
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discussed above. As for this PEP, it introduces two special forms with very similar semantics,
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and it potentially creates a long migration path for users currently using ``TypeGuard``
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who would be better off with different narrowing semantics.
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One way forward, then, is to do nothing and live with the current limitations of the type system.
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However, we believe that the limitations of the current ``TypeGuard``, as outlined in the "Motivation"
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section, are significant enough that it is worthwhile to change the type system to address them.
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If we do not make any change, users will continue to encounter the same unintuitive behaviors from
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``TypeGuard``, and the type system will be unable to properly represent common type narrowing functions
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like ``inspect.isawaitable``.
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|
2024-02-15 20:16:03 -05:00
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Alternative names
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-----------------
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2024-02-10 23:14:42 -05:00
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2024-02-15 20:16:03 -05:00
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This PEP currently proposes the name ``TypeIs``, emphasizing that the special form ``TypeIs[T]``
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returns whether the argument is of type ``T``, and mirroring
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`TypeScript's syntax <https://www.typescriptlang.org/docs/handbook/2/narrowing.html#using-type-predicates>`__.
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Other names were considered, including in an earlier version of this PEP.
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2024-02-10 23:14:42 -05:00
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Options include:
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* ``IsInstance`` (`post by Paul Moore <https://discuss.python.org/t/pep-724-stricter-type-guards/34124/60>`__):
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emphasizes that the new construct behaves similarly to the builtin :py:func:`isinstance`.
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* ``Narrowed`` or ``NarrowedTo``: shorter than ``TypeNarrower`` but keeps the connection to "type narrowing"
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(suggested by Eric Traut).
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* ``Predicate`` or ``TypePredicate``: mirrors TypeScript's name for the feature, "type predicates".
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* ``StrictTypeGuard`` (earlier drafts of :pep:`724`): emphasizes that the new construct performs a stricter
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version of type narrowing than :py:data:`typing.TypeGuard`.
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* ``TypeCheck`` (`post by Nicolas Tessore <https://discuss.python.org/t/pep-724-stricter-type-guards/34124/59>`__):
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emphasizes the binary nature of the check.
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2024-02-15 20:16:03 -05:00
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* ``TypeNarrower``: emphasizes that the function narrows its argument type. Used in an earlier version of this PEP.
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2024-02-10 23:14:42 -05:00
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Acknowledgments
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===============
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Much of the motivation and specification for this PEP derives from :pep:`724`. While
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this PEP proposes a different solution for the problem at hand, the authors of :pep:`724`, Eric Traut, Rich
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Chiodo, and Erik De Bonte, made a strong case for their proposal and this proposal
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would not have been possible without their work.
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Copyright
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=========
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This document is placed in the public domain or under the
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CC0-1.0-Universal license, whichever is more permissive.
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