python-peps/peps/pep-0742.rst

PEP: 742
Title: Narrowing types with TypeIs
Author: Jelle Zijlstra <jelle.zijlstra@gmail.com>
Discussions-To: https://discuss.python.org/t/pep-742-narrowing-types-with-typenarrower/45613
Status: Final
Type: Standards Track
Topic: Typing
Created: 07-Feb-2024
Python-Version: 3.13
Post-History: `11-Feb-2024 <https://discuss.python.org/t/pep-742-narrowing-types-with-typenarrower/45613>`__
Replaces: 724
Resolution: https://discuss.python.org/t/pep-742-narrowing-types-with-typeis/45613/35

.. canonical-typing-spec:: :ref:`typing:typeis` and
                           :external+py3.13:data:`typing.TypeIs`

Abstract
========

This PEP proposes a new special form, ``TypeIs``, to allow annotating functions that can be used
to narrow the type of a value, similar to the builtin :py:func:`isinstance`. Unlike the existing
:py:data:`typing.TypeGuard` special form, ``TypeIs`` can narrow the type in both the ``if``
and ``else`` branches of a conditional.


Motivation
==========

Typed Python code often requires users to narrow the type of a variable based on a conditional.
For example, if a function accepts a union of two types, it may use an :py:func:`isinstance` check
to discriminate between the two types. Type checkers commonly support type narrowing based on various
builtin function and operations, but occasionally, it is useful to use a user-defined function to
perform type narrowing.

To support such use cases, :pep:`647` introduced the :py:data:`typing.TypeGuard` special form, which
allows users to define type guards::

    from typing import assert_type, TypeGuard

    def is_str(x: object) -> TypeGuard[str]:
        return isinstance(x, str)

    def f(x: object) -> None:
        if is_str(x):
            assert_type(x, str)
        else:
            assert_type(x, object)

Unfortunately, the behavior of :py:data:`typing.TypeGuard` has some limitations that make it
less useful for many common use cases, as explained also in the "Motivation" section of :pep:`724`.
In particular:

* Type checkers must use exactly the ``TypeGuard`` return type as the narrowed type if the
  type guard returns ``True``. They cannot use pre-existing knowledge about the type of the
  variable.
* In the case where the type guard returns ``False``, the type checker cannot apply any
  additional narrowing.

The standard library function :py:func:`inspect.isawaitable` may serve as an example. It
returns whether the argument is an awaitable object, and
`typeshed <https://github.com/python/typeshed/blob/a4f81a67a07c18dd184dd068c459b02e71bcac22/stdlib/inspect.pyi#L219>`__
currently annotates it as::

    def isawaitable(object: object) -> TypeGuard[Awaitable[Any]]: ...

A user `reported <https://github.com/python/mypy/issues/15520>`__ an issue to mypy about
the behavior of this function. They observed the following behavior::

    import inspect
    from collections.abc import Awaitable
    from typing import reveal_type

    async def f(t: Awaitable[int] | int) -> None:
        if inspect.isawaitable(t):
            reveal_type(t)  # Awaitable[Any]
        else:
            reveal_type(t)  # Awaitable[int] | int

This behavior is consistent with :pep:`647`, but it did not match the user's expectations.
Instead, they would expect the type of ``t`` to be narrowed to ``Awaitable[int]`` in the ``if``
branch, and to ``int`` in the ``else`` branch. This PEP proposes a new construct that does
exactly that.

Other examples of issues that arose out of the current behavior of ``TypeGuard`` include:

* `Python typing issue <https://github.com/python/typing/issues/996>`__ (``numpy.isscalar``)
* `Python typing issue <https://github.com/python/typing/issues/1351>`__ (:py:func:`dataclasses.is_dataclass`)
* `Pyright issue <https://github.com/microsoft/pyright/issues/3450>`__ (expecting :py:data:`typing.TypeGuard` to work like :py:func:`isinstance`)
* `Pyright issue <https://github.com/microsoft/pyright/issues/3466>`__ (expecting narrowing in the ``else`` branch)
* `Mypy issue <https://github.com/python/mypy/issues/13957>`__ (expecting narrowing in the ``else`` branch)
* `Mypy issue <https://github.com/python/mypy/issues/14434>`__ (combining multiple TypeGuards)
* `Mypy issue <https://github.com/python/mypy/issues/15305>`__ (expecting narrowing in the ``else`` branch)
* `Mypy issue <https://github.com/python/mypy/issues/11907>`__ (user-defined function similar to :py:func:`inspect.isawaitable`)
* `Typeshed issue <https://github.com/python/typeshed/issues/8009>`__ (``asyncio.iscoroutinefunction``)

Rationale
=========

The problems with the current behavior of :py:data:`typing.TypeGuard` compel us to improve
the type system to allow a different type narrowing behavior. :pep:`724` proposed to change
the behavior of the existing :py:data:`typing.TypeGuard` construct, but we :ref:`believe <pep-742-change-typeguard>`
that the backwards compatibility implications of that change are too severe. Instead, we propose
adding a new special form with the desired semantics.

We acknowledge that this leads to an unfortunate situation where there are two constructs with
a similar purpose and similar semantics. We believe that users are more likely to want the behavior
of ``TypeIs``, the new form proposed in this PEP, and therefore we recommend that documentation
emphasize ``TypeIs`` over ``TypeGuard`` as a more commonly applicable tool. However, the semantics of
``TypeGuard`` are occasionally useful, and we do not propose to deprecate or remove it. In the long
run, most users should use ``TypeIs``, and ``TypeGuard`` should be reserved for rare cases
where its behavior is specifically desired.


Specification
=============

A new special form, ``TypeIs``, is added to the :py:mod:`typing`
module. Its usage, behavior, and runtime implementation are similar to
those of :py:data:`typing.TypeGuard`.

It accepts a single
argument and can be used as the return type of a function. A function annotated as returning a
``TypeIs`` is called a type narrowing function. Type narrowing functions must return ``bool``
values, and the type checker should verify that all return paths return
``bool``.

Type narrowing functions must accept at least one positional argument. The type
narrowing behavior is applied to the first positional argument passed to
the function. The function may accept additional arguments, but they are
not affected by type narrowing. If a type narrowing function is implemented as
an instance method or class method, the first positional argument maps
to the second parameter (after ``self`` or ``cls``).

Type narrowing behavior
-----------------------

To specify the behavior of ``TypeIs``, we use the following terminology:

* I = ``TypeIs`` input type
* R = ``TypeIs`` return type
* A = Type of argument passed to type narrowing function (pre-narrowed)
* NP = Narrowed type (positive; used when ``TypeIs`` returned ``True``)
* NN = Narrowed type (negative; used when ``TypeIs`` returned ``False``)

.. code-block:: python

    def narrower(x: I) -> TypeIs[R]: ...

    def func1(val: A):
        if narrower(val):
            assert_type(val, NP)
        else:
            assert_type(val, NN)

The return type ``R`` must be :ref:`consistent with <pep-483-gradual-typing>` ``I``. The type checker should
emit an error if this condition is not met.

Formally, type *NP* should be narrowed to :math:`A \land R`,
the intersection of *A* and *R*, and type *NN* should be narrowed to
:math:`A \land \neg R`, the intersection of *A* and the complement of *R*.
In practice, the theoretic types for strict type guards cannot be expressed
precisely in the Python type system. Type checkers should fall back on
practical approximations of these types. As a rule of thumb, a type checker
should use the same type narrowing logic -- and get results that are consistent
with -- its handling of :py:func:`isinstance`. This guidance allows for changes and
improvements if the type system is extended in the future.

Examples
--------

Type narrowing is applied in both the positive and negative case::

    from typing import TypeIs, assert_type

    def is_str(x: object) -> TypeIs[str]:
        return isinstance(x, str)

    def f(x: str | int) -> None:
        if is_str(x):
            assert_type(x, str)
        else:
            assert_type(x, int)

The final narrowed type may be narrower than **R**, due to the constraints of the
argument's previously-known type::

    from collections.abc import Awaitable
    from typing import Any, TypeIs, assert_type
    import inspect

    def isawaitable(x: object) -> TypeIs[Awaitable[Any]]:
        return inspect.isawaitable(x)

    def f(x: Awaitable[int] | int) -> None:
        if isawaitable(x):
            # Type checkers may also infer the more precise type
            # "Awaitable[int] | (int & Awaitable[Any])"
            assert_type(x, Awaitable[int])
        else:
            assert_type(x, int)

It is an error to narrow to a type that is not consistent with the input type::

    from typing import TypeIs

    def is_str(x: int) -> TypeIs[str]:  # Type checker error
        ...

Subtyping
---------

``TypeIs`` is also valid as the return type of a callable, for example
in callback protocols and in the ``Callable`` special form. In these
contexts, it is treated as a subtype of bool. For example, ``Callable[..., TypeIs[int]]``
is assignable to ``Callable[..., bool]``.

Unlike ``TypeGuard``, ``TypeIs`` is invariant in its argument type:
``TypeIs[B]`` is not a subtype of ``TypeIs[A]``,
even if ``B`` is a subtype of ``A``.
To see why, consider the following example::

    def takes_narrower(x: int | str, narrower: Callable[[object], TypeIs[int]]):
        if narrower(x):
            print(x + 1)  # x is an int
        else:
            print("Hello " + x)  # x is a str

    def is_bool(x: object) -> TypeIs[bool]:
        return isinstance(x, bool)

    takes_narrower(1, is_bool)  # Error: is_bool is not a TypeIs[int]

(Note that ``bool`` is a subtype of ``int``.)
This code fails at runtime, because the narrower returns ``False`` (1 is not a ``bool``)
and the ``else`` branch is taken in ``takes_narrower()``.
If the call ``takes_narrower(1, is_bool)`` was allowed, type checkers would fail to
detect this error.

Backwards Compatibility
=======================

As this PEP only proposes a new special form, there are no implications on
backwards compatibility.


Security Implications
=====================

None known.


How to Teach This
=================

Introductions to typing should cover ``TypeIs`` when discussing how to narrow types,
along with discussion of other narrowing constructs such as :py:func:`isinstance`. The
documentation should emphasize ``TypeIs`` over :py:data:`typing.TypeGuard`; while the
latter is not being deprecated and its behavior is occasionally useful, we expect that the
behavior of ``TypeIs`` is usually more intuitive, and most users should reach for
``TypeIs`` first. The rest of this section contains some example content that could
be used in introductory user-facing documentation.

When to use ``TypeIs``
----------------------

Python code often uses functions like ``isinstance()`` to distinguish between
different possible types of a value. Type checkers understand ``isinstance()``
and various other checks and use them to narrow the type of a variable. However,
sometimes you want to reuse a more complicated check in multiple places, or
you use a check that the type checker doesn't understand. In these cases, you
can define a ``TypeIs`` function to perform the check and allow type checkers
to use it to narrow the type of a variable.

A ``TypeIs`` function takes a single argument and is annotated as returning
``TypeIs[T]``, where ``T`` is the type that you want to narrow to. The function
must return ``True`` if the argument is of type ``T``, and ``False`` otherwise.
The function can then be used in ``if`` checks, just like you would use ``isinstance()``.
For example::

    from typing import TypeIs, Literal

    type Direction = Literal["N", "E", "S", "W"]

    def is_direction(x: str) -> TypeIs[Direction]:
        return x in {"N", "E", "S", "W"}

    def maybe_direction(x: str) -> None:
        if is_direction(x):
            print(f"{x} is a cardinal direction")
        else:
            print(f"{x} is not a cardinal direction")

Writing a safe ``TypeIs`` function
----------------------------------

A ``TypeIs`` function allows you to override your type checker's type narrowing
behavior. This is a powerful tool, but it can be dangerous because an incorrectly
written ``TypeIs`` function can lead to unsound type checking, and type checkers
cannot detect such errors.

For a function returning ``TypeIs[T]`` to be safe, it must return ``True`` if and only if
the argument is compatible with type ``T``, and ``False`` otherwise. If this condition is
not met, the type checker may infer incorrect types.

Below are some examples of correct and incorrect ``TypeIs`` functions::

    from typing import TypeIs

    # Correct
    def good_typeis(x: object) -> TypeIs[int]:
        return isinstance(x, int)

    # Incorrect: does not return True for all ints
    def bad_typeis1(x: object) -> TypeIs[int]:
        return isinstance(x, int) and x > 0

    # Incorrect: returns True for some non-ints
    def bad_typeis2(x: object) -> TypeIs[int]:
        return isinstance(x, (int, float))

This function demonstrates some errors that can occur when using a poorly written
``TypeIs`` function. These errors are not detected by type checkers::

    def caller(x: int | str, y: int | float) -> None:
        if bad_typeis1(x):  # narrowed to int
            print(x + 1)
        else:  # narrowed to str (incorrectly)
            print("Hello " + x)  # runtime error if x is a negative int

        if bad_typeis2(y):  # narrowed to int
            # Because of the incorrect TypeIs, this branch is taken at runtime if
            # y is a float.
            print(y.bit_count())  # runtime error: this method exists only on int, not float
        else:  # narrowed to float (though never executed at runtime)
            pass

Here is an example of a correct ``TypeIs`` function for a more complicated type::

    from typing import TypedDict, TypeIs

    class Point(TypedDict):
        x: int
        y: int

    def is_point(x: object) -> TypeIs[Point]:
        return (
            isinstance(x, dict)
            and all(isinstance(key, str) for key in x)
            and "x" in x
            and "y" in x
            and isinstance(x["x"], int)
            and isinstance(x["y"], int)
        )

``TypeIs`` and ``TypeGuard``
----------------------------

``TypeIs`` and :py:data:`typing.TypeGuard` are both tools for narrowing the type of a variable
based on a user-defined function. Both can be used to annotate functions that take an
argument and return a boolean depending on whether the input argument is compatible with
the narrowed type. These function can then be used in ``if`` checks to narrow the type
of a variable.

``TypeIs`` usually has the most intuitive behavior, but it
introduces more restrictions. ``TypeGuard`` is the right tool to use if:

* You want to narrow to a type that is not compatible with the input type, for example
  from ``list[object]`` to ``list[int]``.  ``TypeIs`` only allows narrowing between
  compatible types.
* Your function does not return ``True`` for all input values that are compatible with
  the narrowed type. For example, you could have a ``TypeGuard[int]`` that returns ``True``
  only for positive integers.

``TypeIs`` and ``TypeGuard`` differ in the following ways:

* ``TypeIs`` requires the narrowed type to be a subtype of the input type, while
  ``TypeGuard`` does not.
* When a ``TypeGuard`` function returns ``True``, type checkers narrow the type of the
  variable to exactly the ``TypeGuard`` type. When a ``TypeIs`` function returns ``True``,
  type checkers can infer a more precise type combining the previously known type of the
  variable with the ``TypeIs`` type. (Technically, this is known as an intersection type.)
* When a ``TypeGuard`` function returns ``False``, type checkers cannot narrow the type of
  the variable at all. When a ``TypeIs`` function returns ``False``, type checkers can narrow
  the type of the variable to exclude the ``TypeIs`` type.

This behavior can be seen in the following example::

    from typing import TypeGuard, TypeIs, reveal_type, final

    class Base: ...
    class Child(Base): ...
    @final
    class Unrelated: ...

    def is_base_typeguard(x: object) -> TypeGuard[Base]:
        return isinstance(x, Base)

    def is_base_typeis(x: object) -> TypeIs[Base]:
        return isinstance(x, Base)

    def use_typeguard(x: Child | Unrelated) -> None:
        if is_base_typeguard(x):
            reveal_type(x)  # Base
        else:
            reveal_type(x)  # Child | Unrelated

    def use_typeis(x: Child | Unrelated) -> None:
        if is_base_typeis(x):
            reveal_type(x)  # Child
        else:
            reveal_type(x)  # Unrelated

Reference Implementation
========================

The ``TypeIs`` special form `has been implemented <https://github.com/python/typing_extensions/pull/330>`__
in the ``typing_extensions`` module and will be released in typing_extensions 4.10.0.

Implementations are available for several type checkers:

- Mypy: `pull request open <https://github.com/python/mypy/pull/16898>`__
- Pyanalyze: `pull request <https://github.com/quora/pyanalyze/pull/718>`__
- Pyright: `added in version 1.1.351 <https://github.com/microsoft/pyright/releases/tag/1.1.351>`__

Rejected Ideas
==============

.. _pep-742-change-typeguard:

Change the behavior of ``TypeGuard``
------------------------------------

:pep:`724` previously proposed changing the specified behavior of :py:data:`typing.TypeGuard` so
that if the return type of the guard is consistent with the input type, the behavior proposed
here for ``TypeIs`` would apply. This proposal has some important advantages: because it
does not require any runtime changes, it requires changes only in type checkers, making it easier
for users to take advantage of the new, usually more intuitive behavior.

However, this approach has some major problems. Users who have written ``TypeGuard`` functions
expecting the existing semantics specified in :pep:`647` would see subtle and potentially breaking
changes in how type checkers interpret their code. The split behavior of ``TypeGuard``, where it
works one way if the return type is consistent with the input type and another way if it is not,
could be confusing for users. The Typing Council was unable to come to an agreement in favor of
:pep:`724`; as a result, we are proposing this alternative PEP.

Do nothing
----------

Both this PEP and the alternative proposed in :pep:`724` have shortcomings. The latter are
discussed above. As for this PEP, it introduces two special forms with very similar semantics,
and it potentially creates a long migration path for users currently using ``TypeGuard``
who would be better off with different narrowing semantics.

One way forward, then, is to do nothing and live with the current limitations of the type system.
However, we believe that the limitations of the current ``TypeGuard``, as outlined in the "Motivation"
section, are significant enough that it is worthwhile to change the type system to address them.
If we do not make any change, users will continue to encounter the same unintuitive behaviors from
``TypeGuard``, and the type system will be unable to properly represent common type narrowing functions
like ``inspect.isawaitable``.

Alternative names
-----------------

This PEP currently proposes the name ``TypeIs``, emphasizing that the special form ``TypeIs[T]``
returns whether the argument is of type ``T``, and mirroring
`TypeScript's syntax <https://www.typescriptlang.org/docs/handbook/2/narrowing.html#using-type-predicates>`__.
Other names were considered, including in an earlier version of this PEP.

Options include:

* ``IsInstance`` (`post by Paul Moore <https://discuss.python.org/t/pep-724-stricter-type-guards/34124/60>`__):
  emphasizes that the new construct behaves similarly to the builtin :py:func:`isinstance`.
* ``Narrowed`` or ``NarrowedTo``: shorter than ``TypeNarrower`` but keeps the connection to "type narrowing"
  (suggested by Eric Traut).
* ``Predicate`` or ``TypePredicate``: mirrors TypeScript's name for the feature, "type predicates".
* ``StrictTypeGuard`` (earlier drafts of :pep:`724`): emphasizes that the new construct performs a stricter
  version of type narrowing than :py:data:`typing.TypeGuard`.
* ``TypeCheck`` (`post by Nicolas Tessore <https://discuss.python.org/t/pep-724-stricter-type-guards/34124/59>`__):
  emphasizes the binary nature of the check.
* ``TypeNarrower``: emphasizes that the function narrows its argument type. Used in an earlier version of this PEP.

Acknowledgments
===============

Much of the motivation and specification for this PEP derives from :pep:`724`. While
this PEP proposes a different solution for the problem at hand, the authors of :pep:`724`, Eric Traut, Rich
Chiodo, and Erik De Bonte, made a strong case for their proposal and this proposal
would not have been possible without their work.


Copyright
=========

This document is placed in the public domain or under the
CC0-1.0-Universal license, whichever is more permissive.