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PEP: 724
Title: Stricter Type Guards
Author: Rich Chiodo <rchiodo at microsoft.com>,
Eric Traut <erictr at microsoft.com>,
Erik De Bonte <erikd at microsoft.com>,
Sponsor: Jelle Zijlstra <jelle.zijlstra@gmail.com>
Discussions-To: https://discuss.python.org/t/pep-724-stricter-type-guards/34124
Status: Draft
Type: Standards Track
Topic: Typing
Content-Type: text/x-rst
Created: 28-Jul-2023
Python-Version: 3.13
Post-History: `30-Dec-2021 <https://mail.python.org/archives/list/typing-sig@python.org/thread/EMUD2D424OI53DCWQ4H5L6SJD2IXBHUL/>`__,
`19-Sep-2023 <https://discuss.python.org/t/pep-724-stricter-type-guards/34124>`__,
Abstract
========
:pep:`647` introduced the concept of a user-defined type guard function which
returns ``True`` if the type of the expression passed to its first parameter
matches its return ``TypeGuard`` type. For example, a function that has a
return type of ``TypeGuard[str]`` is assumed to return ``True`` if and only if
the type of the expression passed to its first input parameter is a ``str``.
This allows type checkers to narrow types when a user-defined type guard
function returns ``True``.
This PEP refines the ``TypeGuard`` mechanism introduced in :pep:`647`. It
allows type checkers to narrow types when a user-defined type guard function
returns ``False``. It also allows type checkers to apply additional (more
precise) type narrowing under certain circumstances when the type guard
function returns ``True``.
Motivation
==========
User-defined type guard functions enable a type checker to narrow the type of
an expression when it is passed as an argument to the type guard function. The
``TypeGuard`` mechanism introduced in :pep:`647` is flexible, but this
flexibility imposes some limitations that developers have found inconvenient
for some uses.
Limitation 1: Type checkers are not allowed to narrow a type in the case where
the type guard function returns ``False``. This means the type is not narrowed
in the negative ("else") clause.
Limitation 2: Type checkers must use the ``TypeGuard`` return type if the type
guard function returns ``True`` regardless of whether additional narrowing can
be applied based on knowledge of the pre-narrowed type.
The following code sample demonstrates both of these limitations.
.. code-block:: python
def is_iterable(val: object) -> TypeGuard[Iterable[Any]]:
return isinstance(val, Iterable)
def func(val: int | list[int]):
if is_iterable(val):
# The type is narrowed to 'Iterable[Any]' as dictated by
# the TypeGuard return type
reveal_type(val) # Iterable[Any]
else:
# The type is not narrowed in the "False" case
reveal_type(val) # int | list[int]
# If "isinstance" is used in place of the user-defined type guard
# function, the results differ because type checkers apply additional
# logic for "isinstance"
if isinstance(val, Iterable):
# Type is narrowed to "list[int]" because this is
# a narrower (more precise) type than "Iterable[Any]"
reveal_type(val) # list[int]
else:
# Type is narrowed to "int" because the logic eliminates
# "list[int]" from the original union
reveal_type(val) # int
:pep:`647` imposed these limitations so it could support use cases where the
return ``TypeGuard`` type was not a subtype of the input type. Refer to
:pep:`647` for examples.
Rationale
=========
There are a number of issues where a stricter ``TypeGuard`` would have
been a solution:
* `Python typing issue - TypeGuard doesn't intersect like isinstance <https://github.com/python/typing/issues/1351>`__
* `Pyright issue - TypeGuard not eliminating possibility on branch <https://github.com/microsoft/pyright/issues/3450>`__
* `Pyright issue - Type narrowing for Literal doesn't work <https://github.com/microsoft/pyright/issues/3466>`__
* `Mypy issue - TypeGuard is incompatible with exhaustive check <https://github.com/python/mypy/issues/15305>`__
* `Mypy issue - Incorrect type narrowing for inspect.isawaitable <https://github.com/python/mypy/issues/15520>`__
* `Typeshed issue - asyncio.iscoroutinefunction is not a TypeGuard <https://github.com/python/typeshed/issues/8009>`__
Specification
=============
The use of a user-defined type guard function involves five types:
* I = ``TypeGuard`` input type
* R = ``TypeGuard`` return type
* A = Type of argument passed to type guard function (pre-narrowed)
* NP = Narrowed type (positive)
* NN = Narrowed type (negative)
.. code-block:: python
def guard(x: I) -> TypeGuard[R]: ...
def func1(val: A):
if guard(val):
reveal_type(val) # NP
else:
reveal_type(val) # NN
This PEP proposes some modifications to :pep:`647` to address the limitations
discussed above. These limitations are safe to eliminate only when a specific
condition is met. In particular, when the output type ``R`` of a user-defined
type guard function is consistent [#isconsistent]_ with the type of its first
input parameter (``I``), type checkers should apply stricter type guard
semantics.
.. code-block:: python
# Stricter type guard semantics are used in this case because
# "Kangaroo | Koala" is consistent with "Animal"
def is_marsupial(val: Animal) -> TypeGuard[Kangaroo | Koala]:
return isinstance(val, Kangaroo | Koala)
# Stricter type guard semantics are not used in this case because
# "list[T]"" is not consistent with "list[T | None]"
def has_no_nones(val: list[T | None]) -> TypeGuard[list[T]]:
return None not in val
When stricter type guard semantics are applied, the application of a
user-defined type guard function changes in two ways.
* Type narrowing is applied in the negative ("else") case.
.. code-block:: python
def is_str(val: str | int) -> TypeGuard[str]:
return isinstance(val, str)
def func(val: str | int):
if not is_str(val):
reveal_type(val) # int
* Additional type narrowing is applied in the positive "if" case if applicable.
.. code-block:: python
def is_cardinal_direction(val: str) -> TypeGuard[Literal["N", "S", "E", "W"]]:
return val in ("N", "S", "E", "W")
def func(direction: Literal["NW", "E"]):
if is_cardinal_direction(direction):
reveal_type(direction) # "Literal[E]"
else:
reveal_type(direction) # "Literal[NW]"
The type-theoretic rules for type narrowing are specificed in the following
table.
============ ======================= ===================
\ Non-strict type guard Strict type guard
============ ======================= ===================
Applies when R not consistent with I R consistent with I
NP is .. :math:`R` :math:`A \land R`
NN is .. :math:`A` :math:`A \land \neg{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 "isinstance". This guidance allows for changes and
improvements if the type system is extended in the future.
Additional Examples
===================
``Any`` is consistent [#isconsistent]_ with any other type, which means
stricter semantics can be applied.
.. code-block:: python
# Stricter type guard semantics are used in this case because
# "str" is consistent with "Any"
def is_str(x: Any) -> TypeGuard[str]:
return isinstance(x, str)
def test(x: float | str):
if is_str(x):
reveal_type(x) # str
else:
reveal_type(x) # float
Backwards Compatibility
=======================
This PEP proposes to change the existing behavior of ``TypeGuard``. This has no
effect at runtime, but it does change the types evaluated by a type checker.
.. code-block:: python
def is_int(val: int | str) -> TypeGuard[int]:
return isinstance(val, int)
def func(val: int | str):
if is_int(val):
reveal_type(val) # "int"
else:
reveal_type(val) # Previously "int | str", now "str"
This behavioral change results in different types evaluated by a type checker.
It could therefore produce new (or mask existing) type errors.
Type checkers often improve narrowing logic or fix existing bugs in such logic,
so users of static typing will be used to this type of behavioral change.
We also hypothesize that it is unlikely that existing typed Python code relies
on the current behavior of ``TypeGuard``. To validate our hypothesis, we
implemented the proposed change in pyright and ran this modified version on
roughly 25 typed code bases using `mypy primer`__ to see if there were any
differences in the output. As predicted, the behavioral change had minimal
impact. The only noteworthy change was that some ``# type: ignore`` comments
were no longer necessary, indicating that these code bases were already working
around the existing limitations of ``TypeGuard``.
__ https://github.com/hauntsaninja/mypy_primer
Breaking change
---------------
It is possible for a user-defined type guard function to rely on the old
behavior. Such type guard functions could break with the new behavior.
.. code-block:: python
def is_positive_int(val: int | str) -> TypeGuard[int]:
return isinstance(val, int) and val > 0
def func(val: int | str):
if is_positive_int(val):
reveal_type(val) # "int"
else:
# With the older behavior, the type of "val" is evaluated as
# "int | str"; with the new behavior, the type is narrowed to
# "str", which is perhaps not what was intended.
reveal_type(val)
We think it is unlikley that such user-defined type guards exist in real-world
code. The mypy primer results didn't uncover any such cases.
How to Teach This
=================
Users unfamiliar with ``TypeGuard`` are likely to expect the behavior outlined
in this PEP, therefore making ``TypeGuard`` easier to teach and explain.
Reference Implementation
========================
A reference `implementation`__ of this idea exists in pyright.
__ https://github.com/microsoft/pyright/commit/9a5af798d726bd0612cebee7223676c39cf0b9b0
To enable the modified behavior, the configuration flag
``enableExperimentalFeatures`` must be set to true. This can be done on a
per-file basis by adding a comment:
.. code-block:: python
# pyright: enableExperimentalFeatures=true
Rejected Ideas
==============
StrictTypeGuard
---------------
A new ``StrictTypeGuard`` construct was proposed. This alternative form would
be similar to a ``TypeGuard`` except it would apply stricter type guard
semantics. It would also enforce that the return type was consistent
[#isconsistent]_ with the input type. See this thread for details:
`StrictTypeGuard proposal`__
__ https://github.com/python/typing/discussions/1013#discussioncomment-1966238
This idea was rejected because it is unnecessary in most cases and added
unnecessary complexity. It would require the introduction of a new special
form, and developers would need to be educated about the subtle difference
between the two forms.
TypeGuard with a second output type
-----------------------------------
Another idea was proposed where ``TypeGuard`` could support a second optional
type argument that indicates the type that should be used for narrowing in the
negative ("else") case.
.. code-block:: python
def is_int(val: int | str) -> TypeGuard[int, str]:
return isinstance(val, int)
This idea was proposed `here`__.
__ https://github.com/python/typing/issues/996
It was rejected because it was considered too complicated and addressed only
one of the two main limitations of ``TypeGuard``. Refer to this `thread`__ for
the full discussion.
__ https://mail.python.org/archives/list/typing-sig@python.org/thread/EMUD2D424OI53DCWQ4H5L6SJD2IXBHUL
Footnotes
=========
.. [#isconsistent] :pep:`PEP 483's discussion of is-consistent <483#summary-of-gradual-typing>`
Copyright
=========
This document is placed in the public domain or under the
CC0-1.0-Universal license, whichever is more permissive.
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