python-peps/peps/pep-0746.rst

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PEP: 746
Title: Type checking Annotated metadata
Author: Adrian Garcia Badaracco <adrian@adriangb.com>
Sponsor: Jelle Zijlstra <jelle.zijlstra@gmail.com>
Discussions-To: https://discuss.python.org/t/pep-746-typedmetadata-for-type-checking-of-pep-593-annotated/53834
Status: Draft
Type: Standards Track
Topic: Typing
Created: 20-May-2024
Python-Version: 3.14
Post-History: 20-May-2024
Abstract
========
This PEP proposes a mechanism for type checking metadata that uses
the :py:data:`typing.Annotated` type. Metadata objects that implement
the new ``__supports_type__`` protocol will be type checked by static
type checkers to ensure that the metadata is valid for the given type.
Motivation
==========
:pep:`593` introduced ``Annotated`` as a way to attach runtime metadata to types.
In general, the metadata is not meant for static type checkers, but even so,
it is often useful to be able to check that the metadata makes sense for the given
type.
Take the first example in :pep:`593`, which uses ``Annotated`` to attach
serialization information to a field::
class Student(struct2.Packed):
name: Annotated[str, struct2.ctype("<10s")]
Here, the ``struct2.ctype("<10s")`` metadata is meant to be used by a serialization
library to serialize the field. Such libraries can only serialize a subset of types:
it would not make sense to write, for example, ``Annotated[list[str], struct2.ctype("<10s")]``.
Yet the type system provides no way to enforce this. The metadata are completely
ignored by type checkers.
This use case comes up in libraries like :pypi:`pydantic`, which use
``Annotated`` to attach validation and conversion information to fields.
Specification
=============
This PEP introduces a protocol that can be used by static and runtime type checkers to validate
the consistency between ``Annotated`` metadata and a given type.
Objects that implement this protocol have a method named ``__supports_type__``
that takes a single positional argument and returns ``bool``::
class Int64:
def __supports_type__(self, obj: int) -> bool:
return isinstance(obj, int)
The protocol being introduced would be defined as follows if it were to be defined in code form::
from typing import Protocol
class SupportsType[T](Protocol):
def __supports_type__(self, obj: T, /) -> bool:
...
When a static type checker encounters a type expression of the form ``Annotated[T, M1, M2, ...]``,
it should enforce that for each metadata element in ``M1, M2, ...``, one of the following is true:
* The metadata element evaluates to an object that does not have a ``__supports_type__`` attribute; or
* The metadata element evaluates to an object ``M`` that implements the ``SupportsType`` protocol;
and, with ``T`` instantiated to a value ``v``, a call to ``M.__supports_type__(v)`` type checks without errors;
and that call does not evaluate to ``Literal[False]``.
The body of the ``__supports_type__`` method is not used to check the validity of the metadata
and static type checkers can ignore it. However, tools that use the annotation at
runtime may call the method to check that a particular value is valid.
For example, to support a generic ``Gt`` metadata, one might write::
from typing import Protocol
class SupportsGt[T](Protocol):
def __gt__(self, __other: T) -> bool:
...
class Gt[T]:
def __init__(self, value: T) -> None:
self.value = value
def __supports_type__(self, obj: SupportsGt[T], /) -> bool:
return obj > self.value
x1: Annotated[int, Gt(0)] = 1 # OK
x2: Annotated[str, Gt(0)] = 0 # type checker error: str is not assignable to SupportsGt[int]
x3: Annotated[int, Gt(1)] = 0 # OK for static type checkers; runtime type checkers may flag this
Implementations may be generic and may use overloads that return ``Literal[True]`` or ``Literal[False]``
to indicate if the metadata is valid for the given type.
Implementations may raise a NotImplementedError if they cannot determine if the metadata is valid for the given type.
Tools calling ``__supports_type__`` at runtime should catch this exception and treat it as if ``__supports_type__``
was not present; they should not take this as an indication that the metadata is invalid for the type.
Tools that use the metadata at runtime may choose to ignore the implementation of ``__supports_type__``; this PEP does not
specify how the method should be used at runtime, only that it may be available for use.
Backwards Compatibility
=======================
Metadata that does not implement the protocol will be considered valid for all types,
so no breaking changes are introduced for existing code. The new checks only apply
to metadata objects that explicitly implement the protocol specified by this PEP.
Security Implications
=====================
None.
How to Teach This
=================
This protocol is intended mostly for libraries that provide ``Annotated`` metadata;
end users of those libraries are unlikely to need to implement the protocol themselves.
The protocol should be mentioned in the documentation for :py:data:`typing.Annotated` and
in the typing specification.
Reference Implementation
========================
None yet.
Rejected ideas
==============
Introducing a type variable instead of a generic class
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
We considered using a special type variable, ``AnnotatedT = TypeVar("AnnotatedT")``,
to represent the type ``T`` of the inner type in ``Annotated``; metadata would be
type checked against this type variable. However, this would require using the old
type variable syntax (before :pep:`695`), which is now a discouraged feature.
In addition, this would use type variables in an unusual way that does not fit well
with the rest of the type system.
Introducing a new type to ``typing.py`` that all metadata objects should subclass
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A previous version of this PEP suggested adding a new generic base class, ``TypedMetadata[U]``,
that metadata objects would subclass. If a metadata object is a subclass of ``TypedMetadata[U]``,
then type checkers would check that the annotation's base type is assignable to ``U``.
However, this mechanism does not integrate as well with the rest of the language; Python
does not generally use marker base classes. In addition, it provides less flexibility than
the current proposal: it would not allow overloads, and it would require metadata objects
to add a new base class, which may make their runtime implementation more complex.
Acknowledgments
===============
We thank Eric Traut for suggesting the idea of using a protocol.
Copyright
=========
This document has been placed in the public domain.