Abstract

This PEP proposes a mechanism for type checking metadata that uses the typing.Annotated type. Metadata objects that implement the new __supports_annotated_base__ 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 pydantic and msgspec, which use Annotated to attach validation and conversion information to fields or fastapi, which uses Annotated to mark parameters as extracted from headers, query strings or dependency injection.

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 an attribute called __supports_annotated_base__ that specifies whether the metadata is valid for a given type:

class Int64:
    __supports_annotated_base__: int

The attribute may also be marked as a ClassVar to avoid interaction with dataclasses:

from dataclasses import dataclass
from typing import ClassVar

@dataclass
class Gt:
    value: int
    __supports_annotated_base__: ClassVar[int]

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_annotated_base__ attribute; or
• The metadata element evaluates to an object M that has a __supports_annotated_base__ attribute; and T is assignable to the type of M.__supports_annotated_base__.

To support generic Gt metadata, one might write:

from typing import Protocol

class SupportsGt[T](Protocol):
    def __gt__(self, __other: T) -> bool:
        ...

class Gt[T]:
    __supports_annotated_base__: ClassVar[SupportsGt[T]]

    def __init__(self, value: T) -> None:
        self.value = 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

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 typing.Annotated and in the typing specification.

Reference Implementation

None yet.

Rejected ideas

Acknowledgments

We thank Eric Traut for suggesting the idea of using a protocol and implementing provisional support in Pyright. Thank you to Jelle Zijlstra for sponsoring this PEP.

Copyright

This document has been placed in the public domain.