Pydantic 2.12.0: FieldInfo.annotation is not a type (Fix)

The Fix

pip install pydantic==2.12.0

Based on closed pydantic/pydantic issue #12349 · PR/commit linked

Production note: Most teams hit this during upgrades or environment changes. Roll out with a canary and smoke critical endpoints (health, OpenAPI/docs) before 100%.

Jump to Verify Open PR/Commit

@@ -10,7 +10,7 @@
 from functools import cache, partial, wraps
 from types import FunctionType
-from typing import TYPE_CHECKING, Any, Callable, Generic, Literal, NoReturn, cast
+from typing import TYPE_CHECKING, Any, Callable, Generic, Literal, NoReturn, TypeVar, cast

repro.py

import pydantic

class T(pydantic.BaseModel):
    a : str | None


print(T.model_fields["a"].annotation)  # str | None
print(type(T.model_fields["a"].annotation))  # <class 'types.UnionType'>
print(issubclass(T.model_fields["a"].annotation, T))  # False

verify

Re-run: uv run --python 3.13 --with pydantic==2.12 foo.py

fix.md

Option A — Upgrade to fixed release\npip install pydantic==2.12.0\nWhen NOT to use: This fix is not applicable if the behavior of issubclass checks is intentionally required to fail.\n\n

Why This Fix Works in Production

Trigger: str | None
Mechanism: The custom __subclasscheck__ implementation in Pydantic models caused TypeError in issubclass checks
Why the fix works: Addresses the issue with the custom __subclasscheck__ implementation in Pydantic models, which caused TypeError in issubclass checks. (first fixed release: 2.12.0).

Production impact:

If left unfixed, the same config can fail only in production (env differences), causing startup failures or partial feature outages.

Why This Breaks in Prod

Shows up under Python 3.13 in real deployments (not just unit tests).
The custom __subclasscheck__ implementation in Pydantic models caused TypeError in issubclass checks
Surfaces as: str | None

Proof / Evidence

GitHub issue: #12349
Fix PR: https://github.com/pydantic/pydantic/pull/11669
First fixed release: 2.12.0
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.95
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.47

Discussion

High-signal excerpts from the issue thread (symptoms, repros, edge-cases).

Jump to Sources Open on GitHub

“You usually want to check if isinstance(obj, type) (or the equivalent inspect.isclass())”

@Viicos · 2025-10-08 · repro detail · source

“The issue reproduces on older Pydantic versions as well (and in general, is expected to fail: issubclass(str | None, <some_type>) isn't valid).”

@Viicos · 2025-10-07 · source

“Hi @Viicos, thanks for the quick reply”

@edvgui · 2025-10-07 · source

“The issue does not reproduce for me on 2.11 as written: vs So I figure something did change in the __instancecheck__, but this is probably…”

@bijlpieter · 2025-10-08 · source

Failure Signature (Search String)

str | None

Error Message

Stack trace

error.txt

Error Message
-------------
str | None
<class 'types.UnionType'>
Traceback (most recent call last):
  File "/home/guillaume/Documents/inmanta-module-git-ops/bug.py", line 9, in <module>
    print(issubclass(T.model_fields["a"].annotation, T))  # False
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: issubclass() arg 1 must be a class

Stack trace

error.txt

Error Message
-------------
$ uv run --python 3.13 --with pydantic==2.12 foo.py
str | None
<class 'types.UnionType'>
Traceback (most recent call last):
  File "/home/pieter/foo.py", line 10, in <module>
    print(issubclass(T.model_fields["a"].annotation, T))  # False
          ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: issubclass() arg 1 must be a class

Minimal Reproduction

repro.py

import pydantic

class T(pydantic.BaseModel):
    a : str | None


print(T.model_fields["a"].annotation)  # str | None
print(type(T.model_fields["a"].annotation))  # <class 'types.UnionType'>
print(issubclass(T.model_fields["a"].annotation, T))  # False

Environment

Python: 3.13
Pydantic: 2

Why It Broke

The custom __subclasscheck__ implementation in Pydantic models caused TypeError in issubclass checks

Fix Options (Details)

Option A — Upgrade to fixed release Safe default (recommended)

pip install pydantic==2.12.0

When NOT to use: This fix is not applicable if the behavior of issubclass checks is intentionally required to fail.

Use when you can deploy the upstream fix. It is usually lower-risk than long-lived workarounds.

Fix reference: https://github.com/pydantic/pydantic/pull/11669

First fixed release: 2.12.0

Last verified: 2026-02-09. Validate in your environment.

When NOT to Use This Fix

This fix is not applicable if the behavior of issubclass checks is intentionally required to fail.

Verify Fix

verify

Re-run: uv run --python 3.13 --with pydantic==2.12 foo.py

Did This Fix Work in Your Case?

Quick signal helps us prioritize which fixes to verify and improve.

Prevention

Add a CI check that diffs key outputs after upgrades (OpenAPI schema snapshots, JSON payload shapes, CLI output).
Upgrade behind a canary and run integration tests against the canary before 100% rollout.

Version Compatibility Table

Version	Status
2.12.0	Fixed

Related Issues

No related fixes found.

Cluster: pydantic:configuration-error Pydantic hub Pydantic best practices All hubs All clusters

Related clusters: Data consistency OpenAPI schema Serialization

Sources

We don’t republish the full GitHub discussion text. Use the links above for context.