Pydantic Partial function not working in predicate (Fix)

The Fix

pip install pydantic==2.12.0

Based on closed pydantic/pydantic issue #12276 · PR/commit linked

Jump to Verify Open PR/Commit

@@ -182,7 +182,8 @@ def apply_known_metadata(annotation: Any, schema: CoreSchema) -> CoreSchema | No
 
     Raises:
-        PydanticCustomError: If `Predicate` fails.
+        RuntimeError: If a constraint can't be applied to a specific schema type.
+        ValueError: If an unknown constraint is encountered.

repro.py

from pydantic import TypeAdapter, ValidationError
from pydantic.experimental.pipeline import validate_as
from typing import Annotated
from functools import partial

incr1 = partial(lambda x, incr: x == incr, incr=1)
ta_str_to_int = TypeAdapter[int](Annotated[int, validate_as(int).predicate(incr1)])
assert ta_str_to_int.validate_python(1) == 1
try:
    ta_str_to_int.validate_python(2)
except ValidationError:
    print("This is expected since 1 != 2")

verify

Re-run the minimal reproduction on your broken version, then apply the fix and re-run.

fix.md

Option A — Upgrade to fixed release\npip install pydantic==2.12.0\nWhen NOT to use: Do not use this fix if your code relies on lambda functions for predicate validation.\n\n

Why This Fix Works in Production

Trigger: assert ta_str_to_int.validate_python(1) == 1
Mechanism: Fixes an issue with using functools.partial in the pipelines API by not relying on inferring names from lambda definitions.
Why the fix works: Fixes an issue with using functools.partial in the pipelines API by not relying on inferring names from lambda definitions. (first fixed release: 2.12.0).

Why This Breaks in Prod

Production symptom (often without a traceback): from pydantic import TypeAdapter, ValidationError

Proof / Evidence

GitHub issue: #12276
Fix PR: https://github.com/pydantic/pydantic/pull/12289
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: 0.52

Discussion

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

Jump to Sources Open on GitHub

“### Initial Checks - [x] I confirm that I'm using Pydantic V2 ### Description I ran into an issue when using the new pipelines API in combination with functools.partial as predicate. This check can also be done by using a lambda, but since”

Issue thread · issue description · source

Failure Signature (Search String)

assert ta_str_to_int.validate_python(1) == 1

Copy-friendly signature

signature.txt

Failure Signature
-----------------
from pydantic import TypeAdapter, ValidationError
assert ta_str_to_int.validate_python(1) == 1

Error Message

Signature-only (no traceback captured)

error.txt

Error Message
-------------
from pydantic import TypeAdapter, ValidationError
assert ta_str_to_int.validate_python(1) == 1

Minimal Reproduction

repro.py

from pydantic import TypeAdapter, ValidationError
from pydantic.experimental.pipeline import validate_as
from typing import Annotated
from functools import partial

incr1 = partial(lambda x, incr: x == incr, incr=1)
ta_str_to_int = TypeAdapter[int](Annotated[int, validate_as(int).predicate(incr1)])
assert ta_str_to_int.validate_python(1) == 1
try:
    ta_str_to_int.validate_python(2)
except ValidationError:
    print("This is expected since 1 != 2")

Environment

Pydantic: 2

What Broke

Users experienced validation errors when using partial functions as predicates in the pipelines API.

Fix Options (Details)

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

pip install pydantic==2.12.0

When NOT to use: Do not use this fix if your code relies on lambda functions for predicate validation.

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/12289

First fixed release: 2.12.0

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

When NOT to Use This Fix

Do not use this fix if your code relies on lambda functions for predicate validation.

Verify Fix

verify

Re-run the minimal reproduction on your broken version, then apply the fix and re-run.

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:validation-error Pydantic hub Pydantic best practices All hubs All clusters

Related clusters: Configuration error Data consistency OpenAPI schema

Sources

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