The Fix
pip install pydantic==2.12.0
Based on closed pydantic/pydantic issue #11136 · 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%.
@@ -62,7 +62,12 @@
from ..json_schema import JsonSchemaValue
from ..version import version_short
-from ..warnings import ArbitraryTypeWarning, PydanticDeprecatedSince20, UnsupportedFieldAttributeWarning
+from ..warnings import (
+ ArbitraryTypeWarning,
repro.py
from pydantic import BaseModel,, TypeAdapter
from typing_extensions import TypedDict
class Test(TypedDict, closed=False):
name: str
a: Test = {"name": "John Doe", "extra": "something"}
print(a) # {"name": "John Doe", "extra": "something"}
class PydanticTest(BaseModel):
a: Test
b = PydanticTest.model_validate({"a": a})
print(b) # a={"name": "John Doe"}
print(b.model_dump()) # {"a": {"name": "John Doe"}}
c = TypeAdapter(Test).validate_python(a)
print(c) # {"name": "John Doe"}
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 you require strict adherence to TypedDict's closed behavior without exceptions.\n\n
Why This Fix Works in Production
- Trigger: To be expected I guess, pydantic does validation and drops the extra key, since the `closed` keyword is not checked for. However, this is unexpected:
- Mechanism: The behavior of TypedDict with the closed attribute was not consistent between BaseModel and TypeAdapter
- Why the fix works: Adds support for PEP 728, addressing the behavior of TypedDict with the closed attribute and ensuring consistency between BaseModel and TypeAdapter. (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
- The behavior of TypedDict with the closed attribute was not consistent between BaseModel and TypeAdapter
- Production symptom (often without a traceback): To be expected I guess, pydantic does validation and drops the extra key, since the `closed` keyword is not checked for. However, this is unexpected:
Proof / Evidence
- GitHub issue: #11136
- Fix PR: https://github.com/pydantic/pydantic/pull/12179
- 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: 0.60
Discussion
High-signal excerpts from the issue thread (symptoms, repros, edge-cases).
“Related: https://github.com/pydantic/pydantic/issues/10785. We'll wait for https://peps.python.org/pep-0728/ to be accepted first, and then we'll sort out these issues.”
“But indeed, we do want to support this in the future. Thanks for the detailed feature request :)”
“> If Test were a BaseModel, the config of extra="allow" would not propagate down to the members”
Failure Signature (Search String)
- To be expected I guess, pydantic does validation and drops the extra key, since the `closed` keyword is not checked for. However, this is unexpected:
- - [ ] [Compatibility between releases](https://docs.pydantic.dev/changelog/)
Copy-friendly signature
signature.txt
Failure Signature
-----------------
To be expected I guess, pydantic does validation and drops the extra key, since the `closed` keyword is not checked for. However, this is unexpected:
- [ ] [Compatibility between releases](https://docs.pydantic.dev/changelog/)
Error Message
Signature-only (no traceback captured)
error.txt
Error Message
-------------
To be expected I guess, pydantic does validation and drops the extra key, since the `closed` keyword is not checked for. However, this is unexpected:
- [ ] [Compatibility between releases](https://docs.pydantic.dev/changelog/)
Minimal Reproduction
repro.py
from pydantic import BaseModel,, TypeAdapter
from typing_extensions import TypedDict
class Test(TypedDict, closed=False):
name: str
a: Test = {"name": "John Doe", "extra": "something"}
print(a) # {"name": "John Doe", "extra": "something"}
class PydanticTest(BaseModel):
a: Test
b = PydanticTest.model_validate({"a": a})
print(b) # a={"name": "John Doe"}
print(b.model_dump()) # {"a": {"name": "John Doe"}}
c = TypeAdapter(Test).validate_python(a)
print(c) # {"name": "John Doe"}
What Broke
Inconsistent validation and serialization behavior when using TypedDict with extra keys.
Why It Broke
The behavior of TypedDict with the closed attribute was not consistent between BaseModel and TypeAdapter
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 you require strict adherence to TypedDict's closed behavior without exceptions.
Use when you can deploy the upstream fix. It is usually lower-risk than long-lived workarounds.
Option D — Guard side-effects with OnceOnly Guardrail for side-effects
Mitigate duplicate external side-effects under retries/timeouts/agent loops by gating the operation before calling external systems.
- Place OnceOnly between your code/agent and real side-effects (Stripe, emails, CRM, APIs).
- Use a stable key per side-effect (e.g., customer_id + action + idempotency_key).
- Fail-safe: configure fail-open vs fail-closed based on blast radius and spend risk.
Show example snippet (optional)
onceonly.py
from onceonly import OnceOnly
import os
once = OnceOnly(api_key=os.environ["ONCEONLY_API_KEY"], fail_open=True)
# Stable idempotency key per real side-effect.
# Use a request id / job id / webhook delivery id / Stripe event id, etc.
event_id = "evt_..." # replace
key = f"stripe:webhook:{event_id}"
res = once.check_lock(key=key, ttl=3600)
if res.duplicate:
return {"status": "already_processed"}
# Safe to execute the side-effect exactly once.
handle_event(event_id)
When NOT to use: Do not use this to hide logic bugs or data corruption. Use it to block duplicate external side-effects and enforce tool permissions/spend caps.
Fix reference: https://github.com/pydantic/pydantic/pull/12179
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 you require strict adherence to TypedDict's closed behavior without exceptions.
- Do not use this to hide logic bugs or data corruption. Use it to block duplicate external side-effects and enforce tool permissions/spend caps.
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.
Sources
We don’t republish the full GitHub discussion text. Use the links above for context.