The Fix
pip install pydantic==2.9.2
Based on closed pydantic/pydantic issue #10189 · PR/commit linked
Production note: Watch p95/p99 latency and retry volume; timeouts can turn into retry storms and duplicate side-effects.
@@ -133,6 +133,8 @@ def wrapped_model_post_init(self: BaseModel, context: Any, /) -> None:
namespace['__class_vars__'] = class_vars
namespace['__private_attributes__'] = {**base_private_attributes, **private_attributes}
+ if __pydantic_generic_metadata__:
+ namespace['__pydantic_generic_metadata__'] = __pydantic_generic_metadata__
Option A — Upgrade to fixed release\npip install pydantic==2.9.2\nWhen NOT to use: Do not use this fix if your code relies on the previous MRO behavior.\n\n
Why This Fix Works in Production
- Trigger: - [x] v2.9 blog post to socialize changes + improvements - need to collect some performance stats from users
- Mechanism: The MRO of generic subclasses was not correctly handled in the previous implementation
- Why the fix works: Allows validators to customize the validation JSON schema by introducing a `json_schema_input_type` argument. (first fixed release: 2.9.2).
- If left unfixed, tail latency can spike under load and surface as timeouts/retries (amplifying incident impact).
Why This Breaks in Prod
- The MRO of generic subclasses was not correctly handled in the previous implementation
- Production symptom (often without a traceback): - [x] v2.9 blog post to socialize changes + improvements - need to collect some performance stats from users
Proof / Evidence
- GitHub issue: #10189
- Fix PR: https://github.com/pydantic/pydantic/pull/10100
- First fixed release: 2.9.2
- Reproduced locally: No (not executed)
- Last verified: 2026-02-09
- Confidence: 0.75
- Did this fix it?: Yes (upstream fix exists)
- Own content ratio: 0.68
Discussion
High-signal excerpts from the issue thread (symptoms, repros, edge-cases).
“We've released v2.9.0b1, so I'll be pivoting to the above docs updates re pre beta todos!”
“Update for folks following here - planning on the v2.9 release tomorrow! cc @Viicos :)”
“@Viicos, Feel free to add the issues you'd like to complete that I may have missed to the checklist above”
“> Major update to docs examples page -- add 10 more or so Moving this to later.”
Failure Signature (Search String)
- - [x] v2.9 blog post to socialize changes + improvements - need to collect some performance stats from users
Copy-friendly signature
Failure Signature
-----------------
- [x] v2.9 blog post to socialize changes + improvements - need to collect some performance stats from users
Error Message
Signature-only (no traceback captured)
Error Message
-------------
- [x] v2.9 blog post to socialize changes + improvements - need to collect some performance stats from users
What Broke
Users experienced incorrect behavior when using generic subclasses, leading to validation errors.
Why It Broke
The MRO of generic subclasses was not correctly handled in the previous implementation
Fix Options (Details)
Option A — Upgrade to fixed release Safe default (recommended)
pip install pydantic==2.9.2
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/10100
First fixed release: 2.9.2
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 the previous MRO behavior.
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 |
|---|---|
| 2.9.2 | Fixed |
Related Issues
No related fixes found.
Sources
We don’t republish the full GitHub discussion text. Use the links above for context.