Pydantic Internal Pydantic code issuing warnings (Fix)

The Fix

pip install pydantic==1.10.19

Based on closed pydantic/pydantic issue #10497 · 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

@@ -1,4 +1,9 @@
@@ -1,4 +1,9 @@
+import warnings
+
+import pytest

repro.py

import pydantic, pydantic.v1, warnings

class Foo(pydantic.BaseModel):
  bar: str

foo = Foo(bar="txt")

warnings.simplefilter("error")
isinstance(foo, pydantic.v1.BaseModel)

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==1.10.19\nWhen NOT to use: This fix is not suitable for applications that require strict adherence to warning suppression.\n\n

Why This Fix Works in Production

Trigger: isinstance(foo, pydantic.v1.BaseModel)
Mechanism: The isinstance check in Pydantic v1 raises a deprecation warning when checking instances of v2 models
Why the fix works: Adds a test for the deprecation warning in the V1 isinstance check, addressing the issue where Pydantic's v1 ModelMetaclass raises a DeprecationWarning when checking instances of v2 models. (first fixed release: 1.10.19).

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 3.9 in real deployments (not just unit tests).
The isinstance check in Pydantic v1 raises a deprecation warning when checking instances of v2 models
Surfaces as: Traceback (most recent call last):

Proof / Evidence

GitHub issue: #10497
Fix PR: https://github.com/pydantic/pydantic/pull/10642
First fixed release: 1.10.19
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.85
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.62

Discussion

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

Jump to Sources Open on GitHub

“Yep, we can definitely fix this. Would you be willing to submit a PR with a fix? Thanks for catching this!”

@sydney-runkle · 2024-09-27 · source

“Which of the three options for fixing it would you suggest I try?”

@alicederyn · 2024-09-27 · source

“> One option would be to wrap this hasattr call in a catch_warnings block and ignore this warning. Let's do this, and catch the deprecation…”

@sydney-runkle · 2024-09-27 · source

“The only downside is, I'm not sure how expensive that is, and I think the point of this callsite was to be fast.”

@alicederyn · 2024-09-27 · source

Failure Signature (Search String)

isinstance(foo, pydantic.v1.BaseModel)

Error Message

Stack trace

error.txt

Error Message
-------------
Traceback (most recent call last):
  File "example.py", line 9, in <module>
    isinstance(foo, pydantic.v1.BaseModel)
  File "pydantic/v1/main.py", line 304, in __instancecheck__
    return hasattr(instance, '__fields__') and super().__instancecheck__(instance)
  File "pydantic/main.py", line 1090, in __fields__
    warnings.warn(
pydantic.warnings.PydanticDeprecatedSince20: The `__fields__` attribute is deprecated, use `model_fields` instead. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.10/migration/

Minimal Reproduction

repro.py

import pydantic, pydantic.v1, warnings

class Foo(pydantic.BaseModel):
  bar: str

foo = Foo(bar="txt")

warnings.simplefilter("error")
isinstance(foo, pydantic.v1.BaseModel)

Environment

Python: 3.9
Pydantic: 2

What Broke

Users encounter deprecation warnings during instance checks, disrupting test runs.

Why It Broke

The isinstance check in Pydantic v1 raises a deprecation warning when checking instances of v2 models

Fix Options (Details)

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

pip install pydantic==1.10.19

When NOT to use: This fix is not suitable for applications that require strict adherence to warning suppression.

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/10642

First fixed release: 1.10.19

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

When NOT to Use This Fix

This fix is not suitable for applications that require strict adherence to warning suppression.

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
1.10.19	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.