Pydantic validate_call makes an unexpected conversion (Fix)

The Fix

pip install pydantic==1.10.15

Based on closed pydantic/pydantic issue #8930 · 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

@@ -274,7 +274,7 @@ class SequenceValidator:
     min_length: int | None = None
     max_length: int | None = None
-    strict: bool = False
+    strict: bool | None = None

repro.py

>> from collections.abc import Set
>> from pydantic import ConfigDict, validate_call
>>
>> @validate_call(config=ConfigDict(strict=True, arbitrary_types_allowed=True),)
... def my_test(a_set: Set[str],):
...     print(type(a_set), a_set)
...
>> my_test({"1","2","3",})
<class 'frozenset'> frozenset({'1', '2', '3'})
>> my_test(("1","2","3",))
<class 'frozenset'> frozenset({'1', '2', '3'})
>>

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==1.10.15\nWhen NOT to use: Do not use this fix if strict validation is not required.\n\n

Why This Fix Works in Production

Trigger: validate_call makes an unexpected conversion
Mechanism: The validate_call function incorrectly converts tuples to frozensets in strict mode
Why the fix works: Fixes the issue where tuples were incorrectly converted to frozensets when strict validation was enabled in Pydantic's validate_call function. (first fixed release: 1.10.15).

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 3.12 in real deployments (not just unit tests).
The validate_call function incorrectly converts tuples to frozensets in strict mode
Production symptom (often without a traceback): validate_call makes an unexpected conversion

Proof / Evidence

GitHub issue: #8930
Fix PR: https://github.com/pydantic/pydantic/pull/8977
First fixed release: 1.10.15
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.85
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.60

Discussion

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

Jump to Sources Open on GitHub

“Ah, this does seem like a bug, but isn't just for validate_call, but also this problem applies to general validation with BaseModel, pydantic dataclasses, etc…”

@sydney-runkle · 2024-03-02 · source

Failure Signature (Search String)

validate_call makes an unexpected conversion
You will notice that the `tuple` got turned into a `frozenset` instead of being rejected as an incompatible input (this is running in `strict=True` mode)

Copy-friendly signature

signature.txt

Failure Signature
-----------------
validate_call makes an unexpected conversion
You will notice that the `tuple` got turned into a `frozenset` instead of being rejected as an incompatible input (this is running in `strict=True` mode)

Error Message

Signature-only (no traceback captured)

error.txt

Error Message
-------------
validate_call makes an unexpected conversion
You will notice that the `tuple` got turned into a `frozenset` instead of being rejected as an incompatible input (this is running in `strict=True` mode)

Minimal Reproduction

repro.py

>> from collections.abc import Set
>> from pydantic import ConfigDict, validate_call
>>
>> @validate_call(config=ConfigDict(strict=True, arbitrary_types_allowed=True),)
... def my_test(a_set: Set[str],):
...     print(type(a_set), a_set)
...
>> my_test({"1","2","3",})
<class 'frozenset'> frozenset({'1', '2', '3'})
>> my_test(("1","2","3",))
<class 'frozenset'> frozenset({'1', '2', '3'})
>>

Environment

Python: 3.12
Pydantic: 2

What Broke

Users experience unexpected type conversions leading to incorrect data handling.

Why It Broke

The validate_call function incorrectly converts tuples to frozensets in strict mode

Fix Options (Details)

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

pip install pydantic==1.10.15

When NOT to use: Do not use this fix if strict validation is not required.

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/8977

First fixed release: 1.10.15

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

When NOT to Use This Fix

Do not use this fix if strict validation is not required.

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
1.10.15	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.