Pydantic BeforeValidator `func` called twice when input

The Fix

pip install pydantic==2.10.6

Based on closed pydantic/pydantic issue #11133 · PR/commit linked

Production note: This usually shows up under retries/timeouts. Treat it as a side-effect risk until you can verify behavior with a canary + real traffic.

Jump to Verify Open PR/Commit

@@ -64,12 +64,11 @@ def __init__(self, metadata: Any):
 
 
-def _update_fields_from_docstrings(cls: type[Any], fields: dict[str, FieldInfo], config_wrapper: ConfigWrapper) -> None:
-    if config_wrapper.use_attribute_docstrings:
-        fields_docs = extract_docstrings_from_cls(cls)

repro.py

# coding: utf-8

import json
import typing as t

from pydantic import ConfigDict, Field, BeforeValidator, BaseModel
from pydantic.dataclasses import dataclass


def _json_to_dict(data: str) -> dict:

    print("_json_to_dict", type(data), data)
    if not data:
        return {}
    # fixme: avoid exception
    if isinstance(data, dict):
        return data
    return json.loads(data)


def _to_str(data: t.Any) -> str:

    print("_to_str", type(data), data)
    if isinstance(data, str):
        return data
    if not data:
        return ""
    return str(data)


_CONFIG = ConfigDict(
    extra="allow",
    validate_assignment=True,
    arbitrary_types_allowed=True,
    coerce_numbers_to_str=True)


@dataclass(config=_CONFIG)
class B:

    a: t.Annotated[str, BeforeValidator(_to_str)] = "4"


@dataclass(config=_CONFIG)
class A:

    b: t.Annotated[B, BeforeValidator(_json_to_dict)] = Field(default_factory=B)


class AA(BaseModel):

    b: t.Annotated[B, BeforeValidator(_json_to_dict)] = Field(default_factory=B)


if __name__ == '__main__':

    data = {"b": json.dumps({"a": None, "b": 200})}
    a = A(**data)  # _json_to_dict <class 'str'> {"a": null, "b": 200}
                   # _json_to_dict <class 'dict'> {'a': None, 'b': 200}
    print(a)
    aa = AA(**data)  # _json_to_dict <class 'str'> {"a": null, "b": 200}
    print(aa)

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==2.10.6\nWhen NOT to use: This fix should not be applied if the application relies on the original behavior of BeforeValidator.\n\n

Why This Fix Works in Production

Trigger: I added a conditional `if isinstance(data, dict): return data` to avoid exception. Or it report excpetion `TypeError: the JSON object must be str, bytes or…
Mechanism: Fixed an issue where the BeforeValidator `func` was called twice when the input field value was a JSON object in `pydantic.dataclass`.
Why the fix works: Fixed an issue where the BeforeValidator `func` was called twice when the input field value was a JSON object in `pydantic.dataclass`. (first fixed release: 2.10.6).

Production impact:

If left unfixed, retries/timeouts can trigger duplicate external side-effects (double charges, duplicate emails, repeated writes).

Why This Breaks in Prod

Shows up under Python 3.9 in real deployments (not just unit tests).
Production symptom (often without a traceback): I added a conditional `if isinstance(data, dict): return data` to avoid exception. Or it report excpetion `TypeError: the JSON object must be str, bytes or bytearray, not dict`.

Proof / Evidence

GitHub issue: #11133
Fix PR: https://github.com/pydantic/pydantic/pull/11246
First fixed release: 2.10.6
Reproduced locally: No (not executed)
Last verified: 2026-02-09
Confidence: 0.95
Did this fix it?: Yes (upstream fix exists)
Own content ratio: 0.41

Discussion

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

Jump to Sources Open on GitHub

“Sorry for the delay, bisected and this was fixed by https://github.com/pydantic/pydantic/pull/11246, which is available in 2.11.”

@Viicos · 2025-04-11 · source

Failure Signature (Search String)

I added a conditional `if isinstance(data, dict): return data` to avoid exception. Or it report excpetion `TypeError: the JSON object must be str, bytes or bytearray, not dict`.

Copy-friendly signature

signature.txt

Failure Signature
-----------------
I added a conditional `if isinstance(data, dict): return data` to avoid exception. Or it report excpetion `TypeError: the JSON object must be str, bytes or bytearray, not dict`.

Error Message

Signature-only (no traceback captured)

error.txt

Error Message
-------------
I added a conditional `if isinstance(data, dict): return data` to avoid exception. Or it report excpetion `TypeError: the JSON object must be str, bytes or bytearray, not dict`.

Minimal Reproduction

repro.py

# coding: utf-8

import json
import typing as t

from pydantic import ConfigDict, Field, BeforeValidator, BaseModel
from pydantic.dataclasses import dataclass


def _json_to_dict(data: str) -> dict:

    print("_json_to_dict", type(data), data)
    if not data:
        return {}
    # fixme: avoid exception
    if isinstance(data, dict):
        return data
    return json.loads(data)


def _to_str(data: t.Any) -> str:

    print("_to_str", type(data), data)
    if isinstance(data, str):
        return data
    if not data:
        return ""
    return str(data)


_CONFIG = ConfigDict(
    extra="allow",
    validate_assignment=True,
    arbitrary_types_allowed=True,
    coerce_numbers_to_str=True)


@dataclass(config=_CONFIG)
class B:

    a: t.Annotated[str, BeforeValidator(_to_str)] = "4"


@dataclass(config=_CONFIG)
class A:

    b: t.Annotated[B, BeforeValidator(_json_to_dict)] = Field(default_factory=B)


class AA(BaseModel):

    b: t.Annotated[B, BeforeValidator(_json_to_dict)] = Field(default_factory=B)


if __name__ == '__main__':

    data = {"b": json.dumps({"a": None, "b": 200})}
    a = A(**data)  # _json_to_dict <class 'str'> {"a": null, "b": 200}
                   # _json_to_dict <class 'dict'> {'a': None, 'b': 200}
    print(a)
    aa = AA(**data)  # _json_to_dict <class 'str'> {"a": null, "b": 200}
    print(aa)

Environment

Python: 3.9
Pydantic: 2

What Broke

Users experienced TypeError exceptions when initializing dataclasses with JSON string inputs.

Fix Options (Details)

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

pip install pydantic==2.10.6

When NOT to use: This fix should not be applied if the application relies on the original behavior of BeforeValidator.

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/11246

First fixed release: 2.10.6

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

When NOT to Use This Fix

This fix should not be applied if the application relies on the original behavior of BeforeValidator.

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
2.10.6	Fixed

Related Issues

No related fixes found.

Cluster: pydantic:duplicate-processing Pydantic hub Pydantic best practices All hubs All clusters

Related clusters: Configuration error Data consistency OpenAPI schema

Sources

We don’t republish the full GitHub discussion text. Use the links above for context.

Pydantic BeforeValidator `func` called twice when input field value is json object in (Fix)