python type_error ai_generated true

pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for <class 'numpy.ndarray'>. Set `arbitrary_types_allowed=True` in the model_config to ignore this error or implement `__get_pydantic_core_schema__` on your type to fully support it.

ID: python/pydantic-arbitrary-type-not-allowed

Also available as: JSON · Markdown · 中文
80%Fix Rate
89%Confidence
0Evidence
2024-07-14First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2.x active — — —

Root Cause

A field uses a third-party class that Pydantic does not know how to validate. Pydantic v2 requires either arbitrary_types_allowed or a custom core schema for unknown types.

generic

中文

字段使用了 Pydantic 无法验证的第三方类。Pydantic v2 对未知类型要求设置 arbitrary_types_allowed 或自定义核心模式。

Workarounds

  1. 90% success 
    from pydantic import BaseModel, ConfigDict
import numpy as np

class Model(BaseModel):
    model_config = ConfigDict(arbitrary_types_allowed=True)
    arr: np.ndarray
  2. 88% success 
    from pydantic import field_serializer

class Model(BaseModel):
    arr: np.ndarray

    @field_serializer('arr')
    def ser(self, v):
        return v.tolist()

Dead Ends

Common approaches that don't work:

  1. 85% fail

    Pydantic still cannot build a schema for it; the error reappears at class definition or import time.

  2. 60% fail

    Disables all validation and serialization for that field, losing type safety and JSON output.