python data_error ai_generated true

pydantic.errors.PydanticInvalidForJsonSchema: Cannot generate a JsonSchema for core_schema.IsInstanceSchema (<class 'decimal.Decimal'>)

ID: python/pydantic-json-schema-generation-error

Also available as: JSON · Markdown · 中文
80%Fix Rate
86%Confidence
0Evidence
2024-06-21First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2.x active — — —

Root Cause

A field uses an arbitrary Python type (via arbitrary_types_allowed or a custom class) that has no defined JSON Schema representation, so model_json_schema() fails.

generic

中文

字段使用了没有定义 JSON Schema 表示的任意 Python 类型（通过 arbitrary_types_allowed 或自定义类），导致 model_json_schema() 失败。

Workarounds

  1. 90% success 
    from typing import Annotated
from pydantic import BaseModel, WithJsonSchema

class Model(BaseModel):
    amount: Annotated[Decimal, WithJsonSchema({'type': 'string', 'format': 'decimal'})]
  2. 88% success 
    class Model(BaseModel):
    amount: float  # or str; convert to Decimal in business logic

Dead Ends

Common approaches that don't work:

  1. 70% fail

    Returns an empty schema, breaking OpenAPI docs and client generation downstream.

  2. 80% fail

    This allows the type at validation time but does not teach Pydantic how to serialize it to JSON Schema.