python type_error ai_generated true

pydantic_core._pydantic_core.ValidationError: 1 validation error for User age Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='abc', input_type=str]

ID: python/pydantic-validation-error-model-type

Also available as: JSON · Markdown · 中文
80%Fix Rate
88%Confidence
0Evidence
2024-03-12First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2.x active — — —

Root Cause

Pydantic v2 strict-by-default coercion fails when a string like 'abc' is passed to an int field; the type coercion cannot parse non-numeric strings.

generic

中文

Pydantic v2 默认严格模式下，将非数字字符串 'abc' 传入 int 字段时会因无法解析而抛出验证错误。

Workarounds

  1. 92% success 
    from pydantic import BaseModel, field_validator
class User(BaseModel):
    age: int
    @field_validator('age', mode='before')
    @classmethod
    def parse_age(cls, v):
        if isinstance(v, str) and not v.isdigit():
            raise ValueError('age must be numeric')
        return int(v)
  2. 95% success 
    from pydantic import ValidationError
try:
    User(age='abc')
except ValidationError as e:
    return {'errors': e.errors()}, 422

Dead Ends

Common approaches that don't work:

  1. 75% fail

    strict=False still refuses to parse 'abc' into int because no valid numeric representation exists.

  2. 60% fail

    This hides the error but downstream code expecting int will crash with TypeError.