python type_error ai_generated true

pydantic_core._pydantic_core.ValidationError: 1 validation error for Settings debug Input should be a valid boolean, unable to interpret input [type=bool_parsing, input_value='yes', input_type=str]

ID: python/pydantic-validation-error-bool-parsing

Also available as: JSON · Markdown · 中文
80%Fix Rate
86%Confidence
0Evidence
2024-07-15First Seen

Version Compatibility

VersionStatusIntroducedDeprecatedNotes
2.x active — — —

Root Cause

Pydantic v2 only accepts a limited set of boolean-like strings ('true','false','1','0','yes','no','on','off' are case-sensitive to specific forms). 'yes' is not accepted by default.

generic

中文

Pydantic v2 只接受有限形式的布尔字符串（'true'、'false'、'1'、'0'、'yes'、'no'、'on'、'off'，且对大小写敏感）。默认不接受 'yes'。

Workarounds

  1. 93% success 
    from pydantic import BaseModel, field_validator

class Settings(BaseModel):
    debug: bool

    @field_validator('debug', mode='before')
    @classmethod
    def parse_bool(cls, v):
        if isinstance(v, str):
            return v.lower() in ('yes','true','1','on')
        return v
  2. 90% success 
    data['debug'] = str(data['debug']).lower() in ('true','1','yes')

Dead Ends

Common approaches that don't work:

  1. 95% fail

    bool('yes') returns True but bool('false') also returns True because any non-empty string is truthy.

  2. 99% fail

    int('yes') raises ValueError immediately.