pydantic-basesettings-class-attributes
Use when defining constants or mappings in Pydantic BaseSettings or BaseModel subclasses results in "non-annotated attribute" errors requiring ClassVar annotations or module-level constants.
安装与使用
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查看来源 ↗使用指南技能说明
Pydantic BaseSettings Class Attributes Pitfall
Overview
When defining class attributes in Pydantic BaseSettings classes, Pydantic treats them as model fields and raises an error. Move constants outside the class as module-level private constants or use ClassVar annotation.
When to Use
- Defining constants in Pydantic BaseSettings or BaseModel subclasses
- Refactoring hardcoded mappings/configs into reusable data structures
- Encountering "non-annotated attribute" errors
The Problem
Pydantic treats class attributes as model fields:
PydanticUserError: A non-annotated attribute was detected: `MAPPING = {...}`.
All model fields require a type annotation; if `MAPPING` is not meant to be a field,
you may be able to resolve this error by annotating it as a `ClassVar`
Solution
Recommended: Move constants outside the class as module-level private constants
# Correct approach
_APOLLO_MAPPING = {
"grok.api.key": "grok_api_key",
"remote.timeout": "timeout_seconds",
}
_BOOLEAN_FIELDS = ["debug", "enabled"]
class Settings(BaseSettings):
grok_api_key: str = ""
timeout_seconds: int = 30
@model_validator(mode="before")
@classmethod
def load_from_apollo(cls, data):
for apollo_key, field in _APOLLO_MAPPING.items():
...
Alternative: Use ClassVar type annotation (works but less clean)
from typing import ClassVar
class Settings(BaseSettings):
MAPPING: ClassVar[dict[str, str]] = {...}
Common Mistakes
- Defining mappings/constants directly in Pydantic classes without annotation
- Using ClassVar when module-level constants would be cleaner
- Forgetting that Pydantic validates all class attributes by default
使用示例
查看来源仓库中的使用示例与配置说明。
查看来源 ↗来源历史
- 收录时间
- 2026-03-11
- 索引更新时间
- 2026-03-11
- Branch
- main
收录与同步日期属于本站记录。源码修改历史请查看来源仓库。
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