json_encoders: 为特定类型提供自定义的 JSON 编码器。 alias_generator: 生成别名的函数,用于字段名称,通常用于生成符合特定API规范的别名。 allow_population_by_field_name: 允许通过字段名称而不是别名来填充模型数据。 min_anystr_length: 字符串和字节类型字段的最小长度。 max_anystr_length: 字符串和字节类...
1.直接在模型上Field(..., alias=) 2.直接在模型上Config.fieldsfields = {'language_code': 'lang'} 3.在父模型上Field(..., alias=) 4.父模型上定义在 中定义Config.fields 6.无论它是在模型上还是在父模型上alias_generator 6.Smart Union fromtypingimportUnionfrompydanticimportBaseModelclassFoo(Bas...
从pydantic 导入 BaseModel, ConfigDict, AliasGenerator, AliasChoices 别名= { "first_name": AliasChoices("fname", "surname", "forename", "first_name"), "last_name": AliasChoices("lname", "family_name", "last_name") } 类FirstNameChoices(BaseModel): ...
hosp_code: Annotated[Union[str, None], Query(alias="hospCode")], study_instance_uid: Annotated[Union[str, None], Query(alias="studyInstanceUid")], ): 请求体参数校验 非必填defalut =None class AIMDcmReciprocalZipRequest(BaseModel): model_config = ConfigDict(alias_generator=to_camel) request...
在我使所有字段都具有相应的PascalCase别名的设置中添加了一个alias_generator = to_camel。
alias_generator = lambda x: x.upper() allow_population_by_field_name = True @app.post("/items/") async def create_item(item: Item): return item 3.3 模型文档 通过Field 的 description 参数,可以为模型字段添加描述信息,这些信息将显示在 API 文档中。
class Item(BaseModel): name: str description: str = None class Config: alias_generator = lambda x: x.upper() allow_population_by_field_name = True @app.post("/items/") async def create_item(item: Item): return item 3.3 模型文档 通过Field 的description 参数,可以为模型字段添加描述信息,...
add alias_generator support, #622 by @Bobronium fix unparameterized generic type schema generation, #625 by @dmontagu fix schema generation with multiple/circular references to the same model, #621 by @tiangolo and @wongpat support custom root types, #628 by @koxudaxi support self as a fi...
This was an alias to str | bytes. pydantic.compiled pydantic.config.get_config pydantic.config.inherit_config pydantic.config.prepare_config pydantic.create_model_from_namedtuple pydantic.create_model_from_typeddict pydantic.dataclasses.create_pydantic_model_from_dataclass pydantic.dataclasses.make_datacl...
(https://docs.pydantic.dev/latest/contributing/#badges) Data validation using Python type hints. Fast and extensible, Pydantic plays nicely with your linters/IDE/brain. Define how data should be in pure, canonical Python 3.8+; validate it with Pydantic. ## Pydantic Logfire :fire: We've ...