yanyongyuchanged the titleFeature: 为model_dump增加exclude_*参数、添加type_validate_json函数Feb 17, 2024 View detailsyanyongyumerged commita830346intomasterFeb 17, 2024 41 of 43 checks passed yanyongyudeleted thefeature/pydantic-methodsbranchFebruary 17, 2024 15:18 ...
model_dump()) except ValidationError as e: print(f"Validation error: {e.json()}") 执行结果: Validation error: [{"type":"value_error","loc":[],"msg":"Value error, 用户年龄必须小于30岁, 且名字必须为小卤蛋","input":{"id":123,"name":"小小卤蛋","age":20,"email":"xiaoludan@...
Initial Checks I confirm that I'm using Pydantic V2 Description I am working to upgrade my code to Pydantic V2 and I'm ruinning into the following test failure: > assert parsed_event.model_dump_json(exclude_none=True) == json.dumps(event...
frompydanticimportBaseModelclassPerson(BaseModel):name:strage:intemail:str 在这个模型中，本文指定了预...
class SimpleModelDumpable(BaseModel): password: SecretStr password_bytes: SecretBytes class Config: json_encoders = { SecretStr: lambda v: v.get_secret_value() if v else None, SecretBytes: lambda v: v.get_secret_value() if v else None, } sm2 = SimpleModelDumpable( password='IAmSensi...
passwd: SecretStr = Field(min_length=6, max_length=20, exclude=True) # passwd不会被序列化 if __name__ == '__main__': print(User.model_json_schema()) user_data = { "_id": 123, # 使用别名 _id "name": "小卤蛋", "age": 20, ...
exclude_none 的 model.model_dump 参数将应用于所有响应条目,因此不合适。 所需的转储结果,当 response.metadata.attr2 = None response = { "stuff1": None "stuff2": 4 "metadata": { "attr1": "hello" } } 我知道 Pydantic v2 有自定义序列化,它允许控制对象如何转换为 JSON,但我使用的是 1.1...
@app.post("/my-post-route") def post_route(data: DBModelView): ... return data.model_dump() Pydantic 版本 1 等效项: from pydantic import create_model EXCLUDE_FIELDS = ['date', 'id'] DBModelView = create_model('DBModelView') DBModelView.__fields__ = { f: DBModel.__fields_...
如果你想避免在输入中没有principal_id字段的时候在模型中使用它，你可以在Pydantic中使用pre方法。这允许你在验证之前预处理数据。这里有一个例子，你可以如何实现这一点：
type.python_type name = attr.key if name in exclude: continue default = None if column.default is None and not column.nullable: default = ... fields[name] = (python_type, default) pydantic_model = create_model( db_model.__name__, **fields # type: ignore ) return pydantic_model ...