from typing import List from pydantic import BaseModel, parse_obj_as class Item(BaseModel): id: int name: str # `item_data` could come from an API call, eg., via something like: # item_data = requests.get('https://my-api.com/items').json() item_data = [{'id': 1, 'name'...
{“message”:“DocumentSchema\ndocumentList->0->articleList->0->otherData的1个验证错误\n JSON对象必须是str、bytes或bytearray(type=type_error.json)"” 我应该提到,没有OtherData一切都好。 我不知道怎么修理它。 提前谢谢。 发生此错误的原因是Json类型希望获得一个JSON字符串以反序列化(作为str、bytes...
│ │ │ └ {'__name__': '__main__', '__doc__': "\nMain entry point into API for endpoints related to HawkSense's main functionality.\nto... │ │ └ {'__name__': '__main__', '__doc__': "\nMain entry point into API for endpoints related to HawkSense's main func...
github.com/pydantic/pydantic) [](https://github.com/pydantic/pydantic/blob/main/LICENSE) []...
Do not compute JSON Schema default when plain serializers are used with when_used set to 'json-unless-none' and the default value is None by @Viicos in #10121 Fix ImportString special cases by @sydney-runkle in #10137 Blacklist default globals to support exotic user code with __ prefix...
Add Python 3.9 and 3.10 examples to docs, #4339 by @Bobronium Discriminated union models now use oneOf instead of anyOf when generating OpenAPI schema definitions, #4335 by @MaxwellPayne Allow type checkers to infer inner type of Json type. Json[list[str]] will be now inferred as list[...
"If you like cattrs, you might be interested in trying out my msgspec library. It works out-of-the-box with attrs objects while being ~10-15x faster than cattrs for encoding/decoding/validating JSON." from Hacker News eyegor 👨💻 "Fastapi suffers from the 'one solo dev in Nebr...
import time from typing import Annotated from pydantic import PositiveFloat, Field, EmailStr, validate_call @validate_call def send_invoice( client_name: Annotated[str, Field(min_length=1)], client_email: EmailStr, items_purchased: list[str], amount_owed: PositiveFloat, ) -> str: email_str...
Provides functionality to serialize model in three ways: To a Python dict made up of the associated Python objects. To a Python dict made up only of “jsonable” types. To a JSON string. JSON Schema can be generated for any Pydantic schema — allowing self-documenting APIs and integration ...
使用[递归pydantic模型](# 3.1.2 递归模型)、typing 的标准类型 (如 List、Tuple 和 Dict 等) 和验证器,可以很清晰且容易地定义、验证和解析复杂数据模式。 可拓展 pydantic允许定义[自定义数据类型](# 3.2.7 自定义数据类型),或者您可以使用被 validator 装饰器装饰的模型上的方法来扩展验证。