Python – pydantic（2）嵌套模型

简单的栗子

class User(BaseModel):id: int  # 必填字段name: str = \"小菠萝\"  # 有默认值，选填字段signup_ts: Optional[datetime] = Nonefriends: List[int] = []  # 列表中元素是 int 类型，或可以直接转成 int 的类型# 关键字参数user = User(id=\"1\",name=\"大菠萝\",signup_ts=\"2021-09-16 12:22\")print(user.dict())# 字典解包传参data = {\"id\": \"2\",\"name\": \"大大的菠萝\",\"friends\": [1, 2, 3]}user = User(**data)print(user.dict())# 输出结果{\'id\': 1, \'name\': \'大菠萝\', \'signup_ts\': datetime.datetime(2021, 9, 16, 12, 22), \'friends\': []}{\'id\': 2, \'name\': \'大大的菠萝\', \'signup_ts\': None, \'friends\': [1, 2, 3]}

嵌套模型

可以使用模型本身作为数据类型提示来定义更复杂的分层数据结构

from typing import Listfrom pydantic import BaseModelclass Foo(BaseModel):count: intsize: float = Noneclass Bar(BaseModel):apple = \'x\'banana = \'y\'class Spam(BaseModel):foo: Foobars: List[Bar]f = Foo(count=2)b = Bar()s = Spam(foo=f, bars=[b])print(s.dict())# 输出结果{\'bars\': [{\'apple\': \'x\', \'banana\': \'y\'}], \'foo\': {\'count\': 2, \'size\': None}}