响应模型

可以在任意路径操作（get,post等）中使用response_model来声明用于返回响应模型

from typing import Anyfrom fastapi import FastAPI
from pydantic import BaseModel, EmailStr
app = FastAPI()class UserIn(BaseModel):username: strpassword: stremail: EmailStrfull_name: str | None = Noneclass UserOut(BaseModel):username: stremail: EmailStrfull_name: str | None = None@app.post("/user/", response_model=UserOut)
async def create_user(user: UserIn) -> Any:return user

需要注意response_model是[装饰器]方法（get,post等）的一个参数，不像之前参数和请求，它不属于路径操作函数

请求体使用UserIn，响应模型使用UserOut，未在输出模型声明的参数都会被过滤掉，示例响应模型会把请求体中的密码给过滤掉。

响应模型编码参数

from typing import List, Unionfrom fastapi import FastAPI
from pydantic import BaseModelapp = FastAPI()class Item(BaseModel):name: strdescription: Union[str, None] = Noneprice: floattax: float = 10.5tags: List[str] = []items = {"foo": {"name": "Foo", "price": 50.2},"bar": {"name": "Bar", "description": "The bartenders", "price": 62, "tax": 20.2},"baz": {"name": "Baz", "description": None, "price": 50.2, "tax": 10.5, "tags": []},
}@app.get("/items/{item_id}", response_model=Item, response_model_exclude_unset=True)
async def read_item(item_id: str):return items[item_id]@app.get("/items/{item_id}/name",response_model=Item,response_model_include={"name", "description"},
)
async def read_item_name(item_id: str):return items[item_id]@app.get("/items/{item_id}/public", response_model=Item, response_model_exclude={"tax"})
async def read_item_public_data(item_id: str):return items[item_id]

在item_id都使用foo情况下

response_model_exclude_unset=True：响应会过滤默认值，只返回实际设置的值

{"name": "Foo","price": 50.2
}

response_model_include：需要传一个set()，只显示set中设置的值

{"name": "Foo","description": null
}

response_model_exclude：需要传一个set()，过滤set中设置的值

{"name": "Foo","description": null,"price": 50.2,"tags": []
}

通过继承减少重复

对用户模型来说尤其如此，因为：

• 输入模型需要拥有密码属性。
• 输出模型不应该包含密码。
• 数据库模型很可能需要保存密码的哈希值。

from fastapi import FastAPI
from pydantic import BaseModel, EmailStrapp = FastAPI()class UserBase(BaseModel):username: stremail: EmailStrfull_name: str | None = Noneclass UserIn(UserBase):password: strclass UserOut(UserBase):passclass UserInDB(UserBase):hashed_password: strdef fake_password_hasher(raw_password: str):return "supersecret" + raw_passworddef fake_save_user(user_in: UserIn):hashed_password = fake_password_hasher(user_in.password)user_in_db = UserInDB(**user_in.dict(), hashed_password=hashed_password)print("User saved! ..not really")return user_in_db@app.post("/user/", response_model=UserOut)
async def create_user(user_in: UserIn):user_saved = fake_save_user(user_in)return user_saved

 可以先声明userBase为基础模型，然后创建继承该模型属性（类型声明，校验等）的子类，只要在子类中添加于基础模型不同的字段即可。

多个响应模型

可以将一个响应声明为两种类型的 Union，这意味着该响应将是两种类型中的任何一种

from typing import Unionfrom fastapi import FastAPI
from pydantic import BaseModelapp = FastAPI()class BaseItem(BaseModel):description: strtype: strclass CarItem(BaseItem):type: str = "car"class PlaneItem(BaseItem):type: str = "plane"size: intitems = {"item1": {"description": "All my friends drive a low rider", "type": "car"},"item2": {"description": "Music is my aeroplane, it's my aeroplane","type": "plane","size": 5,},
}@app.get("/items/{item_id}", response_model=Union[PlaneItem, CarItem])
async def read_item(item_id: str):return items[item_id]

item_id传item1

{"description": "All my friends drive a low rider","type": "car"
}

item_id传item2

{"description": "Music is my aeroplane, it's my aeroplane","type": "plane","size": 5
}