1.请求参数附加信息

#!/usr/bin/env python
# encoding: utf-8

from fastapi import FastAPI, Query
from typing import Optional
import uvicorn

app = FastAPI()

@app.get('/items/')
async def read_items(q: Optional[str] = Query(None, min_length=3, max_length=50)):
    results = {'message': 'item'}
    if q:
        results.update({'q': q})
    return results

if __name__ == '__main__':
    uvicorn.run(app=app, host='127.0.0.1', port=8000)

使用Query作为默认值, 将参数设置min_length为3,max_length为50
添加正则表达式 q: Optional[str] = Query(None, regex="^fixedquery$")
设置默认值 q: str = Query("fixedquery", min_length=3)
title：参数标题
description：参数描述信息
deprecated：表示参数即将过期
alias：参数别名
当不需要声明更多的验证或元数据时，q只需不声明默认值即可使查询参数成为必需：q: str，
当使用Query声明它时，可以将...用作第一个参数，代表必填 eg: q: str = Query(..., min_length=3)

@app.get('/items/')
async def read_item(q: str = Query(..., min_length=3)):
"""使用Query声明它时，可以将...用作第一个参数"""
    results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
    if q:
        results.update({"q": q})
    return results

2.请求参数列表

#!/usr/bin/env python
# encoding: utf-8

from fastapi import FastAPI, Query
from typing import Optional, List
import uvicorn

app = FastAPI()

@app.get('/items_list/')
async def read_item_list(q: Optional[List[str]] = Query(None)):
    query_items = {"q": q}
    return query_items


if __name__ == '__main__':
    uvicorn.run(app=app, host='127.0.0.1', port=8000)

    访问：http://localhost:8000/items/?q=foo&q=bar
    得到结果：{"q": ["foo", "bar"]}
    (1).请求参数列表的缺省值设置：q: List[str] = Query(["foo", "bar"])
    (2).可以用list代替List[str]，但这样的话FastAPI就无法校验列表内容了: q: list = Query(None)

3. 路径参数附加信息

#!/usr/bin/env python
# encoding: utf-8

from fastapi import FastAPI, Query, Path
from typing import Optional
import uvicorn

app = FastAPI()

@app.get('/item_path/{item_id}')
async def read_items_path(
        item_id: int = Path(..., title='The ID of the item to get'),
        q: Optional[str] = Query(None, alias='item-query'),
        size: float = Query(1, gt=0, lt=10.5)
):
    """
    路径参数附加信息
    路径参数在URL里是必选的，因此Path的第一个参数是...，即使你传递了None或其他缺省值，也不会影响参数的必选性。
    """
    results = {'item_id': item_id, 'size': size}
    if q:
        results.update({"q": q})
    return results


if __name__ == '__main__':
    uvicorn.run(app=app, host='127.0.0.1', port=8000)

4. 混合Path，Query和body参数

#!/usr/bin/env python
# encoding: utf-8

from fastapi import FastAPI, Query, Path
import uvicorn
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    description: str = None
    price: float
    tax: float = None

"""
(1).如果把带有缺省值的参数放在了不带缺省值的参数前面，Python会发出运行警告。
因此在实际使用时，我们应当把不带缺省值的参数放在前面，无论这个参数是路径参数还是请求参数。
query: str, item_id: int = Path(..., title="The ID of the item to get")
(2).通过传递 * 作为第一个参数，就解决了上面的参数顺序问题。
*, item_id: int = Path(..., title="The ID of the item to get"), q: str
"""
@app.post('/body/{item_id}')
async def body(
        query: str,
        item_id: int = Path(..., title='', ge=10, le=100),
        item: Item = None
):
    result = {'item_id': item_id}
    if query:
        result.update({"query": query})
    if item:
        result.update({"item": item})
    return result


if __name__ == '__main__':
    uvicorn.run(app)

5. 多body

from typing import Optional
from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    description: Optional[str] = None
    price: float
    tax: Optional[float] = None

class User(BaseModel):
    username: str
    full_name: Optional[str] = None

@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, user: User):
    results = {"item_id": item_id, "item": item, "user": user}
    return results

响应参数：

6. body 的奇异值

from typing import Optional
from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    description: Optional[str] = None
    price: float
    tax: Optional[float] = None


class User(BaseModel):
    username: str
    full_name: Optional[str] = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, user: User, importance: int = Body(...)):
    results = {"item_id": item_id, "item": item, "user": user, "importance": importance}
    return results

以上相当于将importance 参数 与User  Item 组合起来形成一个大的body

7. 嵌入单一body

from typing import Optional
from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    description: Optional[str] = None
    price: float
    tax: Optional[float] = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item = Body(..., embed=True)):
    results = {"item_id": item_id, "item": item}
    return results

item: Item = Body(..., embed=True)
这里"item"是Request Body内部数据内容的键值，那么我们就需要利用Body方法的embed参数，才能正确解析出Request Body内容。使用后参数形式为：
{
    "item": {
        "name": "Foo",
        "description": "The pretender",
        "price": 42.0,
        "tax": 3.2
    }
}

8. body 内参数验证 Feild

需注意的：Feild 是基于pydantic 导出的

from typing import Optional
from fastapi import Body, FastAPI
from pydantic import BaseModel, Field

app = FastAPI()

class Item(BaseModel):
    name: str
    description: Optional[str] = Field(
        None, title="The description of the item", max_length=300
    )
    price: float = Field(..., gt=0, description="The price must be greater than zero")
    tax: Optional[float] = None

@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item = Body(..., embed=True)):
    results = {"item_id": item_id, "item": item}
    return results