【Python】FastAPI学习记录（一）
参数、请求体
- 使用记录
-
- 查询参数
-
- 字符串校验
- 路径参数
- 参数校验
-
- 数值校验
- 请求体
-
- 可选请求体
- 多个请求体
- 使用Body
- 字段校验
- 嵌套模型
使用记录
查询参数
字符串校验
导入Query即可快速使用：
from typing import Union
from fastapi import FastAPI, Query
app = FastAPI()
@app.get("/items/")
async def read_items(
q: Union[str, None] = Query(
default=None,
# 接口的title
title="Query string",
# 接口描述
description="Query string for the items to search in the database that have a good match",
# 参数最小长度，当然也有max_length
min_length=3,
),
):
results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
if q:
results.update({"q": q})
return results
对于请求参数在URL里面的名称可以使用alias设置别名，这样就会过去url里面的item-query参数：
@app.get("/items/")
async def read_items(q: Union[str, None] = Query(default=None, alias="item-query")):
results = {"items": [{"item_id": "Foo"}, {"item_id": "Bar"}]}
if q:
results.update({"q": q})
return results
路径参数
设置路径参数使用Path
建议使用带Annotated的版本
from typing import Annotated
from fastapi import FastAPI, Path, Query
app = FastAPI()
@app.get("/items/{item_id}")
async def read_items(
item_id: Annotated[int, Path(title="The ID of the item to get")],
q: Annotated[str | None, Query(alias="item-query")] = None,
):
results = {"item_id": item_id}
if q:
results.update({"q": q})
return results
路径参数是必须的，因为这是作为路由的一部分
参数校验
数值校验
gt：大于（greaterthan）ge：大于等于（greater than orequal）lt：小于（lessthan）le：小于等于（less than orequal）
数值校验参数，可以在Path和Query类以及其他一些类中使用
from fastapi import FastAPI, Path, Query
app = FastAPI()
@app.get("/items/{item_id}")
async def read_items(
*,
item_id: int = Path(title="The ID of the item to get", ge=0, le=1000),
q: str,
size: float = Query(gt=0, lt=10.5),
):
results = {"item_id": item_id}
if q:
results.update({"q": q})
return results
请求体
可选请求体
如下可以声明一个可选请求体：
from typing import Annotated
from fastapi import FastAPI, Path
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
@app.put("/items/{item_id}")
async def update_item(
item_id: Annotated[int, Path(title="The ID of the item to get", ge=0, le=1000)],
q: str | None = None,
item: Item | None = None,
):
results = {"item_id": item_id}
if q:
results.update({"q": q})
if item:
results.update({"item": item})
return results
多个请求体
可以声明多个请求体
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
class User(BaseModel):
username: str
full_name: str | None = 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
这样声明下，FastAPI期望一个类似下面内容的请求体：
{
"item": {
"name": "Foo",
"description": "The pretender",
"price": 42.0,
"tax": 3.2
},
"user": {
"username": "dave",
"full_name": "Dave Grohl"
}
}
请注意，即使
item的声明方式与之前相同，但现在它被期望通过item键内嵌在请求体中。
使用Body
from typing import Annotated
from fastapi import Body, FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
class User(BaseModel):
username: str
full_name: str | None = None
@app.put("/items/{item_id}")
async def update_item(
item_id: int, item: Item, user: User, importance: Annotated[int, Body()]
):
results = {"item_id": item_id, "item": item, "user": user, "importance": importance}
return results
上面的例子中，引入了Body，他和Query与Path类似，在这里importance将会被内嵌于请求体中，而不是查询参数，按照这样的设置，FastAPI期待如下的请求体：
{
"item": {
"name": "Foo",
"description": "The pretender",
"price": 42.0,
"tax": 3.2
},
"user": {
"username": "dave",
"full_name": "Dave Grohl"
},
"importance": 5
}
Body也可以用来包裹单个Pydantic 模型 作为请求体，针对Item而言，如果希望得到下面的请求体：
{
"item": {
"name": "Foo",
"description": "The pretender",
"price": 42.0,
"tax": 3.2
}
}
则可以使用如下代码：
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
results = {"item_id": item_id, "item": item}
return results
字段校验
使用Field进行字段设置，这个从pydantic引入，而不是FaskAPI，Field的可用参数和Body等类似
from typing import Annotated
from fastapi import Body, FastAPI
from pydantic import BaseModel, Field
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = Field(
default=None, title="The description of the item", max_length=300
)
price: float = Field(gt=0, description="The price must be greater than zero")
tax: float | None = None
@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
results = {"item_id": item_id, "item": item}
return results
嵌套模型
很多时候请求体不是简单的层次，可能会出现多种数据类型组合的模式，比如某个字段是list：
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
tags: list = []
@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):
results = {"item_id": item_id, "item": item}
return results
一般来说，可能对list的字段类型会做限制，比如限制为str，且不能重复，那么可以用set方法：
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
# 使用set，即使传入的list是有重复的也会被处理去重
tags: set[str] = set()
@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):
results = {"item_id": item_id, "item": item}
return results
也可以在模型中嵌套模型，如下就是在Item中嵌套了Image：
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
# 声明了Image
class Image(BaseModel):
url: str
name: str
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
tags: set[str] = set()
# image是一个Image模型类型
image: Image | None = None
@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):
results = {"item_id": item_id, "item": item}
return results
这样可以接收一个嵌套的json请求体：
{
"name": "Foo",
"description": "The pretender",
"price": 42.0,
"tax": 3.2,
"tags": ["rock", "metal", "bar"],
"image": {
"url": "http://example.com/baz.jpg",
"name": "The Foo live"
}
}
嵌套时，也可以使用Pydantic中提供的类型进行简单的校验，比如url这种字段，一般是固定格式的，可以使用HttpUrl进行校验：
from fastapi import FastAPI
from pydantic import BaseModel, HttpUrl
app = FastAPI()
class Image(BaseModel):
url: HttpUrl
name: str
class Item(BaseModel):
name: str
description: str | None = None
price: float
tax: float | None = None
tags: set[str] = set()
image: Image | None = None
@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item):
results = {"item_id": item_id, "item": item}
return results