我们已经提到过Path以及Query,下面来看看更好的对于请求正文的声明
body-多个参数
混合Path,Query和请求正文参数
eg:
from fastapi import FastAPI, Path
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str = None
price: float
tax: float = None
@app.put("/items/{item_id}")
async def update_item(
*,
item_id: int = Path(..., title="The ID of the item to get", ge=0, le=1000),
q: str = None,
item: Item = None,
):
results = {"item_id": item_id}
if q:
results.update({"q": q})
if item:
results.update({"item": item})
return results
多个请求正文参数
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str = None
price: float
tax: float = None
class User(BaseModel):
username: str
full_name: 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
请求body:
{
"item": {
"name": "Foo",
"description": "The pretender",
"price": 42.0,
"tax": 3.2
},
"user": {
"username": "dave",
"full_name": "Dave Grohl"
}
}
body中的单个值参数
因为在fastapi中默认将单个值识别为查询参数所以
fastapi提供了Body,类似Path、Query
。。。
@app.put("/items/{item_id}")
async def update_item(
*, item_id: int, item: Item, user: User, importance: int = Body(…)
):
。。。
然后请求主体就是:
{
“item”: {
“name”: “Foo”,
“description”: “The pretender”,
“price”: 42.0,
“tax”: 3.2
},
“user”: {
“username”: “dave”,
“full_name”: “Dave Grohl”
},
“importance”: 5
}
嵌入单个请求主体参数
当只有单个请求主体参数时,默认fastapi只会直接读取其主体。
但是当想要一个json带有key,item在请求正文中,可以使用embed
from fastapi import Body, FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str = None
price: float
tax: 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
请求主体为:
{
"item": {
"name": "Foo",
"description": "The pretender",
"price": 42.0,
"tax": 3.2
}
}
body-fields
在pydantic模型内部使用Field来声明验证和metadata
eg:
from fastapi import Body, FastAPI
from pydantic import BaseModel, Field
app = FastAPI()
class Item(BaseModel):
name: str
description: 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: 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
额外的json schema
在field,path,query,body中,可以声明额外的部分。
这些参数将被添加到json格式输出。
eg:
from fastapi import Body, FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str = None
price: float
tax: float = None
@app.put("/items/{item_id}")
async def update_item(
*,
item_id: int,
item: Item = Body(
...,
example={
"name": "Foo",
"description": "A very nice Item",
"price": 35.4,
"tax": 3.2,
},
)
):
results = {"item_id": item_id, "item": item}
return results
然后在docs中显示为:

Body-嵌套模型
List fields
可以定义一个属性是子类型,例如list
eg:
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Item(BaseModel):
name: str
description: str = None
price: float
tax: float = 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
其中tags,可以进行子类型验证
eg:
from typing import List
…
tags:List[str]=[]
…
拥有子类型的类型包括:list,dict,tuple等。
set type
from typing imoprt Set
…
tags:Set[str]=set()
…
嵌套模型
eg:
from typing import Set
from fastapi import FastAPI
from pydantic import BaseModel
app = FastAPI()
class Image(BaseModel):
url: str
name: str
class Item(BaseModel):
name: str
description: str = None
price: float
tax: float = None
tags: Set[str] = []
image: Image = None
特别的类型和验证
除了常规的单类型,str,int,float等,你可以使用更复杂的继承自str的单类型。
可以在Pydantic exotic types
中查看更多的类型。
例如,在字段中有一个url field,我们可以将它声明为HttpUrl 去代替str
from pydantic import BaseModel, HttpUrl
class Image(BaseModel):
url: HttpUrl
name: str
这个url字段将被验证是否是正确的Url。
list中也可使用子模型。
images: List[Image] = None
注意:如果事前不知道传送的body中key是什么,可以直接使用
async def create_index_weights(weights: Dict[int, float]):…
body中拥有int类型的key和float类型的值。
本文深入探讨FastAPI框架中如何处理复杂的HTTP请求体,包括混合使用Path、Query与请求体参数,处理多个请求体参数,以及使用嵌入、Body、Field等特性进行精细的参数控制和验证。
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