查询参数模型¶
如果你有一组相关的查询参数，可以创建一个 Pydantic 模型来声明它们。
这允许你在多个地方重复使用该模型，同时还能一次性为所有参数声明验证规则和元数据。😎
Note
此功能从 FastAPI 版本 0.115.0 开始支持。🤓
使用 Pydantic 模型声明查询参数¶
在 Pydantic 模型中声明你需要的查询参数，然后将参数声明为 Query：
from typing import Annotated, Literal
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
app = FastAPI()
class FilterParams(BaseModel):
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
return filter_query
🤓 Other versions and variants
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Annotated, Literal
app = FastAPI()
class FilterParams(BaseModel):
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
return filter_query
from typing import List
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Annotated, Literal
app = FastAPI()
class FilterParams(BaseModel):
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: List[str] = []
@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
return filter_query
Tip
Prefer to use the Annotated version if possible.
from typing import Literal
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
app = FastAPI()
class FilterParams(BaseModel):
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):
return filter_query
Tip
Prefer to use the Annotated version if possible.
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Literal
app = FastAPI()
class FilterParams(BaseModel):
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):
return filter_query
Tip
Prefer to use the Annotated version if possible.
from typing import List
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Literal
app = FastAPI()
class FilterParams(BaseModel):
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: List[str] = []
@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):
return filter_query
FastAPI 会从请求的查询参数中为每个字段提取数据，并返回你定义的 Pydantic 模型。
查看文档¶
你可以在 /docs 的文档界面中查看查询参数：
禁止额外查询参数¶
在某些特殊使用场景中（可能不太常见），你可能需要限制希望接收的查询参数。
你可以使用 Pydantic 的模型配置来 forbid 任何 extra 字段：
from typing import Annotated, Literal
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
app = FastAPI()
class FilterParams(BaseModel):
model_config = {"extra": "forbid"}
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
return filter_query
🤓 Other versions and variants
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Annotated, Literal
app = FastAPI()
class FilterParams(BaseModel):
model_config = {"extra": "forbid"}
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
return filter_query
from typing import List
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Annotated, Literal
app = FastAPI()
class FilterParams(BaseModel):
model_config = {"extra": "forbid"}
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: List[str] = []
@app.get("/items/")
async def read_items(filter_query: Annotated[FilterParams, Query()]):
return filter_query
Tip
Prefer to use the Annotated version if possible.
from typing import Literal
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
app = FastAPI()
class FilterParams(BaseModel):
model_config = {"extra": "forbid"}
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):
return filter_query
Tip
Prefer to use the Annotated version if possible.
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Literal
app = FastAPI()
class FilterParams(BaseModel):
model_config = {"extra": "forbid"}
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: list[str] = []
@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):
return filter_query
Tip
Prefer to use the Annotated version if possible.
from typing import List
from fastapi import FastAPI, Query
from pydantic import BaseModel, Field
from typing_extensions import Literal
app = FastAPI()
class FilterParams(BaseModel):
model_config = {"extra": "forbid"}
limit: int = Field(100, gt=0, le=100)
offset: int = Field(0, ge=0)
order_by: Literal["created_at", "updated_at"] = "created_at"
tags: List[str] = []
@app.get("/items/")
async def read_items(filter_query: FilterParams = Query()):
return filter_query
如果客户端尝试在查询参数中发送一些额外数据，他们将收到一个错误响应。
例如，如果客户端尝试发送值为 plumbus 的 tool 查询参数，如：
https://example.com/items/?limit=10&tool=plumbus
他们将收到一个错误响应，提示查询参数 tool 不被允许：
{
"detail": [
{
"type": "extra_forbidden",
"loc": ["query", "tool"],
"msg": "Extra inputs are not permitted",
"input": "plumbus"
}
]
}
总结¶
你可以在 FastAPI 中使用 Pydantic 模型来声明查询参数。😎
Tip
剧透提醒：你也可以使用 Pydantic 模型来声明 cookie 和请求头，不过你将在后续教程中了解到这些内容。🤫