查询参数模型¶
如果你有一组具有相关性的查询参数，你可以创建一个 Pydantic 模型来声明它们。
这将允许你在多个地方去复用模型，并且一次性为所有参数声明验证和元数据。😎
Note
FastAPI 从 0.115.0 版本开始支持这个特性。🤓
使用 Pydantic 模型的查询参数¶
在一个 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 将会从请求的查询参数中提取出每个字段的数据，并将其提供给你定义的 Pydantic 模型。
查看文档¶
你可以在 /docs 页面的 UI 中查看查询参数：
禁止额外的查询参数¶
在一些特殊的使用场景中（可能不是很常见），你可能希望限制你要接收的查询参数。
你可以使用 Pydantic 的模型配置来 forbid（意为禁止 —— 译者注）任何 extra（意为额外的 —— 译者注）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
假设有一个客户端尝试在查询参数中发送一些额外的数据，它将会收到一个错误响应。
例如，如果客户端尝试发送一个值为 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，告诉他们查询参数 tool 是不允许的：
{
"detail": [
{
"type": "extra_forbidden",
"loc": ["query", "tool"],
"msg": "Extra inputs are not permitted",
"input": "plumbus"
}
]
}
总结¶
你可以使用 Pydantic 模型在 FastAPI 中声明查询参数。😎
Tip
剧透警告：你也可以使用 Pydantic 模型来声明 cookie 和 headers，但你将在本教程的后面部分阅读到这部分内容。🤫