from typing import Union

from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: Union[str, None] = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")

from typing import Annotated, Any, Union

from fastapi import Depends, FastAPI

app = FastAPI()


fake_items_db = [{"item_name": "Foo"}, {"item_name": "Bar"}, {"item_name": "Baz"}]


class CommonQueryParams:
    def __init__(self, q: Union[str, None] = None, skip: int = 0, limit: int = 100):
        self.q = q
        self.skip = skip
        self.limit = limit


@app.get("/items/")

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class BaseItem(BaseModel):
    description: str
    type: str


class CarItem(BaseItem):
    type: str = "car"


class PlaneItem(BaseItem):
    type: str = "plane"
    size: int


items = {
    "item1": {"description": "All my friends drive a low rider", "type": "car"},
    "item2": {

from typing import Annotated

from fastapi import FastAPI, Header

app = FastAPI()


@app.get("/items/")
async def read_items(
    strange_header: Annotated[str | None, Header(convert_underscores=False)] = None,
):

from typing import Annotated

from fastapi import FastAPI, Query

app = FastAPI()


@app.get("/items/")
async def read_items(q: Annotated[list[str], Query()] = ["foo", "bar"]):
    query_items = {"q": q}

Por exemplo, extendendo o modelo anterior, você poder decidir por ter uma outra chave `importance` no mesmo corpo, além de `item` e `user`.

Se você declará-lo como é, porque é um valor singular, o **FastAPI** assumirá que se trata de um parâmetro de consulta.

Mas você pode instruir o **FastAPI** para tratá-lo como outra chave do corpo usando `Body`:

**FastAPI** bietet dieselben `starlette.responses` auch via `fastapi.responses` an, als Annehmlichkeit für Sie, den Entwickler. Die meisten verfügbaren Responses kommen aber direkt von Starlette.

Und da die `Response` häufig zum Setzen von Headern und Cookies verwendet wird, stellt **FastAPI** diese auch unter `fastapi.Response` bereit.

///

* Headern.
* Cookies.
* usw.

Und indem Sie das tun, validiert **FastAPI** diese Daten, konvertiert sie und generiert automatisch Dokumentation für Ihre API.

Es gibt jedoch Situationen, in denen Sie möglicherweise direkt auf das `Request`-Objekt zugreifen müssen.

## Details zum `Request`-Objekt { #details-about-the-request-object }

**FastAPI** provides the same `starlette.responses` as `fastapi.responses` just as a convenience for you, the developer. But most of the available responses come directly from Starlette.

And as the `Response` can be used frequently to set headers and cookies, **FastAPI** also provides it at `fastapi.Response`.

///

## Custom Headers { #custom-headers }

# 表单模型

您可以使用 **Pydantic 模型**在 FastAPI 中声明**表单字段**。

/// info

要使用表单，需预先安装 <a href="https://github.com/Kludex/python-multipart" class="external-link" target="_blank">`python-multipart`</a> 。

确保您创建、激活一个[虚拟环境](../virtual-environments.md){.internal-link target=_blank}后再安装。

```console
$ pip install python-multipart
```

///

/// note

自 FastAPI 版本 `0.113.0` 起支持此功能。🤓

///

## 表单的 Pydantic 模型