from fastapi import Depends, FastAPI, Header, HTTPException

app = FastAPI()


async def verify_token(x_token: str = Header()):
    if x_token != "fake-super-secret-token":
        raise HTTPException(status_code=400, detail="X-Token header invalid")


async def verify_key(x_key: str = Header()):
    if x_key != "fake-super-secret-key":
        raise HTTPException(status_code=400, detail="X-Key header invalid")
    return x_key

from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse


class UnicornException(Exception):
    def __init__(self, name: str):
        self.name = name


app = FastAPI()


@app.exception_handler(UnicornException)
async def unicorn_exception_handler(request: Request, exc: UnicornException):
    return JSONResponse(
        status_code=418,

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: 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:

这段代码声明了类型为 `str` 的可选查询参数 `q`，然后返回这个查询参数。

这个函数很简单（不过也没什么用），但却有助于让我们专注于了解子依赖项的工作方式。

### 第二层依赖项

接下来，创建另一个依赖项函数，并同时用该依赖项自身再声明一个依赖项（所以这也是一个「依赖项」）：

{* ../../docs_src/dependencies/tutorial005.py hl[13] *}

这里重点说明一下声明的参数：

* 尽管该函数自身是依赖项，但还声明了另一个依赖项（它「依赖」于其他对象）
    * 该函数依赖 `query_extractor`, 并把 `query_extractor` 的返回值赋给参数 `q`
* 同时，该函数还声明了类型是 `str` 的可选 cookie（`last_query`）

与之前直接在路径操作中的做法相同，新的 `get_current_user` 依赖项从子依赖项 `oauth2_scheme` 中接收 `str` 类型的 `token`：

{* ../../docs_src/security/tutorial002.py hl[25] *}

## 获取用户

`get_current_user` 使用创建的（伪）工具函数，该函数接收 `str` 类型的令牌，并返回 Pydantic 的 `User` 模型：

{* ../../docs_src/security/tutorial002.py hl[19:22,26:27] *}

## 注入当前用户

在*路径操作* 的 `Depends` 中使用 `get_current_user`：

{* ../../docs_src/security/tutorial002.py hl[31] *}

* Datenvalidierung
* Automatische Dokumentation

## Spezielle Typen und Validierungen { #special-types-and-validation }

Abgesehen von normalen einfachen Typen wie `str`, `int`, `float`, usw. können Sie komplexere einfache Typen verwenden, die von `str` erben.

        Field(discriminator="value"),
    ]

    @app.post("/items/")
    def save_union_body_discriminator(
        item: Item, q: Annotated[str, Field(description="Query string")]
    ) -> dict[str, Any]:
        return {"item": item}

    client = TestClient(app)
    response = client.post("/items/?q=first", json={"value": "first", "price": 100})

    client = TestClient(mod.app)
    return client


@pytest.mark.parametrize("price", ["50.5", 50.5])
def test_post_with_tax(client: TestClient, price: Union[str, float]):
    response = client.post(
        "/items/",
        json={"name": "Foo", "price": price, "description": "Some Foo", "tax": 0.3},
    )
    assert response.status_code == 200
    assert response.json() == {

from typing import Annotated, Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Annotated[
        Item,
        Body(
            examples=[

def get_username():
    try:
        yield "Rick"
    except OwnerError as e:
        raise HTTPException(status_code=400, detail=f"Owner error: {e}")


@app.get("/items/{item_id}")
def get_item(item_id: str, username: Annotated[str, Depends(get_username)]):
    if item_id not in data:
        raise HTTPException(status_code=404, detail="Item not found")
    item = data[item_id]
    if item["owner"] != username: