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,

class LabelSettings(BaseModel):
    await_label: str | None = None
    number: int


default_config = {"approved-2": LabelSettings(await_label="awaiting-review", number=2)}


class Settings(BaseSettings):
    github_repository: str
    token: SecretStr
    debug: bool | None = False
    config: dict[str, LabelSettings] | Literal[""] = default_config


settings = Settings()

from dataclasses import dataclass, field
from typing import Union

from fastapi import FastAPI


@dataclass
class Item:
    name: str
    price: float
    tags: list[str] = field(default_factory=list)
    description: Union[str, None] = None
    tax: Union[float, None] = None


app = FastAPI()


@app.get("/items/next", response_model=Item)
async def read_next_item():
    return {
        "name": "Island In The Moon",

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()


@app.post("/items/", response_model=Item, tags=["items"])
async def create_item(item: Item):
    return item


@app.get("/items/", tags=["items"])
async def read_items():

from pydantic import BaseModel


class Item(BaseModel):
    id: str
    value: str


app = FastAPI()


@app.get(
    "/items/{item_id}",
    response_model=Item,
    responses={
        200: {
            "content": {"image/png": {}},
            "description": "Return the JSON item or an image.",
        }
    },
)
async def read_item(item_id: str, img: bool | None = None):
    if img:

from typing import Union

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.post(
    "/items/",
    response_model=Item,
    summary="Create an item",

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.