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,
    item: Item = Body(
        openapi_examples={
            "normal": {
                "summary": "A normal example",

import java.net.Inet6Address
import java.net.InetAddress
import okhttp3.internal.interleave

/**
 * Implementation of HappyEyeballs Sorting Addresses.
 *
 * The current implementation does not address any of:
 *  - Async DNS split by IP class
 *  - Stateful handling of connectivity results
 *  - The prioritisation of addresses
 *
 * https://datatracker.ietf.org/doc/html/rfc8305#section-4
 */

```

<details markdown="1">
<summary>または <code>async def</code> を使います...</summary>

コードで `async` / `await` を使用する場合は、`async def` を使います。

```Python hl_lines="7  12"
from fastapi import FastAPI

app = FastAPI()


@app.get("/")
async def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
async def read_item(item_id: int, q: str | None = None):

  TFE_DEVICE_PLACEMENT_SILENT_FOR_INT32 = 3,
} TFE_ContextDevicePlacementPolicy;
// LINT.ThenChange(//tensorflow/c/eager/immediate_execution_context.h)

// Sets the default execution mode (sync/async). Note that this can be
// overridden per thread using TFE_ContextSetExecutorForThread.
TF_CAPI_EXPORT extern void TFE_ContextOptionsSetAsync(TFE_ContextOptions*,

```

<details markdown="1">
<summary>또는 <code>async def</code> 사용하기...</summary>

여러분의 코드가 `async` / `await`을 사용한다면, `async def`를 사용하십시오:

```Python hl_lines="7  12"
from fastapi import FastAPI

app = FastAPI()


@app.get("/")
async def read_root():
    return {"Hello": "World"}


@app.get("/items/{item_id}")
async def read_item(item_id: int, q: str | None = None):

    // ThreadLocal is not available to GWT, so we always reuse the same
    // instance.  It is always safe to return the same instance because
    // javascript is single-threaded, and only used by blocks that doesn't
    // involve async callbacks.
    return CHAR_BUFFER;
  }

  private Platform() {}

@dataclass
class Author:
    name: str
    items: list[Item] = field(default_factory=list)  # (3)


app = FastAPI()


@app.post("/authors/{author_id}/items/", response_model=Author)  # (4)
async def create_author_items(author_id: str, items: list[Item]):  # (5)
    return {"name": author_id, "items": items}  # (6)


@app.get("/authors/", response_model=list[Author])  # (7)
def get_authors():  # (8)

    price: float
    tags: list[str] = field(default_factory=list)
    description: str | None = None
    tax: float | None = None


app = FastAPI()


@app.get("/item", response_model=Item)
async def read_item():
    return {
        "id": uuid.uuid4(),
        "name": "Island In The Moon",
        "price": 12.99,
        "description": "A place to be playin' and havin' fun",
        "tags": ["breater"],
    }

app = FastAPI()

oauth2_scheme = OAuth2PasswordBearer(
    tokenUrl="/token",
    description="OAuth2PasswordBearer security scheme",
    auto_error=False,
)


@app.get("/items/")
async def read_items(token: str | None = Security(oauth2_scheme)):
    if token is None:
        return {"msg": "Create an account first"}
    return {"token": token}


client = TestClient(app)


def test_no_token():

**FastAPI** 会创建一个 `BackgroundTasks` 类型的对象并作为该参数传入。

## 创建一个任务函数 { #create-a-task-function }

创建要作为后台任务运行的函数。

它只是一个可以接收参数的标准函数。

它可以是 `async def` 或普通的 `def` 函数，**FastAPI** 知道如何正确处理。

在这种情况下，任务函数将写入一个文件（模拟发送电子邮件）。

由于写操作不使用 `async` 和 `await`，我们用普通的 `def` 定义函数：

{* ../../docs_src/background_tasks/tutorial001_py310.py hl[6:9] *}

## 添加后台任务 { #add-the-background-task }