在你的 *路径操作函数* 里，用 `.add_task()` 方法将任务函数传到 *后台任务* 对象中：

{* ../../docs_src/background_tasks/tutorial001_py310.py hl[14] *}

`.add_task()` 接收以下参数：

* 在后台运行的任务函数(`write_notification`)。
* 应按顺序传递给任务函数的任意参数序列(`email`)。
* 应传递给任务函数的任意关键字参数(`message="some notification"`)。

## 依赖注入 { #dependency-injection }

使用 `BackgroundTasks` 也适用于依赖注入系统，你可以在多个级别声明 `BackgroundTasks` 类型的参数：在 *路径操作函数* 里，在依赖中(可依赖)，在子依赖中，等等。

    version="0.0.1",
    terms_of_service="http://example.com/terms/",
    contact={
        "name": "Deadpoolio the Amazing",
        "url": "http://x-force.example.com/contact/",
        "email": "******@****.***",
    },
    license_info={
        "name": "Apache 2.0",
        "identifier": "Apache-2.0",
    },
)


@app.get("/items/")
async def read_items():

# -------------------
constraints.CreditCardNumber.message = {item} adalah nomor kartu kredit yang tidak valid.
constraints.EAN.message = {item} adalah barcode {type} yang tidak valid.
constraints.Email.message = {item} bukan alamat email yang valid.
constraints.Length.message = Panjang {item} harus antara {min} dan {max}.
constraints.LuhnCheck.message = Checksum Luhn Modulo 11 dari {value} tidak benar.

/// info

To use `EmailStr`, first install [`email-validator`](https://github.com/JoshData/python-email-validator).

Make sure you create a [virtual environment](../virtual-environments.md), activate it, and then install it, for example:

```console
$ pip install email-validator
```

or with:

```console
$ pip install "pydantic[email]"
```

///

/// info | Informação

Para usar `EmailStr`, primeiro instale [`email-validator`](https://github.com/JoshData/python-email-validator).

Certifique-se de criar um [ambiente virtual](../virtual-environments.md), ative-o e então instale-o, por exemplo:

```console
$ pip install email-validator
```

ou com:

```console
$ pip install "pydantic[email]"
```

///

# Generate CONTRIBUTORS.md: contributors.sh

# Tip for finding duplicates (besides scanning the output of CONTRIBUTORS.md for name
# duplicates that aren't also email duplicates): scan the output of:
#   git log --format='%aE - %aN' | sort -uf
#
# For explanation on this file format: man git-shortlog

Anand Babu (AB) Periasamy <******@****.***> Anand Babu (AB) Periasamy <******@****.***>
Anand Babu (AB) Periasamy <******@****.***> <******@****.***>

            result.setInternationaliSDNNumber(DfTypeUtil.toString(source.get("internationaliSDNNumber")));
            result.setLabeledURI(DfTypeUtil.toString(source.get("labeledURI")));
            result.setMail(DfTypeUtil.toString(source.get("mail")));
            result.setMobile(DfTypeUtil.toString(source.get("mobile")));
            result.setName(DfTypeUtil.toString(source.get("name")));

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


class User(BaseModel):
    username: str
    email: str


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

#### `**user_dict`에 대해 { #about-user-dict }

`UserInDB(**user_dict)`는 다음을 의미한다:

*`user_dict`의 키와 값을 다음과 같은 키-값 인수로 직접 전달합니다:*

```Python
UserInDB(
    username = user_dict["username"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info | 정보

`UserInDB(**user_dict)` signifie :

Passez les clés et valeurs de `user_dict` directement comme arguments clé‑valeur, équivalent à :

```Python
UserInDB(
    username = user_dict["username"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
    disabled = user_dict["disabled"],
    hashed_password = user_dict["hashed_password"],
)
```

/// info