pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

app = FastAPI()


def verify_password(plain_password, hashed_password):
    return pwd_context.verify(plain_password, hashed_password)


def get_password_hash(password):
    return pwd_context.hash(password)


def get_user(db, username: str):
    if username in db:

pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

app = FastAPI()


def verify_password(plain_password, hashed_password):
    return pwd_context.verify(plain_password, hashed_password)


def get_password_hash(password):
    return pwd_context.hash(password)


def get_user(db, username: str):
    if username in db:

!!! tip "팁"
    만약 <a href="https://www.jetbrains.com/pycharm/" class="external-link" target="_blank">PyCharm</a>를 편집기로 사용한다면, <a href="https://github.com/koxudaxi/pydantic-pycharm-plugin/" class="external-link" target="_blank">Pydantic PyCharm Plugin</a>을 사용할 수 있습니다.

    다음 사항을 포함해 Pydantic 모델에 대한 편집기 지원을 향상시킵니다:

    * 자동 완성
    * 타입 확인
    * 리팩토링
    * 검색
    * 점검

## 모델 사용하기

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"

```Python hl_lines="20-37  39-40"
{!../../../docs_src/path_operation_advanced_configuration/tutorial006.py!}
```

👉 🖼, 👥 🚫 📣 🙆 Pydantic 🏷. 👐, 📨 💪 🚫 <abbr title="converted from some plain format, like bytes, into Python objects">🎻</abbr> 🎻, ⚫️ ✍ 🔗 `bytes`, &amp; 🔢 `magic_data_reader()` 🔜 🈚 🎻 ⚫️ 🌌.

👐, 👥 💪 📣 📈 🔗 📨 💪.

### 🛃 🗄 🎚 🆎

    }


@needs_py310
def test_wrong_headers(client: TestClient):
    data = '{"name": "Foo", "price": 50.5}'
    response = client.post(
        "/items/", content=data, headers={"Content-Type": "text/plain"}
    )
    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "model_attributes_type",

        "tax": None,
    }


def test_wrong_headers(client: TestClient):
    data = '{"name": "Foo", "price": 50.5}'
    response = client.post(
        "/items/", content=data, headers={"Content-Type": "text/plain"}
    )
    assert response.status_code == 422, response.text
    assert response.json() == IsDict(
        {
            "detail": [
                {
                    "type": "model_attributes_type",

But if we use the same model for another *path operation*, we could be sending our user's passwords to every client.

!!! danger
    Never store the plain password of a user or send it in a response like this, unless you know all the caveats and you know what you are doing.

## Add an output model

De la même façon, il existe bien d'autres outils compatibles, y compris des outils de génération de code
pour de nombreux langages.

## Pydantic

Toute la validation de données est effectué en arrière-plan avec <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a>,
dont vous bénéficierez de tous les avantages. Vous savez donc que vous êtes entre de bonnes mains.

## L'ordre importe

pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")

app = FastAPI()


def verify_password(plain_password, hashed_password):
    return pwd_context.verify(plain_password, hashed_password)


def get_password_hash(password):
    return pwd_context.hash(password)


def get_user(db, username: str):
    if username in db: