У Pydantic-моделей есть метод `.model_dump()`, который возвращает `dict` с данными модели.

Поэтому, если мы создадим Pydantic-объект `user_in` таким способом:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

и затем вызовем:

```Python
user_dict = user_in.model_dump()
```

Os modelos Pydantic possuem um método `.model_dump()` que retorna um `dict` com os dados do modelo.

Então, se criarmos um objeto Pydantic `user_in` como:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

e depois chamarmos:

```Python
user_dict = user_in.model_dump()
```

    email: str | None = None
    full_name: str | None = None
    disabled: bool | None = None


def fake_decode_token(token):
    return User(
        username=token + "fakedecoded", email="john@example.com", full_name="John Doe"
    )


async def get_current_user(token: str = Depends(oauth2_scheme)):
    user = fake_decode_token(token)
    return user


@app.get("/users/me")

    email: str | None = None
    full_name: str | None = None
    disabled: bool | None = None


def fake_decode_token(token):
    return User(
        username=token + "fakedecoded", email="john@example.com", full_name="John Doe"
    )


async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)]):
    user = fake_decode_token(token)
    return user


@app.get("/users/me")

Wenn wir also ein Pydantic-Objekt `user_in` erstellen, etwa so:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

und dann aufrufen:

```Python
user_dict = user_in.model_dump()
```

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

接著呼叫：

```Python
user_dict = user_in.model_dump()
```

此時變數 `user_dict` 會是一個承載資料的 `dict`（也就是 `dict`，而非 Pydantic 模型物件）。

若再呼叫：

```Python
print(user_dict)
```

我們會得到一個 Python `dict`：

```Python
{
    'username': 'john',
    'password': 'secret',

client = TestClient(app)


def test_security_http_basic():
    response = client.get("/users/me", auth=("john", "secret"))
    assert response.status_code == 200, response.text
    assert response.json() == {"username": "john", "password": "secret"}


def test_security_http_basic_no_credentials():
    response = client.get("/users/me")

`user_in`은 Pydantic 모델 클래스인 `UserIn`입니다.

Pydantic 모델은 모델 데이터를 포함한 `dict`를 반환하는 `.model_dump()` 메서드를 제공합니다.

따라서, 다음과 같이 Pydantic 객체 `user_in`을 생성할 수 있습니다:

```Python
user_in = UserIn(username="john", password="secret", email="john******@****.***")
```

그 다음, 다음과 같이 호출합니다:

```Python
user_dict = user_in.model_dump()
```

이제 변수 `user_dict`에 데이터가 포함된 `dict`를 가지게 됩니다(이는 Pydantic 모델 객체가 아닌 `dict`입니다).

client = TestClient(app)


def test_security_http_basic():
    response = client.get("/users/me", auth=("john", "secret"))
    assert response.status_code == 200, response.text
    assert response.json() == {"username": "john", "password": "secret"}


def test_security_http_basic_no_credentials():
    response = client.get("/users/me")

        final String jwtClaim = "{\"sub\":\"user123\",\"name\":\"John Doe\",\"email\":\"john@example.com\"}";
        final Map<String, Object> attributes = new HashMap<>();

        authenticator.parseJwtClaim(jwtClaim, attributes);

        assertEquals("user123", attributes.get("sub"));
        assertEquals("John Doe", attributes.get("name"));
        assertEquals("john@example.com", attributes.get("email"));
    }

    @Test