"ctx": {"pattern": "^fixedquery$"},
                    "loc": ["query", "item-query"],
                    "msg": 'string does not match regex "^fixedquery$"',
                    "type": "value_error.str.regex",
                }
            ]
        }
    )


def test_openapi_schema(client: TestClient):
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text

                    "ctx": {"pattern": "^fixedquery$"},
                    "loc": ["query", "item-query"],
                    "msg": 'string does not match regex "^fixedquery$"',
                    "type": "value_error.str.regex",
                }
            ]
        }
    )


@needs_py310
def test_openapi_schema(client: TestClient):
    response = client.get("/openapi.json")

Dazu aktualisieren wir das Pydantic-Modell `TokenData` mit einem neuen Attribut `scopes`.

Durch die Validierung der Daten mit Pydantic können wir sicherstellen, dass wir beispielsweise präzise eine `list`e von `str`s mit den Scopes und einen `str` mit dem `username` haben.

Anstelle beispielsweise eines `dict`s oder etwas anderem, was später in der Anwendung zu Fehlern führen könnte und darum ein Sicherheitsrisiko darstellt.

    @Test
    public void testSubstitution() throws IOException {
        String str = "port = 4141" + LINE_SEPARATOR + "host = localhost"
                + LINE_SEPARATOR + "url = https://${host}:${port}/service"
                + LINE_SEPARATOR;
        MavenProperties properties = new MavenProperties();
        properties.load(new StringReader(str));
        properties.put("url", "https://localhost:4141/service");

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

Sau đó có thể được sử dụng:

```Python

编写带有类型标注的标准 Python：

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```

可以像这样来使用：

```Python
my_user: User = User(id=3, name="John Doe", joined="2018-07-19")

As, by default, singular values are interpreted as query parameters, you don't have to explicitly add a `Query`, you can just do:

```Python
q: Union[str, None] = None
```

Or in Python 3.10 and above:

```Python
q: str | None = None
```

For example:

//// tab | Python 3.10+

```Python hl_lines="28"
{!> ../../docs_src/body_multiple_params/tutorial004_an_py310.py!}
```

Da einfache Werte standardmäßig als Query-Parameter interpretiert werden, müssen Sie `Query` nicht explizit hinzufügen, Sie können einfach schreiben:

```Python
q: Union[str, None] = None
```

Oder in Python 3.10 und darüber:

```Python
q: str | None = None
```

Zum Beispiel:

//// tab | Python 3.10+

```Python hl_lines="27"
{!> ../../docs_src/body_multiple_params/tutorial004_an_py310.py!}
```

}

func (c *Content) Scan(src interface{}) error {
	var value Content
	str, ok := src.(string)
	if !ok {
		byt, ok := src.([]byte)
		if !ok {
			return errors.New("Embedded.Scan byte assertion failed")
		}
		if err := json.Unmarshal(byt, &value); err != nil {
			return err
		}
	} else {
		if err := json.Unmarshal([]byte(str), &value); err != nil {
			return err
		}
	}

	*c = value

### `UploadFile`

`UploadFile` 은 다음과 같은 어트리뷰트가 있습니다:

* `filename` : 문자열(`str`)로 된 업로드된 파일의 파일명입니다 (예: `myimage.jpg`).
* `content_type` : 문자열(`str`)로 된 파일 형식(MIME type / media type)입니다 (예: `image/jpeg`).