* `datetime.timedelta`:
    * A Python `datetime.timedelta`.
    * In requests and responses will be represented as a `float` of total seconds.
    * Pydantic also allows representing it as a "ISO 8601 time diff encoding", <a href="https://docs.pydantic.dev/latest/concepts/serialization/#json_encoders" class="external-link" target="_blank">see the docs for more info</a>.

```Python
old_dict = {
    "old key": "old value",
    "second old key": "second old value",
}
new_dict = {**old_dict, "new key": "new value"}
```

Ici, `new_dict` contiendra toutes les paires clé-valeur de `old_dict` plus la nouvelle paire clé-valeur :

```Python
{
    "old key": "old value",
    "second old key": "second old value",
    "new key": "new value",
}
```

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

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info
    `**second_user_data` nghĩa là:

def test_get_invalid_second_header_items():
    response = client.get(
        "/items/", headers={"X-Token": "fake-super-secret-token", "X-Key": "invalid"}
    )
    assert response.status_code == 400, response.text
    assert response.json() == {"detail": "X-Key header invalid"}


def test_get_invalid_second_header_users():
    response = client.get(

    The HTTP authorization credentials in the result of using `HTTPBearer` or
    `HTTPDigest` in a dependency.

    The HTTP authorization header value is split by the first space.

    The first part is the `scheme`, the second part is the `credentials`.

    For example, in an HTTP Bearer token scheme, the client will send a header
    like:

    ```
    Authorization: Bearer deadbeef12346
    ```

    In this case:

Quand vous créez des *fonctions de chemins*, vous pouvez vous retrouver dans une situation où vous avez un chemin fixe.

Tel que `/users/me`, disons pour récupérer les données sur l'utilisateur actuel.

Et vous avez un second chemin : `/users/{user_id}` pour récupérer de la donnée sur un utilisateur spécifique grâce à son identifiant d'utilisateur

    bytes: lambda o: o.decode(),
    Color: str,
    datetime.date: isoformat,
    datetime.datetime: isoformat,
    datetime.time: isoformat,
    datetime.timedelta: lambda td: td.total_seconds(),
    Decimal: decimal_encoder,
    Enum: lambda o: o.value,
    frozenset: list,
    deque: list,
    GeneratorType: list,
    IPv4Address: str,
    IPv4Interface: str,
    IPv4Network: str,

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

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info
    `**second_user_data` bedeutet:

```

これは以下のように用いられます:

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

second_user_data = {
    "id": 4,
    "name": "Mary",
    "joined": "2018-11-30",
}

my_second_user: User = User(**second_user_data)
```

!!! info "情報"
    `**second_user_data` は以下を意味します：

    `second_user_data`辞書のキーと値を直接、キーと値の引数として渡します。これは、`User(id=4, name="Mary", joined="2018-11-30")`と同等です。

### エディタのサポート

```Python
from app.routers import items, users
```

!!! info
    The first version is a "relative import":

    ```Python
    from .routers import items, users
    ```

    The second version is an "absolute import":

    ```Python
    from app.routers import items, users
    ```