@pytest.mark.parametrize(
    "path,headers,expected_status,expected_response",
    [
        ("/items", None, 200, {"X-Token values": None}),
        ("/items", {"x-token": "foo"}, 200, {"X-Token values": ["foo"]}),
        (
            "/items",
            [("x-token", "foo"), ("x-token", "bar")],
            200,
            {"X-Token values": ["foo", "bar"]},
        ),
    ],
)
def test(path, headers, expected_status, expected_response):

{!../../../docs_src/path_params/tutorial005.py!}
```

#### Get the *enumeration value*

You can get the actual value (a `str` in this case) using `model_name.value`, or in general, `your_enum_member.value`:

```Python hl_lines="20"
{!../../../docs_src/path_params/tutorial005.py!}
```

!!! tip
    You could also access the value `"lenet"` with `ModelName.lenet.value`.

#### Return *enumeration members*

def deep_dict_update(main_dict: Dict[Any, Any], update_dict: Dict[Any, Any]) -> None:
    for key, value in update_dict.items():
        if (
            key in main_dict
            and isinstance(main_dict[key], dict)
            and isinstance(value, dict)
        ):
            deep_dict_update(main_dict[key], value)
        elif (
            key in main_dict
            and isinstance(main_dict[key], list)

### `dict` unpacking

If you are not familiar with the `UserInDB(**result.value)`, <a href="https://docs.python.org/3/glossary.html#term-argument" class="external-link" target="_blank">it is using `dict` "unpacking"</a>.

It will take the `dict` at `result.value`, and take each of its keys and values and pass them as key-values to `UserInDB` as keyword arguments.

So, if the `dict` contains:

```Python
{

    {!> ../../../docs_src/header_params/tutorial003.py!}
    ```

与*路径操作*通信时，以下面的方式发送两个 HTTP 请求头：

```
X-Token: foo
X-Token: bar
```

响应结果是：

```JSON
{
    "X-Token values": [
        "bar",
        "foo"
    ]
}
```

## 小结

使用 `Header` 声明请求头的方式与 `Query`、`Path` 、`Cookie` 相同。

        * In requests, a list will be read, eliminating duplicates and converting it to a `set`.
        * In responses, the `set` will be converted to a `list`.
        * The generated schema will specify that the `set` values are unique (using JSON Schema's `uniqueItems`).
* `bytes`:
    * Standard Python `bytes`.
    * In requests and responses will be treated as `str`.
    * The generated schema will specify that it's a `str` with `binary` "format".

    ```

Wenn Sie mit einer *Pfadoperation* kommunizieren, die zwei HTTP-Header sendet, wie:

```
X-Token: foo
X-Token: bar
```

Dann wäre die Response:

```JSON
{
    "X-Token values": [
        "bar",
        "foo"
    ]
}
```

## Zusammenfassung

Deklarieren Sie Header mittels `Header`, auf die gleiche Weise wie bei `Query`, `Path` und `Cookie`.

* Retrieve the stored data.
* Put that data in a Pydantic model.
* Generate a `dict` without default values from the input model (using `exclude_unset`).
    * This way you can update only the values actually set by the user, instead of overriding values already stored with default values in your model.
* Create a copy of the stored model, updating it's attributes with the received partial updates (using the `update` parameter).

!!! note
    FastAPI will know that the value of `q` is not required because of the default value `= None`.

    The `Union` in `Union[str, None]` is not used by FastAPI, but will allow your editor to give you better support and detect errors.

## Without Pydantic

  pull_request:
    types:
      - opened
      - synchronize
jobs:
  changes:
    runs-on: ubuntu-latest
    # Required permissions
    permissions:
      pull-requests: read
    # Set job outputs to values from filter step
    outputs:
      docs: ${{ steps.filter.outputs.docs }}
    steps:
    - uses: actions/checkout@v4
    # For pull requests it's not necessary to checkout the code but for master it is