{!> ../../../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。

    * Add support for enumerations in *path operation* parameters. New documentation: [Path Parameters: Predefined values](https://fastapi.tiangolo.com/tutorial/path-params/#predefined-values).

    ```Python hl_lines="8  13"
    {!> ../../../docs_src/dependencies/tutorial006.py!}
    ```

### Return values

And they can return values or not, the values won't be used.

So, you can re-use a normal dependency (that returns a value) you already use somewhere else, and even though the value won't be used, the dependency will be executed:

=== "Python 3.9+"

    ```Python hl_lines="11  16"

```Python hl_lines="9"
{!../../../docs_src/query_params/tutorial001.py!}
```

The query is the set of key-value pairs that go after the `?` in a URL, separated by `&` characters.

For example, in the URL:

```
http://127.0.0.1:8000/items/?skip=0&limit=10
```

...the query parameters are:

* `skip`: with a value of `0`
* `limit`: with a value of `10`

As they are part of the URL, they are "naturally" strings.

It doesn't return a large `str` containing the data in JSON format (as a string). It returns a Python standard data structure (e.g. a `dict`) with values and sub-values that are all compatible with JSON.

!!! note

## Query parameter list / multiple values

When you define a query parameter explicitly with `Query` you can also declare it to receive a list of values, or said in other way, to receive multiple values.

For example, to declare a query parameter `q` that can appear multiple times in the URL, you can write:

=== "Python 3.10+"

## Bodies of arbitrary `dict`s

You can also declare a body as a `dict` with keys of some type and values of some other type.

This way, you don't have to know beforehand what the valid field/attribute names are (as would be the case with Pydantic models).

    'full_name': None,
}
```

#### Unwrapping a `dict`

If we take a `dict` like `user_dict` and pass it to a function (or class) with `**user_dict`, Python will "unwrap" it. It will pass the keys and values of the `user_dict` directly as key-value arguments.

So, continuing with the `user_dict` from above, writing:

```Python
UserInDB(**user_dict)
```

would result in something equivalent to:

```Python
UserInDB(

    "name": "Mary",
    "joined": "2018-11-30",
}

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

!!! info
    `**second_user_data` means:

    Pass the keys and values of the `second_user_data` dict directly as key-value arguments, equivalent to: `User(id=4, name="Mary", joined="2018-11-30")`

### Editor support

    ```

🚥 👆 🔗 ⏮️ 👈 *➡ 🛠️* 📨 2️⃣ 🇺🇸🔍 🎚 💖:

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

📨 🔜 💖:

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

## 🌃

📣 🎚 ⏮️ `Header`, ⚙️ 🎏 ⚠ ⚓ `Query`, `Path` & `Cookie`.