So, even with the code above that doesn't use Pydantic explicitly, FastAPI is using Pydantic to convert those standard dataclasses to Pydantic's own flavor of dataclasses.

And of course, it supports the same:

* data validation
* data serialization
* data documentation, etc.

from typing import Annotated

from fastapi import FastAPI, Header

app = FastAPI()


@app.get("/items/")
async def read_items(
    strange_header: Annotated[str | None, Header(convert_underscores=False)] = None,
):

        deprecated: Union[deprecated, str, bool, None] = None,
        include_in_schema: bool = True,
        json_schema_extra: Union[Dict[str, Any], None] = None,
        **extra: Any,
    ):
        self.convert_underscores = convert_underscores
        super().__init__(
            default=default,
            default_factory=default_factory,
            annotation=annotation,
            alias=alias,

            fields will be ignored at serialization time.
            """
        ),
    ] = None,
    convert_underscores: Annotated[
        bool,
        Doc(
            """
            Automatically convert underscores to hyphens in the parameter field name.

            Read more about it in the

因此，默认情况下，`Header` 把参数名中的字符由下划线（`_`）改为连字符（`-`）来提取并存档请求头 。

同时，HTTP 的请求头不区分大小写，可以使用 Python 标准样式（即 **snake_case**）进行声明。

因此，可以像在 Python 代码中一样使用 `user_agent` ，无需把首字母大写为 `User_Agent` 等形式。

如需禁用下划线自动转换为连字符，可以把 `Header` 的 `convert_underscores` 参数设置为 `False`：

=== "Python 3.10+"

    ```Python hl_lines="10"
    {!> ../../../docs_src/header_params/tutorial002_an_py310.py!}
    ```

=== "Python 3.9+"

FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration.

!!! tip
    If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

```

Because the editor knows the types of the variables, you don't only get completion, you also get error checks:

<img src="/img/python-types/image04.png">

Now you know that you have to fix it, convert `age` to a string with `str(age)`:

```Python hl_lines="2"
{!../../../docs_src/python_types/tutorial004.py!}
```

## Declaring types

The only thing the function returned by `GzipRequest.get_route_handler` does differently is convert the `Request` to a `GzipRequest`.

Doing this, our `GzipRequest` will take care of decompressing the data (if necessary) before passing it to our *path operations*.

After that, all of the processing logic is the same.

from fastapi import FastAPI, Header

app = FastAPI()


@app.get("/items/")
async def read_items(
    strange_header: str | None = Header(default=None, convert_underscores=False),
):

But if the data didn't exist, you want to create it, and return an HTTP status code of "CREATED" `201`.

But you still want to be able to filter and convert the data you return with a `response_model`.

For those cases, you can use a `Response` parameter.

## Use a `Response` parameter