* 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".
* `Decimal`:
    * Standard Python `Decimal`.

        ]
        fastapi_specific_annotations = [
            arg
            for arg in fastapi_annotations
            if isinstance(arg, (params.Param, params.Body, params.Depends))
        ]
        if fastapi_specific_annotations:
            fastapi_annotation: Union[
                FieldInfo, params.Depends, None
            ] = fastapi_specific_annotations[-1]
        else:

    for an OAuth2 password flow.

    The OAuth2 specification dictates that for a password flow the data should be
    collected using form data (instead of JSON) and that it should have the specific
    fields `username` and `password`.

    All the initialization parameters are extracted from the request.

    Read more about it in the

        Optional[Dict[str, Example]],
        Doc(
            """
            OpenAPI-specific examples.

            It will be added to the generated OpenAPI (e.g. visible at `/docs`).

            Swagger UI (that provides the `/docs` interface) has better support for the
            OpenAPI-specific examples than the JSON Schema `examples`, that's the main
            use case for this.

* `HEAD`
* `PATCH`
* `TRACE`

In the HTTP protocol, you can communicate to each path using one (or more) of these "methods".

---

When building APIs, you normally use these specific HTTP methods to perform a specific action.

Normally you use:

* `POST`: to create data.
* `GET`: to read data.
* `PUT`: to update data.
* `DELETE`: to delete data.

You can combine `dataclasses` with other type annotations in many different combinations to form complex data structures.

Check the in-code annotation tips above to see more specific details.

## Learn More

You can also combine `dataclasses` with other Pydantic models, inherit from them, include them in your own models, etc.

Like `/users/me`, let's say that it's to get data about the current user.

And then you can also have a path `/users/{user_id}` to get data about a specific user by some user ID.

Because *path operations* are evaluated in order, you need to make sure that the path for `/users/me` is declared before the one for `/users/{user_id}`:

```Python hl_lines="6  11"

    ---> 100%
    ```

    </div>

    ...or any other ASGI server.

## Run the Server Program

If you installed an ASGI server manually, you would normally need to pass an import string in a special format for it to import your FastAPI application:

=== "Uvicorn"

    <div class="termy">

    ```console
    $ uvicorn main:app --host 0.0.0.0 --port 80

In these cases you can use `root_path` to configure your application.

The `root_path` is a mechanism provided by the ASGI specification (that FastAPI is built on, through Starlette).

The `root_path` is used to handle these specific cases.

And it's also used internally when mounting sub-applications.

## Proxy with a stripped path prefix

But it was created before there existed Python type hints. So, to define every <abbr title="the definition of how data should be formed">schema</abbr> you need to use specific utils and classes provided by Marshmallow.

!!! check "Inspired **FastAPI** to"
    Use code to define "schemas" that provide data types and validation, automatically.