And it shows their true commitment to FastAPI and its **community** (you), as they not only want to provide you a **good service** but also want to make sure you have a **good and healthy framework**, FastAPI. 🙇

For example, you might want to try <a href="https://speakeasyapi.dev/?utm_source=fastapi+repo&utm_medium=github+sponsorship" class="external-link" target="_blank">Speakeasy</a>.

    * So, by using FastAPI you are saving development time, bugs, lines of code, and you would probably get the same performance (or better) you would if you didn't use it (as you would have to implement it all in your code).

    That way you tell the editor that you are intentionally returning anything. But FastAPI will still do the data documentation, validation, filtering, etc. with the `response_model`.

### `response_model` Priority

If you declare both a return type and a `response_model`, the `response_model` will take priority and be used by FastAPI.

    This allows you to use `pytest` directly without complications.

!!! note "Technical Details"
    You could also use `from starlette.testclient import TestClient`.

    **FastAPI** provides the same `starlette.testclient` as `fastapi.testclient` just as a convenience for you, the developer. But it comes directly from Starlette.

!!! tip

```

</div>

### Check the responses

Now, if you go to the URL with the port for Uvicorn: <a href="http://127.0.0.1:8000/app" class="external-link" target="_blank">http://127.0.0.1:8000/app</a>, you will see the normal response:

```JSON
{
    "message": "Hello World",
    "root_path": "/api/v1"
}
```

!!! tip

## Dataclasses in Nested Data Structures

You can also combine `dataclasses` with other type annotations to make nested data structures.

In some cases, you might still have to use Pydantic's version of `dataclasses`. For example, if you have errors with the automatically generated API documentation.

# `Request` class

You can declare a parameter in a *path operation function* or dependency to be of type `Request` and then you can access the raw request object directly, without any validation, etc.

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

!!! tip

# Background Tasks - `BackgroundTasks`

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

## Running on Startup

In most cases, when you create a web API, you want it to be **always running**, uninterrupted, so that your clients can always access it. This is of course, unless you have a specific reason why you want it to run only in certain situations, but most of the time you want it constantly running and **available**.

### In a Remote Server

### Edit it

It's a very simple program.

But now imagine that you were writing it from scratch.

At some point you would have started the definition of the function, you had the parameters ready...

But then you have to call "that method that converts the first letter to upper case".

Was it `upper`? Was it `uppercase`? `first_uppercase`? `capitalize`?

Then, you try with the old programmer's friend, editor autocompletion.