systems is data "<abbr title="also called marshalling, conversion">serialization</abbr>" which is taking data from the code (Python) and converting it into something that can be sent through the network. For example, converting an object containing data from a database into a JSON object. Converting `datetime` objects into strings, etc.

Another big feature needed by APIs is data validation, making sure that the data is valid, given certain parameters. For example, that some field is an `int`,...

!!! info
    Keep in mind that dataclasses can't do everything Pydantic models can do.

    So, you might still need to use Pydantic models.

    But if you have a bunch of dataclasses laying around, this is a nice trick to use them to power a web API using FastAPI. 🤓

## Dataclasses in `response_model`

You can also use `dataclasses` in the `response_model` parameter:

```Python hl_lines="1  7-13  19"

* Systemd
* Supervisor
* Handled internally by a cloud provider as part of their services
* Others...

I'll give you more concrete examples in the next chapters.

## Restarts

Similar to making sure your application is run on startup, you probably also want to make sure it is **restarted** after failures.

### We Make Mistakes

* Allow having empty paths in *path operations* used with `include_router` and a `prefix`.
    * This allows having a router for `/cats` and all its *path operations*, while having one of them for `/cats`.
    * Now it doesn't have to be only `/cats/` (with a trailing slash).

Those two tasks are what **consume time the most**. That's the main work of maintaining FastAPI.

If you can help me with that, **you are helping me maintain FastAPI** and making sure it keeps **advancing faster and better**. 🚀

## Join the chat

# Full Stack FastAPI Template

Templates, while typically come with a specific setup, are designed to be flexible and customizable. This allows you to modify and adapt them to your project's requirements, making them an excellent starting point. 🏁

You can use this template to get started, as it includes a lot of the initial set up, security, database and some API endpoints already done for you.

But at some point, there was no other option than creating something that provided all these features, taking the best ideas from previous tools, and combining them in the best way possible, using language features that weren't even available before (Python 3.6+ type hints).

</blockquote>

## Investigation

You can write <a href="https://en.wikipedia.org/wiki/Markdown" class="external-link" target="_blank">Markdown</a> in the docstring, it will be interpreted and displayed correctly (taking into account docstring indentation).

=== "Python 3.10+"

    ```Python hl_lines="17-25"
    {!> ../../../docs_src/path_operation_configuration/tutorial004_py310.py!}
    ```

=== "Python 3.9+"

```Python
callback_url = "https://example.com/api/v1/invoices/events/"
httpx.post(callback_url, json={"description": "Invoice paid", "paid": True})
```

But possibly the most important part of the callback is making sure that your API user (the external developer) implements the *external API* correctly, according to the data that *your API* is going to send in the request body of the callback, etc.

* Təhlükəsizlik və autentifikasiya, **JWT tokenləri** ilə **OAuth2** dəstəyi və **HTTP Basic** autentifikasiyası.
* **çox dərin JSON modellərini** müəyyən etmək üçün daha irəli səviyyə (lakin eyni dərəcədə asan) üsullar (Pydantic sayəsində).
* <a href="https://strawberry.rocks" class="external-link" target="_blank">Strawberry</a> və digər kitabxanalar ilə **GraphQL** inteqrasiyası.