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`,...

* 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

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

* 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.

But now, having `Query(max_length=50)` inside of `Annotated`, we are telling FastAPI that we want it to extract this value from the query parameters (this would have been the default anyway 🤷) and that we want to have **additional validation** for this value (that's why we do this, to get the additional validation). 😎

FastAPI will now:

* **Validate** the data making sure that the max length is 50 characters

---

Imagine you are the computer / program 🤖 in that story.

While you are at the line, you are just idle 😴, waiting for your turn, not doing anything very "productive". But the line is fast because the cashier is only taking the orders (not preparing them), so that's fine.

Instead of, for example, a `dict`, or something else, as it could break the application at some point later, making it a security risk.

We also verify that we have a user with that username, and if not, we raise that same exception we created before.

=== "Python 3.10+"

    ```Python hl_lines="46  116-127"

Having another process manager inside the container (as would be with Gunicorn or Uvicorn managing Uvicorn workers) would only add **unnecessary complexity** that you are most probably already taking care of with your cluster system.

### Containers with Multiple Processes and Special Cases

                exclude_defaults=exclude_defaults,
                exclude_none=exclude_none,
            )

        def __hash__(self) -> int:
            # Each ModelField is unique for our purposes, to allow making a dict from
            # ModelField to its JSON Schema.
            return id(self)

    def get_annotation_from_field_info(
        annotation: Any, field_info: FieldInfo, field_name: str
    ) -> Any: