These examples run the server program (e.g Uvicorn), starting **a single process**, listening on all the IPs (`0.0.0.0`) on a predefined port (e.g. `80`).

This is the basic idea. But you will probably want to take care of some additional things, like:

* Security - HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

# Advanced Security

## Additional Features

There are some extra features to handle security apart from the ones covered in the [Tutorial - User Guide: Security](../../tutorial/security/index.md){.internal-link target=_blank}.

!!! tip
    The next sections are **not necessarily "advanced"**.

    And it's possible that for your use case, the solution is in one of them.

## Read the Tutorial first

```

!!! info
    <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">Enumerations (or enums) are available in Python</a> since version 3.4.

!!! tip
    If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

### Declare a *path parameter*

    * 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).

!!! tip
    You might remember that request bodies are also declared with Pydantic models.

    Here **FastAPI** won't get confused because you are using `Depends`.

!!! check
    The way this dependency system is designed allows us to have different dependencies (different "dependables") that all return a `User` model.

    We are not restricted to having only one dependency that can return that type of data.

### What is "Mounting"

"Mounting" means adding a complete "independent" application in a specific path, that then takes care of handling all the sub-paths.

This is different from using an `APIRouter` as a mounted application is completely independent. The OpenAPI and docs from your main application won't include anything from the mounted application, etc.

```Python hl_lines="2  12  15-18"
{!../../../docs_src/app_testing/tutorial001.py!}
```

!!! tip
    Notice that the testing functions are normal `def`, not `async def`.

    And the calls to the client are also normal calls, not using `await`.

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

!!! note "Technical Details"

4. The `Author` dataclass is used as the `response_model` parameter.

5. You can use other standard type annotations with dataclasses as the request body.

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.

    FastAPI is still capable of <abbr title="converting the data to a format that can be transmitted">serializing</abbr> the data to JSON.

        raise fastapi.exceptions.FastAPIError(
            "Invalid args for response field! Hint: "
            f"check that {type_} is a valid Pydantic field type. "
            "If you are using a return type annotation that is not a valid Pydantic "
            "field (e.g. Union[Response, dict, None]) you can disable generating the "
            "response model from the type annotation with the path operation decorator "

    A `Request` also has a `request.receive`, that's a function to "receive" the body of the request.

    The `scope` `dict` and `receive` function are both part of the ASGI specification.

    And those two things, `scope` and `receive`, are what is needed to create a new `Request` instance.