## Server Machine and Server Program

There's a small detail about names to keep in mind. 💡

The word "**server**" is commonly used to refer to both the remote/cloud computer (the physical or virtual machine) and also the program that is running on that machine (e.g. Uvicorn).

Just keep in mind that when you read "server" in general, it could refer to one of those two things.

* **Standardmäßig** bedeutet das, dass Sie nur **ein HTTPS-Zertifikat pro IP-Adresse** haben können.
    * Ganz gleich, wie groß Ihr Server ist oder wie klein die einzelnen Anwendungen darauf sind.
    * Hierfür gibt es jedoch eine **Lösung**.

# Exceptions – `HTTPException` und `WebSocketException`

Dies sind die <abbr title="Exception – Ausnahme, Fehler: Python-Objekt, das einen Fehler nebst Metadaten repräsentiert">Exceptions</abbr>, die Sie auslösen können, um dem Client Fehler zu berichten.

    * 이런식으로 구니콘이 import하여 사용할 수 있는 클래스를 전달해줍니다:

        ```Python
        import uvicorn.workers.UvicornWorker
        ```

* `--bind`: 구니콘이 관찰할 IP와 포트를 의미합니다. 콜론 (`:`)을 사용하여 IP와 포트를 구분합니다.
    * 만약에 `--bind 0.0.0.0:80` (구니콘 옵션) 대신 유비콘을 직접 실행하고 싶다면 `--host 0.0.0.0`과 `--port 80`을 사용해야 합니다.

출력에서 각 프로세스에 대한 **PID** (process ID)를 확인할 수 있습니다. (단순한 숫자입니다)

출력 내용:

Given the simplicity of Flask, it seemed like a good match for building APIs. The next thing to find was a "Django REST Framework" for Flask.

!!! check "Inspired **FastAPI** to"
    Be a micro-framework. Making it easy to mix and match the tools and parts needed.

    Have a simple and easy to use routing system.

But when checking benchmarks and comparisons you should keep the following in mind.

## Benchmarks and speed

When you check the benchmarks, it is common to see several tools of different types compared as equivalent.

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

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

    So, you might still need to use Pydantic models.

{!../../../docs_src/behind_a_proxy/tutorial002.py!}
```

Passing the `root_path` to `FastAPI` would be the equivalent of passing the `--root-path` command line option to Uvicorn or Hypercorn.

### About `root_path`

Keep in mind that the server (Uvicorn) won't use that `root_path` for anything else than passing it to the app.

!!! tip "Tipp"
    Wenn Sie den Code zum Dokumentieren eines Callbacks schreiben, kann es hilfreich sein, sich vorzustellen, dass Sie dieser *externe Entwickler* sind. Und dass Sie derzeit die *externe API* implementieren, nicht *Ihre API*.

Several of these are explored in the next chapters of the tutorial.

## Order matters

When creating *path operations*, you can find situations where you have a fixed path.

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.