* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.
    * But it provides you the tools to build simple web applications, with routing based on paths, etc.

Routes are declared in a single place, using functions declared in other places (instead of using decorators that can be placed right on top of the function that handles the endpoint). This is closer to how Django does it than to how Flask (and Starlette) does it. It separates in the code things that are relatively tightly coupled.

!!! check "Inspired **FastAPI** to"

* **PGAdmin** für die PostgreSQL-Datenbank, können Sie problemlos ändern, sodass PHPMyAdmin und MySQL verwendet wird.
* **Flower** für die Überwachung von Celery-Jobs.
* Load Balancing zwischen Frontend und Backend mit **Traefik**, sodass Sie beide unter derselben Domain haben können, getrennt durch den Pfad, aber von unterschiedlichen Containern ausgeliefert.

* **PGAdmin** pour les bases de données PostgreSQL, facilement modifiable pour utiliser PHPMYAdmin ou MySQL.
* **Flower** pour la surveillance de tâches Celery.
* Équilibrage de charge entre le frontend et le backend avec **Traefik**, afin de pouvoir avoir les deux sur le même domaine, séparés par chemins, mais servis par différents conteneurs.

---

"_I’m over the moon excited about **FastAPI**. It’s so fun!_"

---

"_I’m over the moon excited about **FastAPI**. It’s so fun!_"

    ```

    </div>

=== "Hypercorn"

    <div class="termy">

    ```console
    $ hypercorn main:app --bind 0.0.0.0:80

    Running on 0.0.0.0:8080 over http (CTRL + C to quit)
    ```

    </div>

!!! note
    The command `uvicorn main:app` refers to:

    * `main`: the file `main.py` (the Python "module").

On the other hand, if you have 2 servers and you are using **100% of their CPU and RAM**, at some point one process will ask for more memory, and the server will have to use the disk as "memory" (which can be thousands of times slower), or even **crash**. Or one process might need to do some computation and would have to wait until the CPU is free again.

participant dep as Dep with yield
participant operation as Path Operation
participant tasks as Background tasks

    Note over client,tasks: Can raise exception for dependency, handled after response is sent
    Note over client,operation: Can raise HTTPException and can change the response
    client ->> dep: Start request
    Note over dep: Run code up to yield
    opt raise
        dep -->> handler: Raise HTTPException

=== "Python 3.8+"

    ```Python hl_lines="20-21"
    {!> ../../../docs_src/path_operation_configuration/tutorial003.py!}
    ```

## Description from docstring