* **FastAPI**: (uses Starlette) an API microframework with several additional features for building APIs, with data validation, etc.

* **Uvicorn**:
    * Will have the best performance, as it doesn't have much extra code apart from the server itself.

```

</div>

as Uvicorn by default will use the port `8000`, the documentation on port `8008` won't clash.

### Translations

Help with translations is VERY MUCH appreciated! And it can't be done without the help from the community. 🌎 🚀

Here are the steps to help with translations.

#### Tips and guidelines

# Reference - Code API

Here's the reference or code API, the classes, functions, parameters, attributes, and
all the FastAPI parts you can use in your applications.

If you want to **learn FastAPI** you are much better off reading the

    ```Python
    from main import app
    ```

!!! warning
    Uvicorn and others support a `--reload` option that is useful during development.

    The `--reload` option consumes much more resources, is more unstable, etc.

    It helps a lot during **development**, but you **shouldn't** use it in **production**.

## Hypercorn with Trio

Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

How much of the system resources do you want to be consuming/utilizing? It might be easy to think "not much", but in reality, you will probably want to consume **as much as possible without crashing**.

FastAPI does several things internally with Pydantic to make sure that those same rules of class inheritance are not used for the returned data filtering, otherwise you could end up returning much more data than what you expected.

This way, you can get the best of both worlds: type annotations with **tooling support** and **data filtering**.

## See it in the docs

And it generates OpenAPI schemas.

That's how it works in Flask, Starlette, Responder, etc.

But then, we have again the problem of having a micro-syntax, inside of a Python string (a big YAML).

The editor can't help much with that. And if we modify parameters or Marshmallow schemas and forget to also modify that YAML docstring, the generated schema would be obsolete.

!!! info
    APISpec was created by the same Marshmallow developers.

Many packages that simplify it a lot have to make many compromises with the data model, database, and available features. And some of these packages that simplify things too much actually have security flaws underneath.

---

**FastAPI** doesn't make any compromise with any database, data model or tool.

It gives you all the flexibility to choose the ones that fit your project the best.

    assert response.status_code == 200, response.text
    assert response.json() == data


def test_model_with_tuple_invalid():
    data = {"items": [["foo", "bar"], ["baz", "whatelse", "too", "much"]]}
    response = client.post("/model-with-tuple/", json=data)
    assert response.status_code == 422, response.text

    data = {"items": [["foo", "bar"], ["baz"]]}
    response = client.post("/model-with-tuple/", json=data)

Einige der Optionen, die Sie als TLS-Terminierungsproxy verwenden können, sind:

* Traefik (kann auch Zertifikat-Erneuerungen durchführen)
* Caddy (kann auch Zertifikat-Erneuerungen durchführen)
* Nginx
* HAProxy

## Let's Encrypt

Vor Let's Encrypt wurden diese **HTTPS-Zertifikate** von vertrauenswürdigen Dritten verkauft.