As part of that, I needed to investigate, test and use many alternatives.

The history of **FastAPI** is in great part the history of its predecessors.

As said in the section [Alternatives](alternatives.md){.internal-link target=_blank}:

<blockquote markdown="1">

**FastAPI** wouldn't exist if not for the previous work of others.

* **Run as a server** (at least during the certificate acquisition process) on the public IP address associated with the domain.
    * As we said above, only one process can be listening on a specific IP and port.
    * This is one of the reasons why it's very useful when the same TLS Termination Proxy also takes care of the certificate renewal process.

## Query parameter list / multiple values { #query-parameter-list-multiple-values }

When you define a query parameter explicitly with `Query` you can also declare it to receive a list of values, or said in another way, to receive multiple values.

For example, to declare a query parameter `q` that can appear multiple times in the URL, you can write:

Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable.

That's why, as said in the official website:

> Requests is one of the most downloaded Python packages of all time

The way you use it is very simple. For example, to do a `GET` request, you would write:

```Python

It could be just one or two lines of code, like:

```Python
callback_url = "https://example.com/api/v1/invoices/events/"
httpx.post(callback_url, json={"description": "Invoice paid", "paid": True})
```

Depois, ele 🤖 pega a primeira tarefa para finalizar (vamos dizer, nosso "arquivo lento" 📝) e continua o que tem que fazer com ela.

Esse "esperar por algo" normalmente se refere a operações <abbr title="Entrada e Saída">I/O</abbr> que são relativamente "lentas" (comparadas à velocidade do processador e da memória RAM), como esperar por:

* dados do cliente para serem enviados através da rede

```Python hl_lines="2"
# Ceci n'est pas asynchrone
def get_sequential_burgers(number: int):
    # Opérations asynchrones pour créer les burgers
    return burgers
```

Avec `async def`, Python sait que dans cette fonction il doit prendre en compte les expressions `await`, et qu'il peut mettre en pause ⏸ l'exécution de la fonction pour aller faire autre chose 🔀 avant de revenir.

<div class="termy">

```console
$ openssl rand -hex 32

09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7
```

</div>

E copie a saída para a variável `SECRET_KEY` (não use a do exemplo).

Crie uma variável `ALGORITHM` com o algoritmo usado para assinar o token JWT e defina como `"HS256"`.

Crie uma variável para a expiração do token.

			<groupId>org.codelibs</groupId>
			<artifactId>corelib</artifactId>
			<version>${corelib.version}</version>
		</dependency>
		<dependency>
			<groupId>org.codelibs</groupId>
			<artifactId>sai</artifactId>
			<version>${sai.version}</version>
		</dependency>
		<dependency>
			<groupId>org.codelibs</groupId>
			<artifactId>xpp3</artifactId>
			<version>1.1.4c.0</version>
		</dependency>
		<dependency>

---

"_We adopted the **FastAPI** library to spawn a **REST** server that can be queried to obtain **predictions**. [for Ludwig]_"

<div style="text-align: right; margin-right: 10%;">Piero Molino, Yaroslav Dudin, and Sai Sumanth Miryala - <strong>Uber</strong> <a href="https://eng.uber.com/ludwig-v0-2/" target="_blank"><small>(ref)</small></a></div>

---