* **Robuste** : Obtenez un code prêt pour la production. Avec une documentation interactive automatique.

Então o caixa diz que "seus hambúrgueres estão prontos" colocando seu número no balcão, mas você não corre que nem um maluco imediatamente quando o número exibido é o seu. Você sabe que ninguém irá roubar seus hambúrgueres porquê você tem o número de chamada, e os outros tem os números deles.

# Primeros pasos

Un archivo muy simple de FastAPI podría verse así:

```Python
{!../../../docs_src/first_steps/tutorial001.py!}
```

Copia eso a un archivo `main.py`.

Corre el servidor en vivo:

<div class="termy">

```console
$ uvicorn main:app --reload

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)

process** (e.g. a Uvicorn process running your FastAPI application). They would all be **identical containers**, running the same thing, but each with its own process, memory, etc. That way you would take advantage of **parallelization** in **different cores** of the CPU, or even in **different machines**.

And the distributed container system with the **load balancer** would **distribute the requests** to each one of the containers with your app **in turns**. So, each request could be handled...

Und Abhängigkeiten können auf sehr einfache und intuitive Weise erstellt werden, sodass Sie einfach die benötigten Python-Packages importieren und sie in wenigen Codezeilen, *im wahrsten Sinne des Wortes*, mit Ihren API-Funktionen integrieren.

Beispiele hierfür finden Sie in den nächsten Kapiteln zu relationalen und NoSQL-Datenbanken, Sicherheit usw.

## **FastAPI**-Kompatibilität

```
./bin/spark-submit --class org.apache.spark.examples.SparkPi \
    --master yarn-client \
    --num-executors 1 \
    --driver-memory 512m \
    --executor-memory 512m \
    --executor-cores 1 \
    examples/jars/spark-examples*.jar 10
```

The job should produce an output as shown below. Note the value of pi in the output.

```

### Multiple Processes - Workers

If you have more clients than what a single process can handle (for example if the virtual machine is not too big) and you have **multiple cores** in the server's CPU, then you could have **multiple processes** running with the same application at the same time, and distribute all the requests among them.

`max_sleep` to a *lower* value and setting `max_io` to a *higher* value would make heal go faster.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/ heal...

### Autres formes de code asynchrone

L'utilisation d'`async` et `await` est relativement nouvelle dans ce langage.

Mais cela rend la programmation asynchrone bien plus simple.

</a>
</p>

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**Dokumentáció**: <a href="https://fastapi.tiangolo.com" target="_blank">https://fastapi.tiangolo.com</a>

**Forrás kód**: <a href="https://github.com/tiangolo/fastapi" target="_blank">https://github.com/tiangolo/fastapi</a>

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