# Templates

You can use any template engine you want with **FastAPI**.

A common choice is Jinja2, the same one used by Flask and other tools.

There are utilities to configure it easily that you can use directly in your **FastAPI** application (provided by Starlette).

## Install dependencies

Install `jinja2`:

<div class="termy">

```console
$ pip install jinja2

---> 100%
```

</div>

</blockquote>

## Recherche

En utilisant toutes les alternatives précédentes, j'ai eu la chance d'apprendre de toutes, de prendre des idées, et de les combiner de la meilleure façon que j'ai pu trouver pour moi-même et les équipes de développeurs avec lesquelles j'ai travaillé.

Par exemple, il était clair que l'idéal était de se baser sur les annotations de type Python standard.

* **Facile**: Progettato per essere facile da usare e imparare. Si riduce il tempo da dedicare alla lettura della documentazione.
* **Sintentico**: Minimizza la duplicazione di codice. Molteplici funzionalità, ognuna con la propria dichiarazione dei parametri. Meno errori.
* **Robusto**: Crea codice pronto per la produzione con documentazione automatica interattiva.

Then, when it's your turn, you do actual "productive" work, you process the menu, decide what you want, get your crush's choice, pay, check that you give the correct bill or card, check that you are charged correctly, check that the order has the correct items, etc.

Vous verrez quelque chose comme :

```JSON
{"item_id": 5, "q": "somequery"}
```

## Documentation interactive de l'API

Donc, pendant ce temps, l'ordinateur pourra effectuer d'autres tâches, pendant que "fichier-lent" 📝 se termine.

    Mas `open()` não usa `async` e `await`.

    Então, nós declaramos uma função de manipulação de evento com o padrão `def` ao invés de `async def`.

### `startup` e `shutdown` juntos

Há uma grande chance que a lógica para sua *inicialização* e *encerramento* esteja conectada, você pode querer iniciar alguma coisa e então finalizá-la, adquirir um recurso e então liberá-lo, etc.

---

**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.

In this case, it would be better to get **one extra server** and run some processes on it so that they all have **enough RAM and CPU time**.

There's also the chance that for some reason you have a **spike** of usage of your API. Maybe it went viral, or maybe some other services or bots start using it. And you might want to have extra resources to be safe in those cases.

As Python advances, **newer versions** come with improved support for these type annotations and in many cases you won't even need to import and use the `typing` module to declare the type annotations.

If you can choose a more recent version of Python for your project, you will be able to take advantage of that extra simplicity.

In all the docs there are examples compatible with each version of Python (when there's a difference).