given-names: Sherry
  - family-names: Murray
    given-names: Derek
  - family-names: Olah
    given-names: Chris
  - family-names: Shlens
    given-names: Jonathon
  - family-names: Steiner
    given-names: Benoit
  - family-names: Sutskever
    given-names: Ilya
  - family-names: Talwar
    given-names: Kunal
  - family-names: Tucker
    given-names: Paul
  - family-names: Vanhoucke
    given-names: Vincent

## Installation

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

Vous aurez également besoin d'un serveur ASGI pour la production tel que <a href="https://www.uvicorn.org" class="external-link" target="_blank">Uvicorn</a> ou <a href="https://github.com/pgjones/hypercorn" class="external-link" target="_blank">Hypercorn</a>.

* Utilisez les mêmes exemples en Python et ne traduisez que le texte des documents. Vous n'avez pas besoin de changer quoi que ce soit pour que cela fonctionne.

* Utilisez les mêmes images, noms de fichiers et liens. Vous n'avez pas besoin de changer quoi que ce soit pour que cela fonctionne.

## Avertissement

# Configuration avancée des paramètres de chemin

## ID d'opération OpenAPI

!!! warning "Attention"
    Si vous n'êtes pas un "expert" en OpenAPI, vous n'en avez probablement pas besoin.

## Entwicklung

Als ich mit der Erstellung von **FastAPI** selbst begann, waren die meisten Teile bereits vorhanden, das Design definiert, die Anforderungen und Tools bereit und das Wissen über die Standards und Spezifikationen klar und frisch.

## Zukunft

Zu diesem Zeitpunkt ist bereits klar, dass **FastAPI** mit seinen Ideen für viele Menschen nützlich ist.

 * instance for non-daemon threads.
 *
 * The task runner is also responsible for releasing held threads when the library is unloaded.
 * This is for the benefit of container environments that implement code unloading.
 *
 * Most applications should share a process-wide [TaskRunner] and use queues for per-client work.
 */
class TaskRunner(
  val backend: Backend,

 * * `Response.body().source().close()`
 * * `Response.body().charStream().close()`
 * * `Response.body().byteStream().close()`
 * * `Response.body().bytes()`
 * * `Response.body().string()`
 *
 * There is no benefit to invoking multiple `close()` methods for the same response body.
 *
 * For synchronous calls, the easiest way to make sure a response body is closed is with a `try`

    Also, there might be tools that expect and use it (now or in the future) and that might be useful for you or your users, now or in the future.

    That's the benefit of standards...

## See it in action

Open the interactive docs: <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>.

### Authenticate

*   When you contribute a new feature to TensorFlow, the maintenance burden is
    (by default) transferred to the TensorFlow team. This means that the benefit
    of the contribution must be compared against the cost of maintaining the
    feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in