En particulier, on voit Uvicorn, Starlette et FastAPI comparés (parmi de nombreux autres outils).

Plus le problème résolu par un outil est simple, mieux seront les performances obtenues. Et la plupart des tests de performance ne prennent pas en compte les fonctionnalités additionnelles fournies par les outils.

La hiérarchie est la suivante :

* **Uvicorn** : un serveur ASGI

        return new CurlRequest(Method.GET, url);
    }

    /**
     * Creates a new CurlRequest with the HTTP POST method for the specified URL.
     *
     * @param url the URL to which the POST request will be sent
     * @return a new CurlRequest object configured with the POST method and the specified URL
     */
    public static CurlRequest post(final String url) {
        return new CurlRequest(Method.POST, url);
    }

async def create_file(file: bytes | None = File(default=None)):
    if not file:
        return {"message": "No file sent"}
    else:
        return {"file_size": len(file)}


@app.post("/uploadfile/")
async def create_upload_file(file: UploadFile | None = None):
    if not file:
        return {"message": "No upload file sent"}
    else:

    if not file:
        return {"message": "No file sent"}
    else:
        return {"file_size": len(file)}


@app.post("/uploadfile/")
async def create_upload_file(file: Union[UploadFile, None] = None):
    if not file:
        return {"message": "No upload file sent"}
    else:

 *    either peer may not have been transmitted to the other.
 *
 * Note that the state progression is independent for each peer. Arriving at a gracefully-closed
 * state indicates that a peer has sent all of its outgoing messages and received all of its
 * incoming messages. But it does not guarantee that the other peer will successfully receive all of
 * its incoming messages.
 */
interface WebSocket {

from fastapi import Depends, FastAPI

app = FastAPI()


def get_username():
    try:
        yield "Rick"
    finally:
        print("Cleanup up before response is sent")


@app.get("/users/me")
def get_user_me(username: str = Depends(get_username, scope="function")):

Using `Depends(scope="function")`, the exit code after `yield` is executed right after the *path operation function* is finished, before the response is sent back to the client.

And when using `Depends(scope="request")` (the default), the exit code after `yield` is executed after the response is sent.

En héritant de `str` la documentation sera capable de savoir que les valeurs doivent être de type `string` et pourra donc afficher cette `Enum` correctement.

Créez ensuite des attributs de classe avec des valeurs fixes, qui seront les valeurs autorisées pour cette énumération.

{* ../../docs_src/path_params/tutorial005.py hl[1,6:9] *}

/// info

You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent.

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

	// Buffers sent on out can not be referenced once sent.
	StreamHandlerFn func(ctx context.Context, payload []byte, in <-chan []byte, out chan<- []byte) *RemoteErr

	// StreamHandler handles fully bidirectional streams,
	// There is flow control in both directions.
	StreamHandler struct {
		// Handle an incoming request. Initial payload is sent.