... qui comprend également `uvicorn`, que vous pouvez utiliser comme serveur pour exécuter votre code.

/// note

Vous pouvez également l'installer pièce par pièce.

C'est ce que vous feriez probablement une fois que vous voudrez déployer votre application en production :

```
pip install fastapi
```

Installez également `uvicorn` pour qu'il fonctionne comme serveur :

```
pip install uvicorn
```

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
<span style="color: green;">INFO</span>:     Started reloader process [28720]
<span style="color: green;">INFO</span>:     Started server process [28722]
<span style="color: green;">INFO</span>:     Waiting for application startup.
<span style="color: green;">INFO</span>:     Application startup complete.
```

</div>

   * acquire(3) arrives. We serve this request out of storedPermits, and reduce that to 7.0 (how
   * this is translated to throttling time is discussed later). Immediately after, assume that an
   * acquire(10) request arriving. We serve the request partly from storedPermits, using all the
   * remaining 7.0 permits, and the remaining 3.0, we serve them by fresh permits produced by the
   * rate limiter.
   *

/// tip | 提示

如果可以，请尽量使用 `Annotated` 版本。

///

```Python hl_lines="13-14"
{!> ../../docs_src/dependencies/tutorial008c.py!}
```

////

在示例代码的情况下，客户端将会收到 *HTTP 500 Internal Server Error* 的响应，因为我们没有抛出 `HTTPException` 或者类似的异常，并且服务器也 **不会有任何日志** 或者其他提示来告诉我们错误是什么。😱

### 在包含 `yield` 和 `except` 的依赖项中一定要 `raise`

如果你在使用 `yield` 的依赖项中捕获到了一个异常，你应该再次抛出捕获到的异常，除非你抛出 `HTTPException` 或类似的其他异常，

        this.digest.reset();

        int flags = SMBUtil.readInt4(data, offset + 16);
        if ( ( flags & ServerMessageBlock2.SMB2_FLAGS_SIGNED ) == 0 ) {
            log.error("The server did not sign a message we expected to be signed");
            return true;
        }

        byte[] sig = new byte[SIGNATURE_LENGTH];
        System.arraycopy(data, offset + SIGNATURE_OFFSET, sig, 0, SIGNATURE_LENGTH);

#### A Simple App

You could want a process manager in the container if your application is **simple enough** that can run it on a **single server**, not a cluster.

#### Docker Compose

You could be deploying to a **single server** (not a cluster) with **Docker Compose**, so you wouldn't have an easy way to manage replication of containers (with Docker Compose) while preserving the shared network and **load balancing**.

            .build()

        client.newCall(request).execute().use { response ->
          if (!response.isSuccessful) throw IOException("Unexpected code $response")

          println("Server: ${response.header("Server")}")
          println("Date: ${response.header("Date")}")
          println("Vary: ${response.headers("Vary")}")
        }
      }
    ```

=== ":material-language-java: Java"
    ```java

  // as well as requests dispatched from other priority levels
  // borrowing seats from this level.
  // The server's concurrency limit (ServerCL) is divided among the
  // Limited priority levels in proportion to their NCS values:
  //
  // NominalCL(i)  = ceil( ServerCL * NCS(i) / sum_ncs )
  // sum_ncs = sum[limited priority level k] NCS(k)
  //
  // Bigger numbers mean a larger nominal concurrency limit,

		// performed at '/' resource should be routed by the muxer,
		// the assumption is simply such that requests without a bucket
		// in a federated setup cannot be proxied, so serve them at
		// current server.
		if bucket == "" {
			h.ServeHTTP(w, r)
			return
		}

		// MakeBucket requests should be handled at current endpoint

///

## Über „Formularfelder“

HTML-Formulare (`<form></form>`) senden die Daten in einer „speziellen“ Kodierung zum Server, welche sich von JSON unterscheidet.

**FastAPI** stellt sicher, dass diese Daten korrekt ausgelesen werden, statt JSON zu erwarten.

/// note | "Technische Details"