```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513
[19514] [INFO] Booting worker with pid: 19514

        ```

     * 因此，`main:app` 中的冒号相当于 `from main import app` 中的 Python `import` 部分。

* `--workers`：要使用的worker进程数量，每个进程将运行一个 Uvicorn worker进程，在本例中为 4 个worker进程。

* `--worker-class`：在worker进程中使用的与 Gunicorn 兼容的工作类。
     * 这里我们传递了 Gunicorn 可以导入和使用的类：

         ```Python
         import uvicorn.workers.UvicornWorker
         ```

* `--bind`：这告诉 Gunicorn 要监听的 IP 和端口，使用冒号 (`:`) 分隔 IP 和端口。

  /**
   * This counter prevents an ABA issue where a thread may successfully schedule the worker, the
   * worker runs and exhausts the queue, another thread enqueues a task and fails to schedule the
   * worker, and then the first thread's call to delegate.execute() returns. Without this counter,
   * it would observe the QUEUING state and set it to QUEUED, and the worker would never be
   * scheduled again for future submissions.
   */
  @GuardedBy("queue")

  /**
   * This counter prevents an ABA issue where a thread may successfully schedule the worker, the
   * worker runs and exhausts the queue, another thread enqueues a task and fails to schedule the
   * worker, and then the first thread's call to delegate.execute() returns. Without this counter,
   * it would observe the QUEUING state and set it to QUEUED, and the worker would never be
   * scheduled again for future submissions.
   */
  @GuardedBy("queue")

## Gunicorn mit Uvicorn-Workern ausführen

Dann können Sie Gunicorn ausführen mit:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511

        daemon["Gradle daemon"]
        gradle --> daemon
        gradlew --> daemon
        tapi --> daemon
        
        worker["Worker process"]
        daemon --> worker

        worker2["Worker process"]
        daemon --> worker2

        worker3["Worker process"]
        daemon --> worker3
    
```

These are all Java processes. Each process has a corresponding "runtime".

default   details-v1-698d88b-krdw7       10.244.2.55 ambient-worker2 None     HBONE
default   httpbin-7447985f87-t8hv7       10.244.1.40 ambient-worker  None     TCP
default   productpage-v1-675fc69cf-kkrm2 10.244.2.56 ambient-worker2 None     HBONE
default   ratings-v1-6484c4d9bb-8xc2r    10.244.2.57 ambient-worker2 None     HBONE
default   reviews-v1-5b5d6494f4-c7z5w    10.244.1.41 ambient-worker  None     HBONE

default            reviews-v3-5b9bd44f4-z9ms4                           10.244.1.43 ambient-worker        None                                HBONE
default            sleep-7656cf8794-lxcmx                               10.244.2.58 ambient-worker2       None                                HBONE

///

## Multiple Workers

You can start multiple workers with the `--workers` command line option:

//// tab | `fastapi`

If you use the `fastapi` command:

<div class="termy">

```console
$ <pre> <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:single">main.py</u>

  // Create two worker tasks, using single host server defs.
  // A single host server def contains a client and the remote host.
  // Example:
  //
  //  Worker1:
  //  cluster { job { name: "client" tasks { key: 0 value: "localhost:14525" } }
  //            job { name: "worker" tasks { key: 1 value: "localhost:14523" } }
  //          } job_name: "worker" task_index: 1 protocol: "grpc"
  //