/// note | Technical Details

The Docker image was created when Uvicorn didn't support managing and restarting dead workers, so it was needed to use Gunicorn with Uvicorn, which added quite some complexity, just to have Gunicorn manage and restart the Uvicorn worker processes.

/// note | Detalles Técnicos

La imagen de Docker se creó cuando Uvicorn no soportaba gestionar y reiniciar workers muertos, por lo que era necesario usar Gunicorn con Uvicorn, lo que añadía bastante complejidad, solo para que Gunicorn gestionara y reiniciara los worker processes de Uvicorn.

		workers = workers[:len(workers)-1]
		worker <- expiryOp(nil)
		es.stats.workers.Add(-1)
	}
	// Atomically replace workers.
	es.workers.Store(&workers)
}

// Worker handles 4 types of expiration tasks.
// 1. Expiry of objects, includes regular and transitioned objects
// 2. Expiry of noncurrent versions due to NewerNoncurrentVersions

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Запуск с Trio

Далее запустите Hypercorn с опцией `--worker-class` и аргументом `trio`:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

Hypercorn, в свою очередь, запустит ваше приложение использующее Trio.

/// tip | Tipp

Machen Sie sich keine Sorgen, wenn einige dieser Punkte zu **Containern**, Docker oder Kubernetes noch nicht viel Sinn ergeben.

Ich werde Ihnen in einem zukünftigen Kapitel mehr über Container-Images, Docker, Kubernetes, usw. erzählen: [FastAPI in Containern – Docker](docker.md){.internal-link target=_blank}.

///

## Schritte vor dem Start

namespace {

TEST(CAPI_EXPERIMENTAL, GetServerDefTest) {
  const string expected_text_proto(R"(cluster {
  job {
    name: "worker"
    tasks {
      key: 0
      value: "tpuserver:0"
    }
    tasks {
      key: 1
      value: "localhost:1"
    }
  }
}
job_name: "worker"
task_index: 1
protocol: "grpc"
)");

  TF_Status* status = TF_NewStatus();

<div class="termy">

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### 🏃 ⏮️ 🎻

⤴️ 👆 💪 🚶‍♀️ 📋 ⏸ 🎛 `--worker-class` ⏮️ 💲 `trio`:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

&amp; 👈 🔜 ▶️ Hypercorn ⏮️ 👆 📱 ⚙️ 🎻 👩‍💻.

🔜 👆 💪 ⚙️ 🎻 🔘 👆 📱. ⚖️ 👍, 👆 💪 ⚙️ AnyIO, 🚧 👆 📟 🔗 ⏮️ 👯‍♂️ 🎻 &amp; ✳. 👶

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Exécuter avec Trio

Ensuite, vous pouvez passer l'option de ligne de commande `--worker-class` avec la valeur `trio` :

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

Et cela démarrera Hypercorn avec votre application en utilisant Trio comme backend.

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Mit Trio ausführen

Dann können Sie die Befehlszeilenoption `--worker-class` mit dem Wert `trio` übergeben:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

Und das startet Hypercorn mit Ihrer Anwendung und verwendet Trio als Backend.

	if (checkOld > 0 && len(p.workers) != checkOld) || n == len(p.workers) || n < 1 {
		// Either already satisfied or worker count changed while we waited for the lock.
		return
	}
	for len(p.workers) < n {
		input := make(chan ReplicationWorkerOperation, 10000)
		p.workers = append(p.workers, input)

		go p.AddWorker(input, &p.activeWorkers)
	}
	for len(p.workers) > n {
		worker := p.workers[len(p.workers)-1]