<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; ✳. 👶

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();

Hier sind einige mögliche Kombinationen und Strategien:

* **Gunicorn**, welches **Uvicorn-Worker** managt
    * Gunicorn wäre der **Prozessmanager**, der die **IP** und den **Port** überwacht, die Replikation würde durch **mehrere Uvicorn-Workerprozesse** erfolgen
* **Uvicorn**, welches **Uvicorn-Worker** managt

			Optional:    true,
			Type:        "int",
		},
		config.HelpKV{
			Key:         DriveWorkers,
			Description: `the number of workers per drive to heal a new disk replacement` + defaultHelpPostfix(DriveWorkers),
			Optional:    true,
			Type:        "int",
		},
	}

      "coverage" : {
        "per_day" : [ "linux", "macOs", "windows" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.experiment.java.ParallelBuildPerformanceTest.clean assemble with 4 parallel workers",
    "groups" : [ {
      "testProject" : "largeJavaMultiProject",
      "coverage" : {
        "per_week" : [ "linux" ]
      }
    }, {
      "testProject" : "largeMonolithicJavaProject",
      "coverage" : {

</component>...

 * limitations under the License.
 */

package gradlebuild.incubation.action

import org.gradle.api.file.ConfigurableFileCollection
import org.gradle.api.file.RegularFileProperty
import org.gradle.workers.WorkParameters


interface IncubatingApiReportAggregationParameter : WorkParameters {
    val reports: ConfigurableFileCollection
    val htmlReportFile: RegularFileProperty

```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.

	if err != nil {
		return cfg, err
	}
	if replicationMaxWorkers <= 0 || replicationMaxWorkers > 500 {
		return cfg, config.ErrInvalidReplicationWorkersValue(nil).Msg("Number of replication workers should be between 1 and 500")
	}
	cfg.ReplicationMaxWorkers = replicationMaxWorkers

TF_CAPI_EXPORT extern TFE_ContextDevicePlacementPolicy
TFE_ContextGetDevicePlacementPolicy(TFE_Context* ctx);

// A tensorflow.ServerDef specifies remote workers (in addition to the current
// workers name). Operations created in this context can then be executed on
// any of these remote workers by setting an appropriate device.
//
// If the following is set, all servers identified by the
// ServerDef must be up when the context is created.