* mount (verb): montar
* statement (as in code statement): statement (do not translate to "declaración" or "sentencia")
* worker process: worker process (do not translate to "proceso trabajador" or "proceso de trabajo")
* worker processes: worker processes (do not translate to "procesos trabajadores" or "procesos de trabajo")
* worker: worker (do not translate to "trabajador")
* load balancer: load balancer (do not translate to "balanceador de carga")

* the task
* the background task
* the task function

* the template
* the template engine

* the type annotation
* the type hint

* the server worker
* the Uvicorn worker
* the Gunicorn Worker
* the worker process
* the worker class
* the workload

* the deployment
* to deploy

* the SDK
* the software development kit

* the `APIRouter`
* the `requirements.txt`

Und wenn Sie mehrere Worker benötigen, können Sie einfach die `--workers` Befehlszeilenoption verwenden.

/// note | Technische Details

/// tip

Don't worry if some of these items about **containers**, Docker, or Kubernetes don't make a lot of sense yet.

I'll tell you more about container images, Docker, Kubernetes, etc. in a future chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

///

## Previous Steps Before Starting { #previous-steps-before-starting }

## Decision

1. The Gradle distribution will never include a Java runtime.
   Instead, Gradle will leverage Java toolchains for the Daemon and worker processes.
2. The Gradle Daemon, Worker processes, and Tooling API client will continue to support running on different Java versions during a single Gradle invocation.
   The exact versions supported will be determined by the Gradle version.

}

// ExpirationWait returns the duration for which a batch expiration worker
// would wait before working on next object.
func (opts Config) ExpirationWait() time.Duration {
	configMu.RLock()
	defer configMu.RUnlock()

	return opts.ExpirationWorkersWait
}

// ReplicationWait returns the duration for which a batch replication worker
// would wait before working on next object.

/// 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.

#### Docker Compose { #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**.

Then you could want to have **a single container** with a **process manager** starting **several worker processes** inside.

---

```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.

/// tip | Consejo

No te preocupes si algunos de estos elementos sobre **contenedores**, Docker, o Kubernetes no tienen mucho sentido todavía.

Te contaré más sobre imágenes de contenedores, Docker, Kubernetes, etc. en un capítulo futuro: [FastAPI en Contenedores - Docker](docker.md){.internal-link target=_blank}.

///

## Pasos Previos Antes de Iniciar { #previous-steps-before-starting }