* 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`

///

## Multiple Workers { #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
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

## 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.

Example:

Source (English):

```
# FastAPI in Containers - Docker { #fastapi-in-containers-docker }
```

Translate with (German) – notice the dash:

```
# FastAPI in Containern – Docker { #fastapi-in-containers-docker }
```

Do NOT translate with (German) – notice the hyphen:

```
# FastAPI in Containern - Docker { #fastapi-in-containers-docker }
```

In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.

This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes.

    published = false

    requiredRuntimes {
        client = false
        daemon = false
        worker = false
    }

    computedRuntimes {
        client = false
        daemon = false
        worker = false
    }

    // TODO: Most of these properties are the same across projects. We should
    // compute these at the settings-level instead of the project-level.

}

// 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.

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server.release();

  // Update the server def with a new set of names (worker instead of
  // localhost).
  tensorflow::ServerDef updated_server_def = GetServerDef("worker", 2);
  serialized = updated_server_def.SerializeAsString();

  updated_server_def.set_task_index(1);
  absl::Status s = tensorflow::GrpcServer::Create(

* code base: кодовая база
* instantiate: создать экземпляр (avoid "инстанцировать")
* load balancer: балансировщик нагрузки
* load balance: балансировка нагрузки
* worker process: воркер-процесс (or `процесс воркера`)
* worker: воркер
* lifespan: lifespan (do not translate when it's about lifespan events, but translate as `жизненный цикл` or `срок жизни` in other cases)
* mount (verb): монтировать

      {
        "subprojects": [
          "configuration-problems-base",
          "daemon-server-worker",
          "docs-asciidoctor-extensions-base",
          "java-api-extractor",
          "javadoc",
          "logging-api",
          "model-reflect",
          "plugin-use",
          "request-handler-worker",
          "resources",
          "security"
        ],
        "parallelizationMethod": {