Here are some possible combinations and strategies:

* **Gunicorn** managing **Uvicorn workers**
    * Gunicorn would be the **process manager** listening on the **IP** and **port**, the replication would be by having **multiple Uvicorn worker processes**.
* **Uvicorn** managing **Uvicorn workers**

	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]
		p.workers = p.workers[:len(p.workers)-1]
		xioutil.SafeClose(worker)
	}
}

// ResizeWorkerPriority sets replication failed workers pool size

So, in this case, you **would not** want to have a process manager like Gunicorn with Uvicorn workers, or Uvicorn using its own Uvicorn workers. You would want to have just a **single Uvicorn process** per container (but probably multiple containers).

					"ivy",
					"testing-native",
					"maven",
					"integ-test"
				]
			},
			{
				"parallelizationMethod":{
					"name":"TestDistribution"
				},
				"subprojects":[
					"workers",
					"model-core",
					"language-groovy",
					"build-init",
					"logging",
					"plugins-groovy",
					"kotlin-dsl",
					"plugins-java",
					"samples",
					"plugin-development",

// newBatchJobPool creates a pool of job manifest workers of specified size
func newBatchJobPool(ctx context.Context, o ObjectLayer, workers int) *BatchJobPool {
	jpool := &BatchJobPool{
		ctx:          ctx,
		objLayer:     o,
		jobCh:        make(chan *BatchJobRequest, 10000),
		workerKillCh: make(chan struct{}, workers),
		jobCancelers: make(map[string]context.CancelFunc),
	}

	const envDecomWorkers = "_MINIO_DECOMMISSION_WORKERS"
	workerSize, err := env.GetInt(envDecomWorkers, len(pool.sets))
	if err != nil {
		decomLogIf(ctx, fmt.Errorf("invalid workers value err: %v, defaulting to %d", err, len(pool.sets)))
		workerSize = len(pool.sets)
	}

	// Each decom worker needs one List() goroutine/worker
	// add that many extra workers.
	workerSize += len(pool.sets)

	es := newExpiryState(context.Background(), objAPI, 0)
	workers := []chan expiryOp{make(chan expiryOp)}
	es.workers.Store(&workers)
	globalExpiryState = es
	var wg sync.WaitGroup
	wg.Add(1)
	expired := make([]ObjectToDelete, 0, 5)
	go func() {
		defer wg.Done()
		workers := globalExpiryState.workers.Load()
		for t := range (*workers)[0] {
			if t, ok := t.(newerNoncurrentTask); ok {

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

</div>

### Run with Trio

Then you can pass the command line option `--worker-class` with the value `trio`:

<div class="termy">

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

</div>

And that will start Hypercorn with your app using Trio as the backend.

	}
	t.replicationPriority = cfg.ReplicationPriority
	t.replicationMaxWorkers = cfg.ReplicationMaxWorkers

	// N B api.transition_workers will be deprecated
	if globalTransitionState != nil {
		globalTransitionState.UpdateWorkers(cfg.TransitionWorkers)
	}
	t.transitionWorkers = cfg.TransitionWorkers

	t.staleUploadsExpiry = cfg.StaleUploadsExpiry

import okhttp3.internal.assertHeld
import okhttp3.internal.concurrent.TaskRunner.Companion.INSTANCE
import okhttp3.internal.okHttpName
import okhttp3.internal.threadFactory

/**
 * A set of worker threads that are shared among a set of task queues.
 *
 * Use [INSTANCE] for a task runner that uses daemon threads. There is not currently a shared
 * instance for non-daemon threads.
 *