Modern concurrency on Android with Kotlin

9 minute read

Current Java/Android concurrency framework leads to callback hells and blocking states because we do not have any other simple way to guarantee thread safety.

With coroutines, kotlin brings a very efficient and complete framework to manage concurrency in a more performant and simple way.

Suspending vs blocking

Coroutines do not replace threads, it’s more like a framework to manage it.
Its philosophy is to define an execution context which allows to wait for background operations to complete, without blocking the original thread.

The goal here is to avoid callbacks and make concurrency easier.

Basic usage

Very simple first example, we launch a coroutine in the UI context. In it, we retrieve an image from the IO one, and process it back in UI.

launch(UI) {
    val image = withContext(IO) { getImage() } // Get from IO context
    imageView.setImageBitmap(image) // Back on main thread

Staightforward code, like a single threaded function. And while getImage runs in IO dedicated thread, the main thread is free for any other job! withContext function suspends the current coroutine while its action (getImage()) is running. As soon as getImage() returns and main looper is available, coroutine resumes on main thread, and imageView.setImageBitmap(image) is called.

Second example, we now want 2 background works done to use them. We will use the async/await duo to make them run in parallel and use their result in main thread as soon as both are ready:

val job = launch(UI) {
    val deferred1 = async { getFirstValue() }
    val deferred2 = async(IO) { getSecondValue() }
    useValues(deferred1.await(), deferred2.await())

job.join() // suspends current coroutine until job is done

async is similar to launch but returns a deferred (which is the Kotlin equivalent of Future), so we can get its result with await(). Called with no parameter, it runs in CommonPool context.

And once again, the main thread is free while we are waiting for our 2 values.

As you can see, launch funtion returns a Job that can be used to wait for the operation to be over, with the join() function. It works like in any other language, except that it suspends the coroutine instead of blocking the thread.


Dispatching is a key notion with coroutines, it’s the action to ‘jump’ from a thread to another one.

Let’s look at our current java equivalent to UI dispatching, which is runOnUiThread:

public final void runOnUiThread(Runnable action) {
    if (Thread.currentThread() != mUiThread) {; // Dispatch
    } else {; // Immediate execution

Android implementation of UI context is a dispatcher based on a Handler. So this really is the matching implementation:

launch(UI) { ... }
launch(UI, CoroutineStart.UNDISPATCHED) { ... }

launch(UI) posts a Runnable in a Handler, so its code execution is not immediate.
launch(UI, CoroutineStart.UNDISPATCHED) will immediately execute its lambda expression in the current thread.

UI guarantees that coroutine is dispatched on main thread when it resumes, and it uses a Handler as the native Android implementation to post in the application event loop.

See its actual implementation:

val UI = HandlerContext(Handler(Looper.getMainLooper()), "UI")

To get a better understanding of Android dispatching, you can read this blog post on Understanding Android Core: Looper, Handler, and HandlerThread.

Coroutine context

A couroutine context (aka coroutine dispatcher) defines on which thread its code will execute, what to do in case of thrown exception and refers to a parent context, to propagate cancellation.

val job = Job()
val exceptionHandler = CoroutineExceptionHandler {
    coroutineContext, throwable -> whatever(throwable)

launch(CommonPool+exceptionHandler, parent = job) { ... }

job.cancel() will cancel all coroutines that have job as a parent. And exceptionHandler will receive all thrown exceptions in these coroutines.


  • Coroutines limit Java interoperability
  • Confine mutablility to avoid locks
  • Coroutines are for threading waiting
    • Avoid I/O in CommonPool (and UI…)
    • SharedPool dispatcher coming soon to improve this
  • Threads are expensive, so are single-thread contexts
  • CommonPool is based on a ForkJoinPool on Android 5+
  • Coroutines can be used via Channels

CommonPool is a threadpool, aimed to be intensively used. If you perform I/O tasks in it, you could get all its threads blocked at the same time and any coroutine relying on it will be waiting.
JetBrains is adressing this issue and will probably release a shared pool guarantying that at least one thread is always free from I/O operations.
For now, it’s important to keep it free from long tasks and execute them in dedicated threads/contexts, like:

val IO = ThreadPoolExecutor(0, Integer.MAX_VALUE, 60L,
        TimeUnit.SECONDS, SynchronousQueue<Runnable>()

Callbacks and locks elimination with channels

Channel definition from JetBrain documentation:

A Channel is conceptually very similar to BlockingQueue. One key difference is that instead of a blocking put operation it has a suspending send, and instead of a blocking take operation it has a suspending receive.


Let’s start with a simple tool to use Channels, the Actor.

We already saw it in this blog with the DiffUtil kotlin implementation.

Actor is, yet again, very similar to Handler: we define a coroutine context (so, the tread where to execute actions) and it will execute it in a sequencial order.

Difference is it uses coroutines of course :), we can specify a capacity and executed code can suspend.

An actor will basically forward any order to a coroutine Channel. It will guaranty the order execution and confine operations in its context. It greatly helps to remove synchronize calls and keep all threads free!

protected val updateActor by lazy {
    actor<Update>(UI, capacity = Channel.UNLIMITED) {
        for (update in channel) when (update) {
            Refresh -> updateList()
            is Filter -> filter.filter(update.query)
            is MediaUpdate -> updateItems(update.mediaList as List<T>)
            is MediaAddition -> addMedia( as T)
            is MediaListAddition -> addMedia(update.mediaList as List<T>)
            is MediaRemoval -> removeMedia( as T)
// usage
suspend fun filter(query: String?) = updateActor.offer(Filter(query))

In this example, we take advantage of the Kotlin sealed classes feature to select which action to execute.

sealed class Update
object Refresh : Update()
class Filter(val query: String?) : Update()
class MediaAddition(val media: Media) : Update()

And all this actions will be queued, they will never run in parallel. That’s a good way to achieve mutability confinement.

Android lifecycle + Coroutines

(Sample shamefully copied from JetBrain’s Guide to UI programming with coroutines)

Actors can be profitable for Android UI management too, they can ease tasks cancellation and prevent overloading of the UI thread.

Let’s first declare a JobHolder interface, which will be applied to our Activity. This job will be used as a parent for any user triggered task, and will allow their cancellation.

interface JobHolder {
    val job: Job

Let’s implement it and call job.cancel() when activity is destroyed.

class MyActivity : AppCompatActivity(), JobHolder {
    override val job: Job = Job() // the instance of a Job for this activity

    override fun onDestroy() {
        job.cancel() // cancel the job when activity is destroyed

A bit better, with an extension function, we can make this Job accessible from any View of a JobHolder

val View.contextJob: Job
    get() = (context as? JobHolder)?.job ?: NonCancellable

We can now combine all this, setOnClick function creates a conflated actor to manage its onClick actions. In case of multiple clicks, intermediates actions will be ignored, preventing any ANR, and these actions will be executed in a context with contextJob as a parent. So it will be cancelled when Activity is destroyed 😎

fun View.setOnClick(action: suspend () -> Unit) {
    // launch one actor as a parent of the context job
    val eventActor = actor<Unit>(context = UI,
                start = CoroutineStart.UNDISPATCHED,
                capacity = Channel.CONFLATED,
                parent = contextJob) {
        for (event in channel) action()
    // install a listener to activate this actor
    setOnClickListener { eventActor.offer(Unit) }

In this example, we set the Channel as Conflated to ignore events when we have too much of them. You can change it to Channel.UNLIMITED if you prefer to queue events without missing anyone of them, but still protect your app from ANR

We also can combine coroutines and Lifecycle frameworks to automate UI tasks cancellation:

val LifecycleOwner.untilDestroy: Job get() {
    val job = Job()

    lifecycle.addObserver(object: LifecycleObserver {
        fun onDestroy() { job.cancel() }

    return job
launch(UI, parent = untilDestroy) { /* amazing things happen here! */ }

Callbacks mitigation (Part 1)

Example of a callback based API use transformed thank to a Channel.

API works like this:

  1. requestBrowsing(url, listener) triggers the parsing of folder at url address.
  2. The listener receives onMediaAdded(media: Media) for each discovered media in this folder.
  3. listener.onBrowseEnd() is called once folder parsing is done.

Here is the old refresh function in VLC browser provider:

private val refreshList = mutableListOf<Media>()

fun refresh() = requestBrowsing(url, refreshListener)

private val refreshListener = object : EventListener{
    override fun onMediaAdded(media: Media) {
    override fun onBrowseEnd() {
        val list = refreshList.toMutableList()
        launch(UI) {
            dataset.value = list

How to improve this?

We create a channel, which will be initiated in refresh. Browser callbacks will now only forward media to this channel then close it.

Refresh function is now easier to understand. It sets the channel, calls the VLC browser then fills a list with the media and processes it.

Instead of the select or consumeEach functions, we can use for to wait for media and it will break once browserChannel is closed

private lateinit var browserChannel : Channel<Media>

override fun onMediaAdded(media: Media) {

override fun onBrowseEnd() {

suspend fun refresh() {
    browserChannel = Channel(Channel.UNLIMITED)
    val refreshList = mutableListOf<Media>()
    //Suspends at every iteration to wait for media
    for (media in browserChannel) refreshList.add(media)
    //Channel has been closed
    dataset.value = refreshList

Callbacks mitigation (Part 2): Retrofit

Second approach, we don’t use kotlinx-coroutines at all but the coroutine core framework.
Let’s see how coroutines really work!

retrofitSuspendCall function wraps a Retrofit Call request to make it a suspend function.
With suspendCoroutine we call the Call.enqueue method and suspend the coroutine. The provided callback will call continuation.resume(response) to resume the coroutine with the server response once received.

Then, we just have to bundle our Retrofit functions in retrofitSuspendCall to have a suspending functions returning the requests result.

suspend inline fun <reified T> retrofitSuspendCall(request: () -> Call<T>
) : Response<T> = suspendCoroutine { continuation ->
    request.invoke().enqueue(object : Callback<T> {
        override fun onResponse(call: Call<T>, response: Response<T>) {
        override fun onFailure(call: Call<T>, t: Throwable) {

suspend fun browse(path: String?) = retrofitSuspendCall {

// usage (within UI coroutine context)
livedata.value = Repo.browse(path)

This way, the network blocking call is done in Retrofit dedicated thread, coroutine is here to wait for the response, and in-app usage couldn’t be simpler!

This implementation is inspired by gildor/kotlin-coroutines-retrofit library, which makes it ready to use.
JakeWharton/retrofit2-kotlin-coroutines-adapter is also available with another implementation, for the same result.

To be continued

Channel framework can be used in many other ways, you can look at BroadcastChannel for more powerful implementations according to your needs.
We can also create channels with the Produce function.
It can also be useful for communication between UI components: an adapter can pass click events to its Fragment/Activity via a Channel or an Actor for example.

Related readings:

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