VLC media player

VideoLAN is publishing today, VLC 3.1.0 on iOS and on Windows App (WinRT) platforms. This release brings hardware encoding and ChromeCast on those 2 mobile platforms. It also updates the libvlc to 3.0.3 in those platforms.

VideoLAN is publishing today, VLC 3.1.0 on iOS and on Windows App (WinRT) platforms. This release brings hardware encoding and ChromeCast on those 2 mobile platforms. It also updates the libvlc to 3.0.3 in those platforms.

VideoLAN is publishing today, VLC 3.1.0 on iOS and on Windows App (WinRT) platforms. This release brings hardware encoding and ChromeCast on those 2 mobile platforms. It also updates the libvlc to 3.0.3 in those platforms.

VLC 3.1.0 release After a few months since the release of VLC 3.0, today we release VLC 3.1.0 on 2 mobile OSes: iOS and Windows Store (UWP). This release brings ChromeCast integration to iOS and UWP, like it was present on desktop and Android ... [More] versions. ChromeCast and hardware encoding However, it supports ChromeCast in a more performant way, because we added hardware encoders to those 2 platforms. Indeed, here, for local streaming, we care more about speed and battery saving than we care about bandwidth efficiency, si hardware encoding is a good fit. On iOS, we're using the standard VideoToolbox hardware encoding to produce H.264 streams, muxed in MKV. On UWP, we're using Quick Sync Video for intel CPUs (that covers almost all CPUs since 3rd core generation). In fact, VLC has a QSV encoder since 2013, but it's very rarely used, because people usually prefer software encode (x264). Here, we fixed it and modified it to work inside the UWP sandbox. iOS You should really read Caro's blogpost here! But in that version you have: ChromeCast, 360 video support, with sensors, Numerous bugfixes on the playback core (inherited mostly from VLC 3.0.1-3.0.3) Some decoding speed improvements, Quite a few interface bugs (see 3.1.0 milestone) UWP The version is similar to the iOS version, in the fact that it has hardware encoding and ChromeCast integration. As explained, the hardware encoding is done using QSV. But it features also a large rework of the codebase and fixes a very large number of crashes. Also, funnily enough, we've worked on the 8.1 version too, and we will push that one soon on the store. This includes SurfaceRT devices, even if Microsoft has forgotten them! So VLC 3.1.0, UWP version will be out for: Windows 10 Desktop (x86) XBox One Windows 10 Mobile (ARM) Windows 8.1 Desktop (x86) Windows 8.1 RT (ARM) Once we fixed an issue, we might even do Windows Phone 8.1. The Windows 10 versions are on the store today, and we're waiting for a deployment issue to be fixed to push the 8.1 versions! (Note: if you are from Windows Central, you can contact me for more details) Have fun! [Less]

After quite a bit of time far from the blog, I am back around here. The biggest reason for this silence was that this was taking a lot of my time, but I had almost no positive feedback on those posts. Let's see if we can do better this time Here is a small cone, to make you more happy:

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 ... [More] concurrency in a more performant and simple way. Coroutines way Suspending vs blocking Basic usage Dispatch Coroutine context Scope Notes Callbacks and locks elimination with channels Actors Android lifecycle + Coroutines Callbacks mitigation (Part 1) Callbacks mitigation (Part 2): Retrofit To be continued 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 Main context (main thread). In it, we retrieve an image from the IO one, and process it back in Main. launch(Dispatchers.Main) { val image = withContext(Dispatchers.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 threadpool, 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(Dispatchers.Main) { val deferred1 = async(Dispatchers.Default) { getFirstValue() } val deferred2 = async(Dispatchers.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 current scope default 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. Dispatch 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 of Main dispatching, which is runOnUiThread: public final void runOnUiThread(Runnable action) { if (Thread.currentThread() != mUiThread) { mHandler.post(action); // Dispatch } else { action.run(); // Immediate execution } } Android implementation of Main context is a dispatcher based on a Handler. So this really is the matching implementation: launch(Dispatchers.Main) { ... } vs launch(Dispatchers.Main, CoroutineStart.UNDISPATCHED) { ... } // Since kotlinx 0.26: launch(Dispatchers.Main.immediate) { ... } launch(Dispatchers.Main) posts a Runnable in a Handler, so its code execution is not immediate. launch(Dispatchers.Main, CoroutineStart.UNDISPATCHED) will immediately execute its lambda expression in the current thread. Dispatchers.Main 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. Its actual implementation looks like: val Main: HandlerDispatcher = HandlerContext(mainHandler, "Main") 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(Disaptchers.Default+exceptionHandler+job) { ... } job.cancel() will cancel all coroutines that have job as a parent. And exceptionHandler will receive all thrown exceptions in these coroutines. Scope A coroutineScope makes errors handling easier: If any child coroutine fails, the entire scope fails and all of children coroutines are cancelled. In the async example, if the retrieval of a value failed, the other one continued then we would have a broken state to manage. With a coroutineScope, useValues will be called only if both values retrieval succeeded. Also, if deferred2 fails, deferred1 is cancelled. coroutineScope { val deferred1 = async(Dispatchers.Default) { getFirstValue() } val deferred2 = async(Dispatchers.IO) { getSecondValue() } useValues(deferred1.await(), deferred2.await()) } We also can “scope” an entire class to define its default CoroutineContext and leverage it. Example of a class implementing CoroutineScope: open class ScopedViewModel : ViewModel(), CoroutineScope { protected val job = Job() override val coroutineContext = Dispatchers.Main+job override fun onCleared() { super.onCleared() job.cancel() } } Launching coroutines in a CoroutineScope: launch or async default dispatcher is now the current scope dispatcher. And we can still choose a different one the same way we did before. launch { val foo = withContext(Dispatchers.IO) { … } // lambda runs within scope's CoroutineContext … } launch(Dispatchers.Default) { // lambda runs in default threadpool. … } Standalone coroutine launching (outside of any CoroutineScope): GlobalScope.launch(Dispatchers.Main) { // lambda runs in main thread. … } Notes Coroutines limit Java interoperability Confine mutablility to avoid locks Coroutines are for threading waiting Avoid I/O in Dispatchers.Default (and Main…) Dispatchers.IO designed for this Threads are expensive, so are single-thread contexts Dispatchers.Default is based on a ForkJoinPool on Android 5+ Coroutines can be used via Channels 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 (or a non-blocking offer), and instead of a blocking take operation it has a suspending receive. Actors 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>(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(update.media as T) is MediaListAddition -> addMedia(update.mediaList as List<T>) is MediaRemoval -> removeMedia(update.media as T) } } } // usage fun filter(query: String?) = updateActor.offer(Filter(query)) //or suspend fun filter(query: String?) = updateActor.send(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 Actors can be profitable for Android UI management too, they can ease tasks cancellation and prevent overloading of the main thread. Let’s implement it and call job.cancel() when activity is destroyed. class MyActivity : AppCompatActivity(), CoroutineScope { protected val job = SupervisorJob() // the instance of a Job for this activity override val coroutineContext = Dispatchers.Main.immediate+job override fun onDestroy() { super.onDestroy() job.cancel() // cancel the job when activity is destroyed } } A SupervisorJob is similar to a regular Job with the only exception that cancellation is propagated only downwards. So we do not cancel all coroutines in the Activity, when one fails. A bit better, with an extension function, we can make this CoroutineContext accessible from any View of a CoroutineScope val View.coroutineContext: CoroutineContext? get() = (context as? CoroutineScope)?.coroutineContext 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 Activity’s scope. 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 = (context as? CoroutineScope)?.actor<Unit>( capacity = Channel.CONFLATED) { for (event in channel) action() } ?: GlobalScope.actor<Unit>( Dispatchers.Main, capacity = Channel.CONFLATED) { 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 { @OnLifecycleEvent(Lifecycle.Event.ON_DESTROY) fun onDestroy() { job.cancel() } }) return job } //usage GlobalScope.launch(Dispatchers.Main, 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: requestBrowsing(url, listener) triggers the parsing of folder at url address. The listener receives onMediaAdded(media: Media) for each discovered media in this folder. 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) { refreshList.add(media)) } override fun onBrowseEnd() { val list = refreshList.toMutableList() refreshList.clear() launch { dataset.value = list parseSubDirectories() } } } 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) { browserChannel.offer(media) } override fun onBrowseEnd() { browserChannel.close() } suspend fun refresh() { browserChannel = Channel(Channel.UNLIMITED) val refreshList = mutableListOf<Media>() requestBrowsing(url) //Suspends at every iteration to wait for media for (media in browserChannel) refreshList.add(media) //Channel has been closed dataset.value = refreshList parseSubDirectories() } 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>) { continuation.resume(response) } override fun onFailure(call: Call<T>, t: Throwable) { continuation.resumeWithException(t) } }) } suspend fun browse(path: String?) = retrofitSuspendCall { ApiClient.browse(path) } // usage (within Main 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: Coroutines guide Guide to UI programming with coroutines Understanding Android Core: Looper, Handler, and HandlerThread Presenter as a Function: Reactive MVP for Android Using Kotlin Coroutines [Less]

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 ... [More] concurrency in a more performant and simple way. Coroutines way Suspending vs blocking Basic usage Dispatch Coroutine context Scope Notes Callbacks and locks elimination with channels Actors Android lifecycle + Coroutines Callbacks mitigation (Part 1) Callbacks mitigation (Part 2): Retrofit To be continued 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 Main context (main thread). In it, we retrieve an image from the IO one, and process it back in Main. launch(Dispatchers.Main) { val image = withContext(Dispatchers.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 threadpool, 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(Dispatchers.Main) { val deferred1 = async(Dispatchers.Default) { getFirstValue() } val deferred2 = async(Dispatchers.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 current scope default 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. Dispatch 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 of Main dispatching, which is runOnUiThread: public final void runOnUiThread(Runnable action) { if (Thread.currentThread() != mUiThread) { mHandler.post(action); // Dispatch } else { action.run(); // Immediate execution } } Android implementation of Main context is a dispatcher based on a Handler. So this really is the matching implementation: launch(Dispatchers.Main) { ... } vs launch(Dispatchers.Main, CoroutineStart.UNDISPATCHED) { ... } // Since kotlinx 0.26: launch(Dispatchers.Main.immediate) { ... } launch(Dispatchers.Main) posts a Runnable in a Handler, so its code execution is not immediate. launch(Dispatchers.Main, CoroutineStart.UNDISPATCHED) will immediately execute its lambda expression in the current thread. Dispatchers.Main 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. Its actual implementation looks like: val Main: HandlerDispatcher = HandlerContext(mainHandler, "Main") 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(Disaptchers.Default+exceptionHandler+job) { ... } job.cancel() will cancel all coroutines that have job as a parent. And exceptionHandler will receive all thrown exceptions in these coroutines. Scope A coroutineScope makes errors handling easier: If any child coroutine fails, the entire scope fails and all of children coroutines are cancelled. In the async example, if the retrieval of a value failed, the other one continued then we would have a broken state to manage. With a coroutineScope, useValues will be called only if both values retrieval succeeded. Also, if deferred2 fails, deferred1 is cancelled. coroutineScope { val deferred1 = async(Dispatchers.Default) { getFirstValue() } val deferred2 = async(Dispatchers.IO) { getSecondValue() } useValues(deferred1.await(), deferred2.await()) } We also can “scope” an entire class to define its default CoroutineContext and leverage it. Example of a class implementing CoroutineScope: open class ScopedViewModel : ViewModel(), CoroutineScope { protected val job = Job() override val coroutineContext = Dispatchers.Main+job override fun onCleared() { super.onCleared() job.cancel() } } Launching coroutines in a CoroutineScope: launch or async default dispatcher is now the current scope dispatcher. And we can still choose a different one the same way we did before. launch { val foo = withContext(Dispatchers.IO) { … } // lambda runs within scope's CoroutineContext … } launch(Dispatchers.Default) { // lambda runs in default threadpool. … } Standalone coroutine launching (outside of any CoroutineScope): GlobalScope.launch(Dispatchers.Main) { // lambda runs in main thread. … } We can even define a scope for application with dispatcher Main as default: object AppScope : CoroutineScope by GlobalScope { override val coroutineContext = Dispatchers.Main.immediate } Notes Coroutines limit Java interoperability Confine mutablility to avoid locks Coroutines are for threading waiting Avoid I/O in Dispatchers.Default (and Main…) Dispatchers.IO designed for this Threads are expensive, so are single-thread contexts Dispatchers.Default is based on a ForkJoinPool on Android 5+ Coroutines can be used via Channels 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 (or a non-blocking offer), and instead of a blocking take operation it has a suspending receive. Actors 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>(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(update.media as T) is MediaListAddition -> addMedia(update.mediaList as List<T>) is MediaRemoval -> removeMedia(update.media as T) } } } // usage fun filter(query: String?) = updateActor.offer(Filter(query)) //or suspend fun filter(query: String?) = updateActor.send(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 Actors can be profitable for Android UI management too, they can ease tasks cancellation and prevent overloading of the main thread. Let’s implement it and call job.cancel() when activity is destroyed. class MyActivity : AppCompatActivity(), CoroutineScope { protected val job = SupervisorJob() // the instance of a Job for this activity override val coroutineContext = Dispatchers.Main.immediate+job override fun onDestroy() { super.onDestroy() job.cancel() // cancel the job when activity is destroyed } } A SupervisorJob is similar to a regular Job with the only exception that cancellation is propagated only downwards. So we do not cancel all coroutines in the Activity, when one fails. A bit better, with an extension function, we can make this CoroutineContext accessible from any View of a CoroutineScope val View.coroutineContext: CoroutineContext? get() = (context as? CoroutineScope)?.coroutineContext 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 Activity’s scope. 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 scope = (context as? CoroutineScope)?: AppScope val eventActor = scope.actor<Unit>(capacity = Channel.CONFLATED) { 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 { @OnLifecycleEvent(Lifecycle.Event.ON_DESTROY) fun onDestroy() { job.cancel() } }) return job } //usage GlobalScope.launch(Dispatchers.Main, 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: requestBrowsing(url, listener) triggers the parsing of folder at url address. The listener receives onMediaAdded(media: Media) for each discovered media in this folder. 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) { refreshList.add(media)) } override fun onBrowseEnd() { val list = refreshList.toMutableList() refreshList.clear() launch { dataset.value = list parseSubDirectories() } } } 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) { browserChannel.offer(media) } override fun onBrowseEnd() { browserChannel.close() } suspend fun refresh() { browserChannel = Channel(Channel.UNLIMITED) val refreshList = mutableListOf<Media>() requestBrowsing(url) //Suspends at every iteration to wait for media for (media in browserChannel) refreshList.add(media) //Channel has been closed dataset.value = refreshList parseSubDirectories() } 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>) { continuation.resume(response) } override fun onFailure(call: Call<T>, t: Throwable) { continuation.resumeWithException(t) } }) } suspend fun browse(path: String?) = retrofitSuspendCall { ApiClient.browse(path) } // usage (within Main 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: Coroutines guide Guide to UI programming with coroutines Understanding Android Core: Looper, Handler, and HandlerThread Presenter as a Function: Reactive MVP for Android Using Kotlin Coroutines Sample DiffUtil implementation [Less]

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 ... [More] concurrency in a more performant and simple way. Coroutines way Suspending vs blocking Basic usage Dispatch Coroutine context Notes Callbacks and locks elimination with channels Actors Android lifecycle + Coroutines Callbacks mitigation (Part 1) Callbacks mitigation (Part 2): Retrofit To be continued 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. Dispatch 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) { mHandler.post(action); // Dispatch } else { action.run(); // Immediate execution } } Android implementation of UI context is a dispatcher based on a Handler. So this really is the matching implementation: launch(UI) { ... } vs 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. Notes 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>() ).asCoroutineDispatcher() 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. Actors 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(update.media as T) is MediaListAddition -> addMedia(update.mediaList as List<T>) is MediaRemoval -> removeMedia(update.media 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() { super.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 { @OnLifecycleEvent(Lifecycle.Event.ON_DESTROY) fun onDestroy() { job.cancel() } }) return job } //usage 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: requestBrowsing(url, listener) triggers the parsing of folder at url address. The listener receives onMediaAdded(media: Media) for each discovered media in this folder. 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) { refreshList.add(media)) } override fun onBrowseEnd() { val list = refreshList.toMutableList() refreshList.clear() launch(UI) { dataset.value = list parseSubDirectories() } } } 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) { browserChannel.offer(media) } override fun onBrowseEnd() { browserChannel.close() } suspend fun refresh() { browserChannel = Channel(Channel.UNLIMITED) val refreshList = mutableListOf<Media>() requestBrowsing(url) //Suspends at every iteration to wait for media for (media in browserChannel) refreshList.add(media) //Channel has been closed dataset.value = refreshList parseSubDirectories() } 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>) { continuation.resume(response) } override fun onFailure(call: Call<T>, t: Throwable) { continuation.resumeWithException(t) } }) } suspend fun browse(path: String?) = retrofitSuspendCall { ApiClient.browse(path) } // 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: Coroutines guide Guide to UI programming with coroutines Understanding Android Core: Looper, Handler, and HandlerThread Presenter as a Function: Reactive MVP for Android Using Kotlin Coroutines [Less]

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 ... [More] 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 Main context (main thread). In it, we retrieve an image from the IO one, and process it back in Main. launch(Dispatchers.Main) { val image = withContext(Dispatchers.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 threadpool, 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(Dispatchers.Main) { val deferred1 = async(Dispatchers.Default) { getFirstValue() } val deferred2 = async(Dispatchers.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 current scope default 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. Dispatch 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 of Main dispatching, which is runOnUiThread: public final void runOnUiThread(Runnable action) { if (Thread.currentThread() != mUiThread) { mHandler.post(action); // Dispatch } else { action.run(); // Immediate execution } } Android implementation of Main context is a dispatcher based on a Handler. So this really is the matching implementation: launch(Dispatchers.Main) { ... } vs launch(Dispatchers.Main, CoroutineStart.UNDISPATCHED) { ... } // Since kotlinx 0.26: launch(Dispatchers.Main.immediate) { ... } launch(Dispatchers.Main) posts a Runnable in a Handler, so its code execution is not immediate. launch(Dispatchers.Main, CoroutineStart.UNDISPATCHED) will immediately execute its lambda expression in the current thread. Dispatchers.Main 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. Its actual implementation looks like: val Main: HandlerDispatcher = HandlerContext(mainHandler, "Main") 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(Disaptchers.Default+exceptionHandler+job) { ... } job.cancel() will cancel all coroutines that have job as a parent. And exceptionHandler will receive all thrown exceptions in these coroutines. Scope A coroutineScope makes errors handling easier: If any child coroutine fails, the entire scope fails and all of children coroutines are cancelled. In the async example, if the retrieval of a value failed, the other one continued then we would have a broken state to manage. With a coroutineScope, useValues will be called only if both values retrieval succeeded. Also, if deferred2 fails, deferred1 is cancelled. coroutineScope { val deferred1 = async(Dispatchers.Default) { getFirstValue() } val deferred2 = async(Dispatchers.IO) { getSecondValue() } useValues(deferred1.await(), deferred2.await()) } We also can “scope” an entire class to define its default CoroutineContext and leverage it. Example of a class implementing CoroutineScope: open class ScopedViewModel : ViewModel(), CoroutineScope { protected val job = Job() override val coroutineContext = Dispatchers.Main+job override fun onCleared() { super.onCleared() job.cancel() } } Launching coroutines in a CoroutineScope: launch or async default dispatcher is now the current scope dispatcher. And we can still choose a different one the same way we did before. launch { val foo = withContext(Dispatchers.IO) { … } // lambda runs within scope's CoroutineContext … } launch(Dispatchers.Default) { // lambda runs in default threadpool. … } Standalone coroutine launching (outside of any CoroutineScope): GlobalScope.launch(Dispatchers.Main) { // lambda runs in main thread. … } We can even define a scope for application with dispatcher Main as default: object AppScope : CoroutineScope by GlobalScope { override val coroutineContext = Dispatchers.Main.immediate } Notes Coroutines limit Java interoperability Confine mutablility to avoid locks Coroutines are for threading waiting Avoid I/O in Dispatchers.Default (and Main…) Dispatchers.IO designed for this Threads are expensive, so are single-thread contexts Dispatchers.Default is based on a ForkJoinPool on Android 5+ Coroutines can be used via Channels 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 (or a non-blocking offer), and instead of a blocking take operation it has a suspending receive. Actors 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>(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(update.media as T) is MediaListAddition -> addMedia(update.mediaList as List<T>) is MediaRemoval -> removeMedia(update.media as T) } } } // usage fun filter(query: String?) = updateActor.offer(Filter(query)) //or suspend fun filter(query: String?) = updateActor.send(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 Actors can be profitable for Android UI management too, they can ease tasks cancellation and prevent overloading of the main thread. Let’s implement it and call job.cancel() when activity is destroyed. class MyActivity : AppCompatActivity(), CoroutineScope { protected val job = SupervisorJob() // the instance of a Job for this activity override val coroutineContext = Dispatchers.Main.immediate+job override fun onDestroy() { super.onDestroy() job.cancel() // cancel the job when activity is destroyed } } A SupervisorJob is similar to a regular Job with the only exception that cancellation is propagated only downwards. So we do not cancel all coroutines in the Activity, when one fails. A bit better, with an extension function, we can make this CoroutineContext accessible from any View of a CoroutineScope val View.coroutineContext: CoroutineContext? get() = (context as? CoroutineScope)?.coroutineContext 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 Activity’s scope. 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 scope = (context as? CoroutineScope)?: AppScope val eventActor = scope.actor<Unit>(capacity = Channel.CONFLATED) { 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 { @OnLifecycleEvent(Lifecycle.Event.ON_DESTROY) fun onDestroy() { job.cancel() } }) return job } //usage GlobalScope.launch(Dispatchers.Main, 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: requestBrowsing(url, listener) triggers the parsing of folder at url address. The listener receives onMediaAdded(media: Media) for each discovered media in this folder. 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) { refreshList.add(media)) } override fun onBrowseEnd() { val list = refreshList.toMutableList() refreshList.clear() launch { dataset.value = list parseSubDirectories() } } } 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) { browserChannel.offer(media) } override fun onBrowseEnd() { browserChannel.close() } suspend fun refresh() { browserChannel = Channel(Channel.UNLIMITED) val refreshList = mutableListOf<Media>() requestBrowsing(url) //Suspends at every iteration to wait for media for (media in browserChannel) refreshList.add(media) //Channel has been closed dataset.value = refreshList parseSubDirectories() } 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>) { continuation.resume(response) } override fun onFailure(call: Call<T>, t: Throwable) { continuation.resumeWithException(t) } }) } suspend fun browse(path: String?) = retrofitSuspendCall { ApiClient.browse(path) } // usage (within Main 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: Coroutines guide Guide to UI programming with coroutines Understanding Android Core: Looper, Handler, and HandlerThread Presenter as a Function: Reactive MVP for Android Using Kotlin Coroutines Sample DiffUtil implementation [Less]

VideoLAN is publishing the VLC 3.0.3 release, a new minor release of 3.0. This release is fixing numerous crashes and regressions from VLC 3.0.0, "Vetinari", and it fixes some security issues. More information available here. Update for everyone is advised for this release.