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Why does kotlin flow not trigger the transform function after an error is handled

I have the below code in my view model class.
class MarketViewModel #Inject constructor(repo: MarketRepository) : ViewModel() {
private val retry = MutableStateFlow(0)
val marketState: LiveData<State<Market>> =
retry.flatMapLatest{repo.refreshMarket()}
.map { State.Success(it) as State<T> }
.catch { error -> emit(State.Error(error)) }
.stateIn(vmScope, SharingStarted.WhileSubscribed(5000), State.Loading())
.asLiveData()
fun retry() {
retry.value++
}
}
MarketRepository.kt:
fun refreshMarket() =
flow { emit(api.getMarkets()) }
.onEach { db.upsert(it) }
.flowOn(dispatchers.IO)
It works fine until a network error occurs in the repository method refreshMarket then when I call the retry() on the view model, it doesn't trigger the flatMapLatest transformer function anymore on the retry MutableStateFlow, why?
Does the flow get complete when it calls a Catch block? how to handle such situation?

You're right, catch won't continue emitting after an exception is caught. As the documentation says, it is conceptually similar to wrapping all the code above it in try. If there is a loop in a traditional try block, it does not continue iterating once something is thrown, for example:
try {
for (i in 1..10) {
if (i == 2) throw RuntimeException()
println(i)
}
} catch (e: RuntimeException) {
println("Error!")
}
In this example, once 2 is encountered, the exception is caught, but code flow does not return to the loop in the try block. You will not see any numbers printed that come after 2.
You can use retryWhen instead of catch to be able to restart the flow. To do it on demand like you want, maybe this strategy could be used (I didn't test it):
class MarketViewModel #Inject constructor(repo: MarketRepository) : ViewModel() {
private val retry = MutableSharedFlow<Unit>()
val marketState: LiveData<State<Market>> =
repo.refreshMarket()
.map { State.Success(it) as State<T> }
.retryWhen { error, _ ->
emit(State.Error(error))
retry.first() // await next value from retry flow
true
}
.stateIn(vmScope, SharingStarted.WhileSubscribed(5000), State.Loading())
.asLiveData()
fun retry() {
retry.tryEmit(Unit)
}
}

Kotlin Coroutine Flow: When does wasting resource happen when using Flow

I am reading this article to fully understand the dos and donts of using Flow while comparing it to my implementation, but I can't grasp clearly how to tell if you are wasting resource when using Flow or flow builder. When is the time a flow is being release/freed in memory and when is the time that you are wasting resource like accidentally creating multiple instances of flow and not releasing them?
I have a UseCase class that invokes a repository function that returns Flow. In my ViewModel this is how it looks like.
class AssetViewModel constructor(private val getAssetsUseCase: GetAssetsUseCase) : BaseViewModel() {
private var job: Job? = null
private val _assetState = defaultMutableSharedFlow<AssetState>()
fun getAssetState() = _assetState.asSharedFlow()
init {
job = viewModelScope.launch {
while(true) {
if (lifecycleState == LifeCycleState.ON_START || lifecycleState == LifeCycleState.ON_RESUME)
fetchAssets()
delay(10_000)
}
}
}
fun fetchAssets() {
viewModelScope.launch {
withContext(Dispatchers.IO) {
getAssetsUseCase(
AppConfigs.ASSET_BASE_URL,
AppConfigs.ASSET_PARAMS,
AppConfigs.ASSET_SIZES[AppConfigs.ASSET_LIMIT_INDEX]
).onEach {
when(it){
is RequestStatus.Loading -> {
_assetState.tryEmit(AssetState.FetchLoading)
}
is RequestStatus.Success -> {
_assetState.tryEmit(AssetState.FetchSuccess(it.data.assetDataDomain))
}
is RequestStatus.Failed -> {
_assetState.tryEmit(AssetState.FetchFailed(it.message))
}
}
}.collect()
}
}
}
override fun onCleared() {
job?.cancel()
super.onCleared()
}
}
The idea here is we are fetching data from remote every 10 seconds while also allowing on demand fetch of data via UI.
Just a typical useless UseCase class
class GetAssetsUseCase #Inject constructor(
private val repository: AssetsRepository // Passing interface not implementation for fake test
) {
operator fun invoke(baseUrl: String, query: String, limit: String): Flow<RequestStatus<AssetDomain>> {
return repository.fetchAssets(baseUrl, query, limit)
}
}
The concrete implementation of repository
class AssetsRepositoryImpl constructor(
private val service: CryptoService,
private val mapper: AssetDtoMapper
) : AssetsRepository {
override fun fetchAssets(
baseUrl: String,
query: String,
limit: String
) = flow {
try {
emit(RequestStatus.Loading())
val domainModel = mapper.mapToDomainModel(
service.getAssetItems(
baseUrl,
query,
limit
)
)
emit(RequestStatus.Success(domainModel))
} catch (e: HttpException) {
emit(RequestStatus.Failed(e))
} catch (e: IOException) {
emit(RequestStatus.Failed(e))
}
}
}
After reading this article which says that using stateIn or sharedIn will improve the performance when using a flow, it seems that I am creating new instances of the same flow on-demand. But there is a limitation as the stated approach only works for variable and not function that returns Flow.

stateIn and shareIn can save resources if there are multiple observers, by avoiding redundant fetching. And in your case, you could set it up to automatically pause the automatic re-fetching when there are no observers. If, on the UI side you use repeatOnLifecycle, then it will automatically drop your observers when the view is off screen and then you will avoid wasted fetches the user will never see.
I think it’s not often described this way, but often the multiple observers are just observers coming from the same Activity or Fragment class after screen rotations or rapidly switching between fragments. If you use WhileSubscribed with a timeout to account for this, you can avoid having to restart your flow if it’s needed again quickly.
Currently you emit to from an external coroutine instead of using shareIn, so there’s no opportunity to pause execution.
I haven't tried to create something that supports both automatic and manual refetching. Here's a possible strategy, but I haven't tested it.
private val refreshRequest = Channel<Unit>(Channel.CONFLATED)
fun fetchAssets() {
refreshRequest.trySend(Unit)
}
val assetState = flow {
while(true) {
getAssetsUseCase(
AppConfigs.ASSET_BASE_URL,
AppConfigs.ASSET_PARAMS,
AppConfigs.ASSET_SIZES[AppConfigs.ASSET_LIMIT_INDEX]
).map {
when(it){
is RequestStatus.Loading -> AssetState.FetchLoading
is RequestStatus.Success -> AssetState.FetchSuccess(it.data.assetDataDomain)
is RequestStatus.Failed -> AssetState.FetchFailed(it.message)
}
}.emitAll()
withTimeoutOrNull(100L) {
// drop any immediate or pending manual request
refreshRequest.receive()
}
// Wait until a fetch is manually requested or ten seconds pass:
withTimeoutOrNull(10000L - 100L) {
refreshRequest.receive()
}
}
}.shareIn(viewModelScope, SharingStarted.WhileSubscribed(4000L), replay = 1)

To this I would recommend not using flow as the return type of the usecase function and the api call must not be wrapped inside a flow builder.
Why:
The api call actually is happening once and then again after an interval it is triggered by the view model itself, returning flow from the api caller function will be a bad usage of powerful tool that is actually meant to be called once and then it must be self-reliant, it should emit or pump in the data till the moment it has a subscriber/collector.
One usecase you can consider when using flow as return type from the room db query call, it is called only once and then the room emits data into it till the time it has subscriber.
.....
fun fetchAssets() {
viewModelScope.launch {
// loading true
val result=getusecase(.....)
when(result){..process result and emit on state..}
// loading false
}
}
.....
suspend operator fun invoke(....):RequestStatus<AssetDomain>{
repository.fetchAssets(baseUrl, query, limit)
}
.....
override fun fetchAssets(
baseUrl: String,
query: String,
limit: String
):RequestStatus {
try {
//RequestStatus.Loading()//this can be managed in viewmodel itself
val domainModel = mapper.mapToDomainModel(
service.getAssetItems(
baseUrl,
query,
limit
)
)
RequestStatus.Success(domainModel)
} catch (e: HttpException) {
RequestStatus.Failed(e)
} catch (e: IOException) {
RequestStatus.Failed(e)
}
}

Kotlin Multiplatform Mobile: Ktor - how to cancel active coroutine (network request, background work) in Kotlin Native (iOS)?

In my project I write View and ViewModel natively and share Repository, Db, networking.
When user navigates from one screen to another, I want to cancel all network requests or other heavy background operations that are currently running in the first screen.
Example function in Repository class:
#Throws(Throwable::class)
suspend fun fetchData(): List<String>
In Android's ViewModel I can use viewModelScope to automatically cancel all active coroutines. But how to cancel those tasks in iOS app?

Lets suppose that the object session is a URLSession instance, you can cancel it by:
session.invalidateAndCancel()

I didn't find any first party information about this or any good solution, so I came up with my own. Shortly, it will require turning repository suspend functions to regular functions with return type of custom interface that has cancel() member function. Function will take action lambda as parameter. On implementation side, coroutine will be launched and reference for Job will be kept so later when it is required to stop background work interface cancel() function will cancel job.
In addition, because it is very hard to read type of error (in case it happens) from NSError, I wrapped return data with custom class which will hold error message and type. Earlier I asked related question but got no good answer for my case where ViewModel is written natively in each platform.
If you find any problems with this approach or have any ideas please share.
Custom return data wrapper:
class Result<T>(
val status: Status,
val value: T? = null,
val error: KError? = null
)
enum class Status {
SUCCESS, FAIL
}
data class KError(
val type: ErrorType,
val message: String? = null,
)
enum class ErrorType {
UNAUTHORIZED, CANCELED, OTHER
}
Custom interface
interface Cancelable {
fun cancel()
}
Repository interface:
//Convert this code inside of Repository interface:
#Throws(Throwable::class)
suspend fun fetchData(): List<String>
//To this:
fun fetchData(action: (Result<List<String>>) -> Unit): Cancelable
Repository implementation:
override fun fetchData(action: (Result<List<String>>) -> Unit): Cancelable = runInsideOfCancelableCoroutine {
val result = executeAndHandleExceptions {
val data = networkExample()
// do mapping, db operations, etc.
data
}
action.invoke(result)
}
// example of doing heavy background work
private suspend fun networkExample(): List<String> {
// delay, thread sleep
return listOf("data 1", "data 2", "data 3")
}
// generic function for reuse
private fun runInsideOfCancelableCoroutine(task: suspend () -> Unit): Cancelable {
val job = Job()
CoroutineScope(Dispatchers.Main + job).launch {
ensureActive()
task.invoke()
}
return object : Cancelable {
override fun cancel() {
job.cancel()
}
}
}
// generic function for reuse
private suspend fun <T> executeAndHandleExceptions(action: suspend () -> T?): Result<T> {
return try {
val data = action.invoke()
Result(status = Status.SUCCESS, value = data, error = null)
} catch (t: Throwable) {
Result(status = Status.FAIL, value = null, error = ErrorHandler.getError(t))
}
}
ErrorHandler:
object ErrorHandler {
fun getError(t: Throwable): KError {
when (t) {
is ClientRequestException -> {
try {
when (t.response.status.value) {
401 -> return KError(ErrorType.UNAUTHORIZED)
}
} catch (t: Throwable) {
}
}
is CancellationException -> {
return KError(ErrorType.CANCELED)
}
}
return KError(ErrorType.OTHER, t.stackTraceToString())
}
}

You probably have 3 options:
If you're using a some sort of reactive set up iOS side (e.g. MVVM) you could just choose to ignore cancellation. Cancellation will only save a minimal amount of work.
Wrap your iOS calls to shared code in an iOS reactive framework (e.g. combine) and handle cancellation using the iOS framework. The shared work would still be done, but the view won't be updated as your iOS framework is handling cancellation when leaving the screen.
Use Flow with this closable helper

Convert LiveData to RxJava observable

I have 2 views: EditText with amount (which should not be empty) and agreement checkbox (which should be checked). I also have 2 MutableLive data variables which represent states of this views inside my ViewModel.
I want to combine this 2 variables in Observables and use Observable.combineLattest to enable/disable my "Send" button.
I have found library which called android.arch.lifecycle:reactivestreams and converted my LiveData to Publishers, but I cannot use them in Observable.combineLattest because org.reactivestreams because Publisher is org.reactivestreams interface and Observable.combineLattest accept observable source.
I read some articles but they all refer to this library.
Currently I have code like this:
override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
super.onViewCreated(view, savedInstanceState)
...
dispossable = Observable.combineLatest(
LiveDataReactiveStreams.toPublisher(this, vm.amount),
LiveDataReactiveStreams.toPublisher(this, vm.isAgreementChecked),
BiFunction<String, Boolean, Boolean> { amount, isChecked ->
amount.isNotEmpty() && isChecked
})
}
Is anyone know good workaround to convert LiveData to Observable.
Thanks in advance.

As Blackbelt rightly said - instead of using Observable for combineLatest (and other operators like Zip, Debounce etc) I can use Flowable from LiveData with:
LiveDataReactiveStreams.toPublisher(/*lifecycle*/, /*observable Field*/).
So my current solution looks like this:
disposable = Flowable.combineLatest(
LiveDataReactiveStreams.toPublisher(this, vm.amount),
LiveDataReactiveStreams.toPublisher(this, vm.isAgreementChecked),
BiFunction<String, Boolean, Boolean> { amount, isChecked ->
amount.isNotEmpty() && isChecked
}).subscribe { isDataValid ->
vm.setIsDataValid(isDataValid)
}
Thanks again :)

An alternative solution might be (I needed this because WorkManager only returns LiveData):
fun getWorkData(): Flowable<List<WorkInfo>> {
val workDataLiveData = WorkManager.getInstance().getWorkInfosByTagLiveData("TAG")
Flowable.create({emitter ->
val observer = Observer> { emitter.onNext(it) }
val disposable = disposeInUiThread { workDataLiveData.removeObserver(observer) }
emitter.setDisposable(disposable)
workDataLiveData.observeForever(observer)
}, BackpressureStrategy.LATEST)
}
private fun disposeInUiThread(action: Action): Disposable {
return Disposables.fromAction {
if (Looper.getMainLooper() == Looper.myLooper()) {
action.run()
} else {
val inner = AndroidSchedulers.mainThread().createWorker()
inner.schedule {
try {
action.run()
} catch (e: Exception) {
Timber.e(e, "Could not unregister receiver in UI Thread")
}
inner.dispose()
}
}
}
}

Making synchronous calls to Cloud Firestore when running off the main thread

I am building an app based off of the Android Clean Architecture Kotlin version (https://github.com/android10/Android-CleanArchitecture-Kotlin).
Using this architecture, each time you want to invoke a use case, a Kotlin coroutine is launched and the result is posted in the main thread. This is achieved by this code:
abstract class UseCase<out Type, in Params> where Type : Any {
abstract suspend fun run(params: Params): Either<Failure, Type>
fun execute(onResult: (Either<Failure, Type>) -> Unit, params: Params) {
val job = async(CommonPool) { run(params) }
launch(UI) { onResult.invoke(job.await()) }
}
In his example architecture, Mr. Android10 uses Retrofit to make a synchronous api call inside the kotlin couroutine. For example:
override fun movies(): Either<Failure, List<Movie>> {
return when (networkHandler.isConnected) {
true -> request(service.movies(), { it.map { it.toMovie() } }, emptyList())
false, null -> Left(NetworkConnection())
}
}
private fun <T, R> request(call: Call<T>, transform: (T) -> R, default: T): Either<Failure, R> {
return try {
val response = call.execute()
when (response.isSuccessful) {
true -> Right(transform((response.body() ?: default)))
false -> Left(ServerError())
}
} catch (exception: Throwable) {
Left(ServerError())
}
}
'Either' represents a disjoint type, meaning the result will either be a Failure or the object of type T you want.
His service.movies() method is implemented like so (using retrofit)
#GET(MOVIES) fun movies(): Call<List<MovieEntity>>
Now here is my question. I am replacing retrofit with Google Cloud Firestore. I know that currently, Firebase/Firestore is an all async library. I want to know if anyone knows of a method more elegant way of making a synchronous API call to Firebase.
I implemented my own version of Call:
interface Call<T: Any> {
fun execute(): Response<T>
data class Response<T>(var isSuccessful: Boolean, var body: T?, var failure: Failure?)
}
and my API call is implemented here
override fun movieList(): Call<List<MovieEntity>> = object : Call<List<MovieEntity>> {
override fun execute(): Call.Response<List<MovieEntity>> {
return movieListResponse()
}
}
private fun movieListResponse(): Call.Response<List<MovieEntity>> {
var response: Call.Response<List<MovieEntity>>? = null
FirebaseFirestore.getInstance().collection(DataConfig.databasePath + MOVIES_PATH).get().addOnCompleteListener { task ->
response = when {
!task.isSuccessful -> Call.Response(false, null, Failure.ServerError())
task.result.isEmpty -> Call.Response(false, null, MovieFailure.ListNotAvailable())
else -> Call.Response(true, task.result.mapTo(ArrayList()) { MovieEntity.fromSnapshot(it) }, null)
}
}
while (response == null)
Thread.sleep(50)
return response as Call.Response<List<MovieEntity>>
}
Of course, the while loop at the end bothers me. Is there any other, more elegant ways, to wait for the response to be assigned before returning from the movieListResponse method?
I tried calling await() on the Task that is returned from the Firebase get() method, but the movieListResponse method would return immediately anyway. Thanks for the help!

So I found what I was looking for in the Google Tasks API: "If your program is already executing in a background thread you can block a task to get the result synchronously and avoid callbacks" https://developers.google.com/android/guides/tasks#blocking
So my previous problematic code becomes:
private fun movieListResponse(): Call.Response<List<MovieEntity>> {
return try {
val taskResult = Tasks.await(FirebaseFirestore.getInstance().
collection(DataConfig.databasePath + MOVIES_PATH).get(), 2, TimeUnit.SECONDS)
Call.Response(true, taskResult.mapTo(ArrayList()) { MovieEntity.fromSnapshot(it) }, null)
} catch (e: ExecutionException) {
Call.Response(false, null, Failure.ServerError())
} catch (e: InterruptedException) {
Call.Response(false, null, Failure.InterruptedError())
} catch (e: TimeoutException) {
Call.Response(false, null, Failure.TimeoutError())
}
}
Note I no longer need my Thread.sleep while loop.
This code should only be run in a background thread/kotlin coroutine.

This is overengineered, there are several layers trying to do the same thing. I suggest you go back a few steps, undo the abstractions and get into the mood of using coroutines directly. Implement a suspend fun according to this template. You don't need the crutches of Either, handle exceptions in the most natural way: a try-catch around a suspend fun call.
You should end up with a signature as follows:
suspend fun movieList(): List<MovieEntity>
Call site:
launch(UI) {
try {
val list = movieList()
...
} catch (e: FireException) {
// handle
}
}

That's is not the way how firebase works. Firebase is based on callback.
I recommend architecture component's livedata.
Please check the following example.
here is a link: https://android.jlelse.eu/android-architecture-components-with-firebase-907b7699f6a0