Develop Reference

Why does Flow (kotlinx.coroutines.flow) not working with Retry even though I manually set as null in Android?

So basically, on the snackbar action button, I want to Retry API call if user click on Retry.
I have used core MVVM architecture with Flow. I even used Flow between Viewmodel and view as well. Please note that I was already using livedata between view and ViewModel, but now the requirement has been changed and I have to use Flow only. Also I'm not using and shared or state flow, that is not required.
Code:
Fragment:
private fun apiCall() {
viewModel.fetchUserReviewData()
}
private fun setObservers() {
lifecycleScope.launch {
viewModel.userReviewData?.collect {
LogUtils.d("Hello it: " + it.code)
setLoadingState(it.state)
when (it.status) {
Resource.Status.ERROR -> showErrorSnackBarLayout(-1, it.message, {
// Retry action button logic
viewModel.userReviewData = null
apiCall()
})
}
}
}
Viewmodel:
var userReviewData: Flow<Resource<ReviewResponse>>? = emptyFlow<Resource<ReviewResponse>>()
fun fetchUserReviewData() {
LogUtils.d("Hello fetchUserReviewData: " + userReviewData)
userReviewData = flow {
emit(Resource.loading(true))
repository.getUserReviewData().collect {
emit(it)
}
}
}
EDIT in ViewModel:
// var userReviewData = MutableStateFlow<Resource<ReviewResponse>>(Resource.loading(false))
var userReviewData = MutableSharedFlow<Resource<ReviewResponse>>()
fun fetchUserReviewData() {
viewModelScope.launch {
userReviewData.emit(Resource.loading(true))
repository.getUserReviewData().collect {
userReviewData.emit(it)
}
}
}
override fun onCreate() {}
}
EDIT in Activity:
private fun setObservers() {
lifecycleScope.launchWhenStarted {
viewModel.userReviewData.collect {
setLoadingState(it.state)
when (it.status) {
Resource.Status.SUCCESS ->
if (it.data != null) {
val reviewResponse: ReviewResponse = it.data
if (!AppUtils.isNull(reviewResponse)) {
setReviewData(reviewResponse.data)
}
}
Resource.Status.ERROR -> showErrorSnackBarLayout(it.code, it.message) {
viewModel.fetchUserReviewData()
}
}
}
}
}
Now, I have only single doubt, should I use state one or shared one? I saw Phillip Lackener video and understood the difference, but still thinking what to use!
The thing is we only support Portrait orientation, but what in future requirement comes? In that case I think I have to use state one so that it can survive configuration changes! Don't know what to do!

Because of the single responsibility principle, the ViewModel alone should be updating its flow to show the latest requested data, rather than having to cancel the ongoing request and resubscribe to a new one from the Fragment side.
Here is one way you could do it. Use a MutableSharedFlow for triggering fetch requests and flatMapLatest to restart the downstream flow on a new request.
A Channel could also be used as a trigger, but it's a little more concise with MutableSharedFlow.
//In ViewModel
private val fetchRequest = MutableSharedFlow<Unit>(replay = 1, BufferOverflow.DROP_OLDEST)
var userReviewData = fetchRequest.flatMapLatest {
flow {
emit(Resource.loading(true))
emitAll(repository.getUserReviewData())
}
}.shareIn(viewModelScope, SharingStarted.WhlieSubscribed(5000), 1)
fun fetchUserReviewData() {
LogUtils.d("Hello fetchUserReviewData: " + userReviewData)
fetchRequest.tryEmit(Unit)
}
Your existing Fragment code above should work with this, but you no longer need the ?. null-safe call since the flow is not nullable.
However, if the coroutine does anything to views, you should use viewLifecycle.lifecycleScope instead of just lifecycleScope.

How to cancel a combine of flows when one of them emits a certain value?

I am doing multiple network requests in parallel and monitoring the result using a Stateflow.
Each network request is done in a separate flow, and I use combine to push the latest status on my Stateflow. Here's my code:
Repo class:
fun networkRequest1(id: Int): Flow<Resource<List<Area>>> =
flow {
emit(Resource.Loading())
try {
val areas = retrofitInterface.getAreas(id)
emit(Resource.Success(areas))
} catch (throwable: Throwable) {
emit(
Resource.Error()
)
)
}
}
fun networkRequest2(id: Int): Flow<Resource<List<Area>>> = //same code as above for simplicity
fun networkRequest3(id: Int): Flow<Resource<List<Area>>> = //same code as above for simplicity
fun networkRequest4(id: Int): Flow<Resource<List<Area>>> = //same code as above for simplicity
ViewModel class:
val getDataCombinedStateFlow: StateFlow<Resource<HashMap<String, Resource<out List<Any>>>>?> =
getDataTrigger.flatMapLatest {
withContext(it) {
combine(
repo.networkRequest1(id: Int),
repo.networkRequest2(id: Int),
repo.networkRequest3(id: Int),
repo.networkRequest4(id: Int)
) { a,
b,
c,
d
->
hashMapOf(
Pair("1", a),
Pair("2",b),
Pair("3", c),
Pair("4", d),
)
}.flatMapLatest {
val progress = it
var isLoading = false
flow<Resource<HashMap<String, Resource<out List<Any>>>>?> {
emit(Resource.Loading())
progress.forEach { (t, u) ->
if (u is Resource.Error) {
emit(Resource.Error(error = u.error!!))
// I want to cancel here, as I no longer care if 1 request fails
return#flow
}
if (u is Resource.Loading) {
isLoading = true
}
}
if (isLoading) {
emit(Resource.Loading())
return#flow
}
if (!isLoading) {
emit(Resource.Success(progress))
}
}
}
}
}.stateIn(viewModelScope, SharingStarted.Lazily, null)
View class:
viewLifecycleOwner.lifecycleScope.launchWhenCreated() {
viewModel.getDataCombinedStateFlow.collect {
val result = it ?: return#collect
binding.loadingErrorState.apply {
if (result is Resource.Loading) {
//show smth
}
if (result is Resource.Error) {
//show error msg
}
if (result is Resource.Success) {
//done
}
}
}
}
I want to be able to cancel all work after a Resource.Error is emitted, as I no longer want to wait or do any related work for the response of other API calls in case one of them fails.
How can I achieve that?
I tried to cancel the collect, but the flows that build the Stateflow keep working and emmit results. I know that they won't be collected but still, I find this a waste of resources.

I think this whole situation is complicated by the fact that you have source flows just to precede what would otherwise be suspend functions with a Loading state. So then you're having to merge them and filter out various loading states, and your end result flow keeps repeatedly emitting a loading state until all the sources are ready.
If you instead have basic suspend functions for your network operations, for example:
suspend fun networkRequest1(id: Int): List<Area> =
retrofitInterface.getAreas(id)
Then your view model flow becomes simpler. It doesn't make sense to use a specific context just to call a flow builder function, so I left that part out. (I'm also confused as to why you have a flow of CoroutineContexts.)
I also think it's much cleaner if you break out the request call into a separate function.
private fun makeParallelRequests(id: Int): Map<String, Resource<out List<Any>> = coroutineScope {
val results = listOf(
async { networkRequest1(id) },
async { networkRequest2(id) },
async { networkRequest2(id) },
async { networkRequest4(id) }
).awaitAll()
.map { Resource.Success(it) }
listOf("1", "2", "3", "4").zip(results).toMap()
}
val dataCombinedStateFlow: StateFlow<Resource<Map<String, Resource<out List<Any>>>>?> =
getDataTrigger.flatMapLatest {
flow {
emit(Resource.Loading())
try {
val result = makeParallelRequests(id)
emit(Resource.Success(result))
catch (e: Throwable) {
emit(Resource.Error(e))
}
}
}

I agree with #Tenfour04 that those nested flows are overly complicated and there are several ways to simplify this (#Tenfour04's solution is a good one).
If you don't want to rewrite everything then you can fix that one line that breaks the structured concurrency:
.stateIn(viewModelScope, SharingStarted.Lazily, null)
With this the whole ViewModel flow is started in the ViewModel's scope while the view starts the collect from a separate scope (viewLifecycleOwner.lifecycleScope which would be the Fragment / Activity scope).
If you want to cancel the flow from the view, you need to use either the same scope or expose a cancel function that would cancel the ViewModel's scope.
If you want to cancel the flow from the ViewModel itself (at the return#flow statement) then you can simply add:
viewModelScope.cancel()

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)
}
}

How to pause/stop collecting/emitting data in a Flow while app minimised?

I have a UseCase and remote repository that return Flow in a loop and I collect the result of UseCase in the ViewModel like this:
viewModelScope.launch {
useCase.updatePeriodically().collect { result ->
when (result.status) {
Result.Status.ERROR -> {
errorModel.value = result.errorModel
}
Result.Status.SUCCESS -> {
items.value = result.data
}
Result.Status.LOADING -> {
loading.value = true
}
}
}
}
the problem is when the app is in the background (minimized) flow continues working. so can I pause it when the app is in the background and resume it when the app comes back to the foreground?
and also I don't want to observe the data in my view (fragment or activity).

I'd play around with the stateIn operator and the way I'm currently consuming the flow in the view.
Something like:
val state = useCase.updatePeriodically().map { ... }
.stateIn(viewModelScope, SharingStarted.WhileSubscribed, initialValue)
And consume it from the View like:
viewModel.flowWithLifecycle(this, Lifecycle.State.STARTED)
.onEach {
}
.launchIn(lifecycleScope)
For other potential ways on how to collect flows from the UI: https://medium.com/androiddevelopers/a-safer-way-to-collect-flows-from-android-uis-23080b1f8bda
EDIT:
If you don't want to consume it from the view, you still have to signal for the VM that your View is in the background currently.
Something like:
private var job: Job? = null
fun start(){
job = viewModelScope.launch {
state.collect { ... }
}
}
fun stop(){
job?.cancel()
}

Even if the viewModelScope is cancelled, the flow will continue to collect because it is not cooperative to cancellation.
To make a flow cancellable, you can do one of the following things:
In the collect lambda, call currentCoroutineContext().ensureActive() to make sure the context in which the flow is being collected is still active. This will however throw a CancellableException, which you will need to catch, if the coroutine scope was cancelled already (viewModel scope for your case.)
You can use cancellable() operator as follows:
myFlow.cancellable().collect { //do stuff here.. }
And you can call cancel() whenever you want to cancel the flow.
For official documentation on cancelling the flow see:
https://kotlinlang.org/docs/flow.html#flow-cancellation-checks

I believe you want something like this
lifecycleScope.launch {
repeatOnLifecycle(Lifecycle.State.STARTED) {
state.collect {
}
}
}
Here's an execellent article on repeatOnLifecyle: https://medium.com/androiddevelopers/repeatonlifecycle-api-design-story-8670d1a7d333

Kotlin Coroutines - Suspend function returning a Flow runs forever

I am making a network repository that supports multiple data retrieval configs, therefore I want to separate those configs' logic into functions.
However, I have a config that fetches the data continuously at specified intervals. Everything is fine when I emit those values to the original Flow. But when I take the logic into another function and return another Flow through it, it stops caring about its coroutine scope. Even after the scope's cancelation, it keeps on fetching the data.
TLDR: Suspend function returning a flow runs forever when currentCoroutineContext is used to control its loop's termination.
What am I doing wrong here?
Here's the simplified version of my code:
Fragment calling the viewmodels function that basically calls the getData()
lifecycleScope.launch {
viewModel.getLatestDataList()
}
Repository
suspend fun getData(config: MyConfig): Flow<List<Data>>
{
return flow {
when (config)
{
CONTINUOUS ->
{
//It worked fine when fetchContinuously was ingrained to here and emitted directly to the current flow
//And now it keeps on running eternally
fetchContinuously().collect { updatedList ->
emit(updatedList)
}
}
}
}
}
//Note logic of this function is greatly reduced to keep the focus on the problem
private suspend fun fetchContinuously(): Flow<List<Data>>
{
return flow {
while (currentCoroutineContext().isActive)
{
val updatedList = fetchDataListOverNetwork().await()
if (updatedList != null)
{
emit(updatedList)
}
delay(refreshIntervalInMs)
}
Timber.i("Context is no longer active - terminating the continuous-fetch coroutine")
}
}
private suspend fun fetchDataListOverNetwork(): Deferred<List<Data>?> =
withContext(Dispatchers.IO) {
return#withContext async {
var list: List<Data>? = null
try
{
val response = apiService.getDataList().execute()
if (response.isSuccessful && response.body() != null)
{
list = response.body()!!.list
}
else
{
Timber.w("Failed to fetch data from the network database. Error body: ${response.errorBody()}, Response body: ${response.body()}")
}
}
catch (e: Exception)
{
Timber.w("Exception while trying to fetch data from the network database. Stacktrace: ${e.printStackTrace()}")
}
finally
{
return#async list
}
list //IDE is not smart enough to realize we are already returning no matter what inside of the finally block; therefore, this needs to stay here
}
}

I am not sure whether this is a solution to your problem, but you do not need to have a suspending function that returns a Flow. The lambda you are passing is a suspending function itself:
fun <T> flow(block: suspend FlowCollector<T>.() -> Unit): Flow<T> (source)
Here is an example of a flow that repeats a (GraphQl) query (simplified - without type parameters) I am using:
override fun query(query: Query,
updateIntervalMillis: Long): Flow<Result<T>> {
return flow {
// this ensures at least one query
val result: Result<T> = execute(query)
emit(result)
while (coroutineContext[Job]?.isActive == true && updateIntervalMillis > 0) {
delay(updateIntervalMillis)
val otherResult: Result<T> = execute(query)
emit(otherResult)
}
}
}

I'm not that good at Flow but I think the problem is that you are delaying only the getData() flow instead of delaying both of them.
Try adding this:
suspend fun getData(config: MyConfig): Flow<List<Data>>
{
return flow {
when (config)
{
CONTINUOUS ->
{
fetchContinuously().collect { updatedList ->
emit(updatedList)
delay(refreshIntervalInMs)
}
}
}
}
}
Take note of the delay(refreshIntervalInMs).