Develop Reference

Koltin Flow is repeating execution using flatMapMerge

I was trying to implement an approach to fetch products from two Data sources (Room & FirebaseFirestore) using Flows.
It was working fine until I noticed that the debugger was returning to the same break point infinitely. When the execution of "ViewmMdel.insertProducts(products)" ends, the debugger returns to Repository.getProducts(//) & repeats.
I changed the approach using only suspending functions & coroutines & works fine but I am curious about how I must to use Flows to implement this approach.
Maybe is only that flatMapMerge is in preview version.
Thanks in advance :D
This one is the implementation:
ViewModel:
fun getProductNames(companyName: String) {
viewModelScope.launch {
repository.getProducts(companyName).catch {
_event.value = AddSaleEvents.ShouldShowLoading(false)
_event.value = AddSaleEvents.ProductsFailureResponse(it.message.toString())
}.collect { products ->
productsList = products
if (products != emptyList<Product>()) {
_event.value = AddSaleEvents.ShouldShowLoading(false)
_event.value = AddSaleEvents.ProductsSuccessfulResponse(products)
insertProducts(products)
} else {
_event.value = AddSaleEvents.ShouldShowLoading(false)
_event.value = AddSaleEvents.ProductsSuccessfulResponse(products)
}
}
}
}
Repository:
#OptIn(FlowPreview::class)
override suspend fun getProducts(compnayName: String): Flow<List<Product>> {
return localDataSource.getProducts().flatMapMerge { list -> // LINE RUNNING INFINITELY
getProductsFromFirebase(list, compnayName)
}.flowOn(Dispatchers.IO).catch {
Log.d("Error", it.message.toString())
}
}
private fun getProductsFromFirebase(products: List<Product>, compnayName: String) = flow {
if (products.isEmpty()) {
remoteDataSource.getProducts(compnayName).collect {
emit(it)
}
} else {
emit(products)
}
}
LocalDataSource with Room:
override suspend fun getProducts(): Flow<List<Product>> = saleDao.getProducts()
Firebase Data Source:
override suspend fun getProducts(company: String): Flow<List<Product>> = flow {
val response = fireStore.collection("products").whereEqualTo("company", company).get()
response.await()
if (response.isSuccessful && !response.result.isEmpty) {
emit(response.result.toObjects(FirebaseProduct::class.java).toEntity())
}
}.catch {
Log.d("Error", it.message.toString())
}
How can I chain the response of a flow to trigger another one inside the MVVM Architecture + Clean Architecture?
6 if it is possible, I want to understand the reason the code is repeating infinitely.

Looks like insertProducts(products) triggers room's DAO.
So localDataSource.getProducts() is a observable read query
Observable queries are read operations that emit new values whenever there are changes to any of the tables that are referenced by the query.
Try to change LocalDataSource
interface SaleDao {
// fun getProducts(): Flow<List<Product>>
suspend fun getProducts(): List<Product>
}

Kotlin Flow collect takes a long time

I have a local database in my Android app. There is a function that takes some data from server and updates local database.
When this function is running, if I collect a list from local database by returning Flow, it takes unusual time to finish.
I don't have any problem with LiveData, it works well but Flow doesn't.
this is my dao :
#Transaction
#Query("SELECT * FROM tbl WHERE id=:id")
fun getData(id: String): Flow<Entity?>
repo :
fun getData(id: String): Flow<Entity?> {
return dao.getData(id).map { it?.toModel() }
}
fragment :
lifecycleScope.launch() {
repo.getData(args.id)
.flowWithLifecycle(viewLifecycleOwner.lifecycle)
.distinctUntilChanged()
.collect { data ->
data?.let {
setData(data)
}
}
}

Try to add .flowOn(Dispatchers.IO) in you repository function after map like this:
Repository
fun getData(id: String): Flow<Entity?> {
return dao.getData(id)
.map { it?.toModel() }
.flowOn(Dispatchers.IO)
}
I think the problem is that you delay the main thread with your heavy function operation (map) on the flow.

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).

How to handle database call errors using Flows

Usually I'm returning from my dao suspend function:
#Dao
interface DataDao {
#Query("SELECT * FROM data")
fun getAllData(): List<Data>
}
And handle the call within the repository:
class DataRepository(
private val dataDao: DataDao
) {
fun getAllData(): Flow<DataState> = flow {
val cacheResult = safeDatabaseCall(dispatcher = Dispatchers.IO) { dataDao.getAllData() }
//handle cacheResult, convert to DataState, emit DataState values
}.flowOn(Dispatchers.IO)
}
With generic fun:
suspend fun <T> safeDatabaseCall(
dispatcher: CoroutineDispatcher,
cacheCall: suspend () -> T?
): CacheResult<T?> {
return withContext(dispatcher) {
try {
withTimeout(10000L) {
CacheResult.Success(cacheCall.invoke())
}
} catch (t: Throwable) {
when (t) {
is TimeoutCancellationException -> {
CacheResult.Error("Timeout error")
}
else -> {
CacheResult.Error("Unknown error")
}
}
}
}
}
The problem is that I want return fun getAllData(): Flow<List<Data>> instead of fun getAllData(): List<Data> In order to get immediate updates, But if I'm returning Flow from the Dao, I can't handle the call with safe call and catch errors.
I thought about collecting the data, but if i'm collecting the data the call already done without error handling
Basically I need the cache result return CacheResult<Data> and not CacheResult<Flow<Data>>
How can I solve the problem And make a generic safeDatabaseCall while returning Flow from Dao?

So if I understand correctly you just want to handle the query and return of information safely in a flow. My only question is around the types. I can sorta assume Data DataState and CacheResult are not the same types so I use a "magic" function that converts the intermediary values to the correct one. You will need to adjust accordingly
class DataRepository(
private val dataDao: DataDao
) {
fun getAllData(): Flow<DataState> = flow {
val result = safeDatabaseCall(dispatcher = Dispatchers.IO) {
dataDao.getAllData()
}
// Emit the result
emit(result)
}.catch { t : Throwable ->
// Do our transformation like before
val result = when (t) {
is TimeoutCancellationException -> {
CacheResult.Error("Timeout error")
}
else -> {
CacheResult.Error("Unknown error")
}
}
// And because catch is actually extending a FlowCollector
// We can emit the result in the stream
emit(result)
}.map { cacheResult ->
convertToDataOrDataState(cacheResult)
}
You shouldn't need flowOn with a dispatcher here since the work inside this flow doesn't require thread dispatching
to Dispatcher.IO. The code we are putting in our flow, is purely exception handling and invoking a function. The only place that seems to require any manual dispatch changing is, safeDatabaseCall(). I am not familiar with this function but if it does exist and takes a dispatcher for the result of actualing making the db calls on an IO thread, then all should be good without flowOn. Otherwise you will be switching dispatchers from original dispatcher -> IO and then to IO again. It's not much but the extra no-op context switch doesn't add anything other than confusion later on.
The flow itself traps any upstream issues and you then make them part of the resulting flow

How to call again LiveData Coroutine Block

I'm using LiveData's version "androidx.lifecycle:lifecycle-livedata-ktx:2.2.0-alpha05". Once my LiveData block executes successfully I want to explicitly trigger it to execute again, e.g.
I navigate to a fragment
User's data loads
I click delete btn while being in the same fragment
User's data should refresh
I have a fragment where I observe my LiveData, a ViewModel with LiveData and Repository:
ViewModel:
fun getUserLiveData() = liveData(Dispatchers.IO) {
val userData = usersRepo.getUser(userId)
emit(userData)
}
Fragment:
viewModel.getUserLiveData.observe(viewLifecycleOwner,
androidx.lifecycle.Observer {..
Then I'm trying to achieve desired behaviour like this:
viewModel.deleteUser()
viewModel.getUserLiveData()
According to the documentation below LiveData block won't execute if it has completed successfully and if I put a while(true) inside the LiveData block, then my data refreshes, however I don't want this to do since I need to update my view reactively.
If the [block] completes successfully or is cancelled due to reasons other than [LiveData]
becoming inactive, it will not be re-executed even after [LiveData] goes through active
inactive cycle.
Perhaps I'm missing something how I can reuse the same LiveDataScope to achieve this? Any help would be appreciated.

To do this with liveData { .. } block you need to define some source of commands and then subscribe to them in a block. Example:
MyViewModel() : ViewModel() {
val commandsChannel = Channel<Command>()
val liveData = livedata {
commandsChannel.consumeEach { command ->
// you could have different kind of commands
//or emit just Unit to notify, that refresh is needed
val newData = getSomeNewData()
emit(newData)
}
}
fun deleteUser() {
.... // delete user
commandsChannel.send(RefreshUsersListCommand)
}
}
Question you should ask yourself: Maybe it would be easier to use ordinary MutableLiveData instead, and mutate its value by yourself?
livedata { ... } builder works well, when you can collect some stream of data (like a Flow / Flowable from Room DB) and not so well for plain, non stream sources, which you need to ask for data by yourself.

I found a solution for this. We can use switchMap to call the LiveDataScope manually.
First, let see the official example for switchMap:
/**
* Here is an example class that holds a typed-in name of a user
* `String` (such as from an `EditText`) in a [MutableLiveData] and
* returns a `LiveData` containing a List of `User` objects for users that have
* that name. It populates that `LiveData` by requerying a repository-pattern object
* each time the typed name changes.
* <p>
* This `ViewModel` would permit the observing UI to update "live" as the user ID text
* changes.
**/
class UserViewModel: AndroidViewModel {
val nameQueryLiveData : MutableLiveData<String> = ...
fun usersWithNameLiveData(): LiveData<List<String>> = nameQueryLiveData.switchMap {
name -> myDataSource.usersWithNameLiveData(name)
}
fun setNameQuery(val name: String) {
this.nameQueryLiveData.value = name;
}
}
The example was very clear. We just need to change nameQueryLiveData to your own type and then combine it with LiveDataScope. Such as:
class UserViewModel: AndroidViewModel {
val _action : MutableLiveData<NetworkAction> = ...
fun usersWithNameLiveData(): LiveData<List<String>> = _action.switchMap {
action -> liveData(Dispatchers.IO){
when (action) {
Init -> {
// first network request or fragment reusing
// check cache or something you saved.
val cache = getCache()
if (cache == null) {
// real fecth data from network
cache = repo.loadData()
}
saveCache(cache)
emit(cache)
}
Reload -> {
val ret = repo.loadData()
saveCache(ret)
emit(ret)
}
}
}
}
// call this in activity, fragment or any view
fun fetchData(ac: NetworkAction) {
this._action.value = ac;
}
sealed class NetworkAction{
object Init:NetworkAction()
object Reload:NetworkAction()
}
}

First add implementation "androidx.lifecycle:lifecycle-viewmodel-ktx:2.2.0" to your gradle file. Make your ViewModel as follows:
MyViewModel() : ViewModel() {
val userList = MutableLiveData<MutableList<User>>()
fun getUserList() {
viewModelScope.launch {
userList.postValue(usersRepo.getUser(userId))
}
}
}
Then onserve the userList:
viewModel.sessionChartData.observe(viewLifecycleOwner, Observer { users ->
// Do whatever you want with "users" data
})
Make an extension to delete single user from userList and get notified:
fun <T> MutableLiveData<MutableList<T>>.removeItemAt(index: Int) {
if (!this.value.isNullOrEmpty()) {
val oldValue = this.value
oldValue?.removeAt(index)
this.value = oldValue
} else {
this.value = mutableListOf()
}
}
Call that extension function to delete any user and you will be notified in your Observer block after one user get deleted.
viewModel.userList.removeItemAt(5) // Index 5
When you want to get userList from data source just call viewModel.getUserList() You will get data to the observer block.

private val usersLiveData = liveData(Dispatchers.IO) {
val retrievedUsers = MyApplication.moodle.getEnrolledUsersCoroutine(course)
repo.users = retrievedUsers
roles.postValue(repo.findRolesByAll())
emit(retrievedUsers)
}
init {
usersMediator.addSource(usersLiveData){ usersMediator.value = it }
}
fun refreshUsers() {
usersMediator.removeSource(usersLiveData)
usersMediator.addSource(usersLiveData) { usersMediator.value = it }
The commands in liveData block {} doesn't get executed again.
Okay yes, the observer in the viewmodel holding activity get's triggered, but with old data.
No further network call.
Sad. Very sad. "Solution" seemed promisingly and less boilerplaty compared to the other suggestions with Channel and SwitchMap mechanisms.

You can use MediatorLiveData for this.
The following is a gist of how you may be able to achieve this.
class YourViewModel : ViewModel() {
val mediatorLiveData = MediatorLiveData<String>()
private val liveData = liveData<String> { }
init {
mediatorLiveData.addSource(liveData){mediatorLiveData.value = it}
}
fun refresh() {
mediatorLiveData.removeSource(liveData)
mediatorLiveData.addSource(liveData) {mediatorLiveData.value = it}
}
}
Expose mediatorLiveData to your View and observe() the same, call refresh() when your user is deleted and the rest should work as is.