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Emitting ui state while collecting does not update ui

This init block is in my ViewModel:
init {
viewModelScope.launch {
userRepository.login()
userRepository.user.collect {
_uiState.value = UiState.Success(it)
}
}
}
This is very similar to what's actually written on the app, but even this simple example doesn't work. After userRepository.login(), user which is a SharedFlow emits a new user state. This latest value DOES get collected within this collect function shown above, but when emitting a new uiState containing the result, the view does not get such update.
val uiState by viewModel.uiState.collectAsStateWithLifecycle()
Doing this for some reason, does not work. I suspect the issue is related to the lifecycle of the viewmodel, because when I treat the viewmodel as a singleton, this doesn't happen. It happens only when the viewmodel gets destroyed and then created a 2nd (or more) time(s).
What I'm trying to achieve is that the screen containing the view model is aware of the user state. Meaning that when I navigate to the screen, I want it to collect the latest user state, and then decide which content to show.
I also realize this is not the best pattern, most likely. I'm currently looking into a solution that holds the User as part of the app state and collecting per screen (given that it basically changes all or many screens and functionalities) so if you have any resources on an example on such implementation I'd be thankful. But I can't get my head around why this current implementation doesn't work so any light shed on the situation is much appreciated.
EDIT
This is what I have in mind for the repository
private val _user = MutableSharedFlow<User>()
override val user: Flow<User> = _user
override suspend fun login() {
delay(2000)
_user.emit(LoggedUser.aLoggedUser())
}
override suspend fun logout() {
delay(2000)
_user.emit(GuestUser)
}

For your case better to use this pattern:
ViewModel class:
sealed interface UserUiState {
object NotLoggedIn : UserUiState
object Error : UserUiState
data class LoggedIn(val user: User) : UserUiState
}
class MyViewModel #Inject constructor(
userRepository: UserRepository
) : ViewModel() {
val userUiState = userRepository.login()
.map { user ->
if (user != null)
UserUiState.LoggedIn(user)
else
UserUiState.Error
}
.stateIn(
scope = viewModelScope,
started = SharingStarted.WhileSubscribed(5_000),
initialValue = UserUiState.NotLoggedIn
)
}
Repository class:
class UserRepository {
fun login(): Flow<User?> = flow {
val user = TODO("Your code to get user")
if (isSuccess) {
emit(user)
} else {
emit(null)
}
}
}
Your screen Composable:
#Composable
fun Screen() {
val userUiState by viewModel.userUiState.collectAsStateWithLifecycle()
when (userUiState) {
is UserUiState.LoggedIn -> { TODO("Success code") }
UserUiState.NotLoggedIn -> { TODO("Waiting for login code") }
UserUiState.Error -> { TODO("Error display code") }
}
}
How it works: login() in repository returns autorized user flow which can be used in ViewModel. I use UserUiState sealed class to handle possible user states. And then I convert User value in map {} to UserUiState to display it in the UI Layer. Then Flow of UserUiState needs to be converted to StateFlow to obtain it from the Composable function, so I made stateIn.
And of course, this will solve your problem
Tell me in the comments if I got something wrong or if the code does not meet your expectations
Note: SharedFlow and StateFlow are not used in the Data Layer like you do.
EDIT:
You can emiting flow like this if you are working with network:
val user = flow of {
while (true) {
// network call to get user
delay(2000)
}
}
If you use Room you can do this in your dao.
#Query(TODO("get actual user query"))
fun getUser(): Flow<User>
It is a better way and it recommended by android developers YouTube channel

How to complete a Kotlin Flow in Android Worker

I'm investigating the use of Kotlin Flow within my current Android application
My application retrieves its data from a remote server via Retrofit API calls.
Some of these API's return 50,000 data items in 500 item pages.
Each API response contains an HTTP Link header containing the Next pages complete URL.
These calls can take up to 2 seconds to complete.
In an attempt to reduce the elapsed time I have employed a Kotlin Flow to concurrently process each page
of data while also making the next page API call.
My flow is defined as follows:
private val persistenceThreadPool = Executors.newFixedThreadPool(3).asCoroutineDispatcher()
private val internalWorkWorkState = MutableStateFlow<Response<List<MyPage>>?>(null)
private val workWorkState = internalWorkWorkState.asStateFlow()
private val myJob: Job
init {
myJob = GlobalScope.launch(persistenceThreadPool) {
workWorkState.collect { page ->
if (page == null) {
} else managePage(page!!)
}
}
}
My Recursive function is defined as follows that fetches all pages:-
private suspend fun managePages(accessToken: String, response: Response<List<MyPage>>) {
when {
result != null -> return
response.isSuccessful -> internalWorkWorkState.emit(response)
else -> {
manageError(response.errorBody())
result = Result.failure()
return
}
}
response.headers().filter { it.first == HTTP_HEADER_LINK && it.second.contains(REL_NEXT) }.forEach {
val parts = it.second.split(OPEN_ANGLE, CLOSE_ANGLE)
if (parts.size >= 2) {
managePages(accessToken, service.myApiCall(accessToken, parts[1]))
}
}
}
private suspend fun managePage(response: Response<List<MyPage>>) {
val pages = response.body()
pages?.let {
persistResponse(it)
}
}
private suspend fun persistResponse(myPage: List<MyPage>) {
val myPageDOs = ArrayList<MyPageDO>()
myPage.forEach { page ->
myPageDOs.add(page.mapDO())
}
database.myPageDAO().insertAsync(myPageDOs)
}
My numerous issues are
This code does not insert all data items that I retrieve
How do complete the flow when all data items have been retrieved
How do I complete the GlobalScope job once all the data items have been retrieved and persisted
UPDATE
By making the following changes I have managed to insert all the data
private val persistenceThreadPool = Executors.newFixedThreadPool(3).asCoroutineDispatcher()
private val completed = CompletableDeferred<Int>()
private val channel = Channel<Response<List<MyPage>>?>(UNLIMITED)
private val channelFlow = channel.consumeAsFlow().flowOn(persistenceThreadPool)
private val frank: Job
init {
frank = GlobalScope.launch(persistenceThreadPool) {
channelFlow.collect { page ->
if (page == null) {
completed.complete(totalItems)
} else managePage(page!!)
}
}
}
...
...
...
channel.send(null)
completed.await()
return result ?: Result.success(outputData)
I do not like having to rely on a CompletableDeferred, is there a better approach than this to know when the Flow has completed everything?

You are looking for the flow builder and Flow.buffer():
suspend fun getData(): Flow<Data> = flow {
var pageData: List<Data>
var pageUrl: String? = "bla"
while (pageUrl != null) {
TODO("fetch pageData from pageUrl and change pageUrl to the next page")
emitAll(pageData)
}
}
.flowOn(Dispatchers.IO /* no need for a thread pool executor, IO does it automatically */)
.buffer(3)
You can use it just like a normal Flow, iterate, etc. If you want to know the total length of the output, you should calculate it on the consumer with a mutable closure variable. Note you shouldn't need to use GlobalScope anywhere (ideally ever).

There are a few ways to achieve the desired behaviour. I would suggest to use coroutineScope which is designed specifically for parallel decomposition. It also provides good cancellation and error handling behaviour out of the box. In conjunction with Channel.close behaviour it makes the implementation pretty simple. Conceptually the implementation may look like this:
suspend fun fetchAllPages() {
coroutineScope {
val channel = Channel<MyPage>(Channel.UNLIMITED)
launch(Dispatchers.IO){ loadData(channel) }
launch(Dispatchers.IO){ processData(channel) }
}
}
suspend fun loadData(sendChannel: SendChannel<MyPage>){
while(hasMoreData()){
sendChannel.send(loadPage())
}
sendChannel.close()
}
suspend fun processData(channel: ReceiveChannel<MyPage>){
for(page in channel){
// process page
}
}
It works in the following way:
coroutineScope suspends until all children are finished. So you don't need CompletableDeferred anymore.
loadData() loads pages in cycle and posts them into the channel. It closes the channel as soon as all pages have been loaded.
processData fetches items from the channel one by one and process them. The cycle will finish as soon as all the items have been processed (and the channel has been closed).
In this implementation the producer coroutine works independently, with no back-pressure, so it can take a lot of memory if the processing is slow. Limit the buffer capacity to have the producer coroutine suspend when the buffer is full.
It might be also a good idea to use channels fan-out behaviour to launch multiple processors to speed up the computation.

How can I get the query result at once when I use Room?

I hope to get the total of all records with Room database at once. But, normally Room use background thread to query record asynchronously.
If I use getTotalOfVoiceAsLiveData() in Code A, it will return LiveData<Long>, you know that LiveData variable is lazy, maybe the result is null.
If I use getTotalOfVoice() in Code A, I will get error because I can't use return in viewModelScope.launch{ }.
How can I get the total of all records at once with Room database?
Code A
class HomeViewModel(val mApplication: Application, private val mDBVoiceRepository: DBVoiceRepository) : AndroidViewModel(mApplication) {
fun getTotalOfVoice():Long {
viewModelScope.launch {
return mDBVoiceRepository.getTotalOfVoice() //It will cause error
}
}
fun getTotalOfVoiceAsLiveData(): LiveData<Long>{
return mDBVoiceRepository.getTotalOfVoiceAsLiveData() //It's lazy, maybe the result is null.
}
}
class DBVoiceRepository private constructor(private val mDBVoiceDao: DBVoiceDao){
suspend fun getTotalOfVoice() = mDBVoiceDao.getTotalOfVoice()
fun getTotalOfVoiceAsLiveData() = mDBVoiceDao.getTotalOfVoiceAsLiveData()
}
#Dao
interface DBVoiceDao{
#Query("SELECT count(id) FROM voice_table")
suspend fun getTotalOfVoice(): Long
//When Room queries return LiveData, the queries are automatically run asynchronously on a background thread.
#Query("SELECT count(id) FROM voice_table")
fun getTotalOfVoiceAsLiveData(): LiveData<Long>
}
Add content
To Tobi: Thanks!
Why it is important to you to get the data directly?
I need to generate a filename based the total of the records, such as "untitled0", "untitled1", "untitled2"...
If I can get the query result at once, I can use the following code easyly.
Added again
I hope to record a voice by filename based the total of query records when I click Start button. You know the total of records will change when a reocrd is added or deleted!
Code B
fun getTotalOfVoice():Long {
//Get the query result at once
...
}
fun createdFileanme(){
return "untitled"+getTotalOfVoice().toString()
}
btnStart.setOnClickListener{
recordVoice(createdFileanme()) //I will record voice by filename
}
fun addRecord(){
...
}
fun deleteRecord(){
...
}
New added content
Thanks!
I think 'You should also move all of that into the viewmodel class, without LiveData ' is good way, you can see Image A and How can I get the value of a LivaData<String> at once in Android Studio? .
Do you agree with it?
Image A

Question: at once meaning synchronous or what ? if yes, what happens if the function to get the result has to take a longer time? like network call? well you can decide to do that on another thread.
What I think is for you to use a mutable Object and use the postValue function to dispatch the result to the observers. It should look something like below:
class HomeViewModel(val mApplication: Application, private val mDBVoiceRepository: DBVoiceRepository) : AndroidViewModel(mApplication) {
private val voices = MutableLiveData<Long>()
fun getTotalOfVoiceAsLiveData(): LiveData<Long> {
voices.postValue(mDBVoiceRepository.getTotalOfVoiceAsLiveData().value)
return voices;
}
}
Making use of it in your Fragment will look like below:
override fun onActivityCreated(savedInstanceState: Bundle?) {
super.onActivityCreated(savedInstanceState)
if (activity != null) {
val viewModel = ViewModelProvider(requireActivity())
viewModel.get(HomeViewModel::class.java).getTotalOfVoiceAsLiveData().observe(viewLifecycleOwner, Observer { voices: Long ? ->
voices // Sound of music ? be very free to use ...
})
}
}
Happy Coding.

I hope to get the result at once, but LiveData is lazy
Sorry to tell, but this is how the Room interface is designed.
You are right with the lazyness of the returned LiveData object. But this allows you to handle it on a different thread without having to manually handle different threads.
Based on your new information!
You basically have two options:
A) you could do the following:
load data from Room via LivaData
add observer that stores the current total amount
when the button is clicked you just read the local copy
In your View: (only one observer and one clickListener)
val totalVoiceCount: long
val viewModel = ViewModelProvider(requireActivity()).get(HomeViewModel::class.java)
viewModel.getTotalOfVoiceAsLiveData().observe(viewLifecycleOwner, Observer { totalOfVoice : Long ? ->
if (totalOfVoice != null)
totalVoiceCount = totalOfVoice
})
btnStart.setOnClickListener{
viewModel.recordVoice(totalVoiceCount)
}
In your ViewModel: (the logic and everything else)
fun recordVoice(totalVoiceCount : long){
val fileName = createdFileanme(totalVoiceCount)
// create your recording // depending on how you do this, it probably runs on a background thread anyways
}
fun createdFileName(totalVoiceCount : long){
return "untitled"+ String.valueOf(totalVoiceCount)
}
This works reliably because the LiveData has enough time to update the local copy of totalVoiceCount before the user has the chance to click the button.
B) Based on the answer in your parallel question you can of course outsource even more to a background thread. Then you also have the option to call the DAO query with a non-livedata return (as room returns non-livedata queries only on background threads). Is it worth to implement the threading suggestion of Ridcully? Not possible to answer without knowing what else is going on simultaneously... To me it seems like an overkill, but he is right that the more you do on background threads the better for your refresh rate..

You can return Deferred<Long> from viewModelScope.async. I recommend you to use:
val deferred = viewModelScope.async(Dispatchers.IO) {
return#async mDBVoiceRepository.getTotalOfVoice()
}
val value = deferred.await()
await() is suspend
Edit:
If you want to get a getter which will use in your activity or fragment
you need to write a suspend function like this:
suspend fun getTotalOfVoice(): Long {
return viewModelScope.async(Dispatchers.IO) {
return#async mDBVoiceRepository.getTotalOfVoice()
}.await()
}
But mvvm pattern allows you to create LiveData inside your ViewModel, which gives your fragment an observer.
In view model:
private val _totalOfVoiceLD: MutableLiveData<Long> = MutableLiveData()
val totalOfVoiceLD: LiveData<Long>
get() = _totalOfVoiceLD
fun updateTotalOfVoice() {
viewModelScope.launch(Dispatchers.IO) {
val totalOfVoice = mDBVoiceRepository.getTotalOfVoice()
_totalOfVoiceLD.postValue(totalOfVoice)
}
}
and in your fragment:
override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
super.onViewCreated(view, savedInstanceState)
viewModel.totalOfVoiceLD.observe(viewLifecycleOwner, Observer { totalOfVoice ->
totalOfVoiceTextView.text = totalOfVoice.toString()
})
}

You can use coroutineContext.async to get data from DB and wait for getting it's response with data by using .await function for a async dispatch.
suspend fun getAllVoices() : Long{
val awatingResults = viewModelScope.async(Dispatchers.IO) {
mDBVoiceRepository.getTotalOfVoice()
}
val records = awatingResults.await()
return records
}
It is necessary to call a Suspend function from a coroutine and
async.await() is always called in a suspended function so,
val voiceLiveData: MutableLiveData<Long> = MutableLiveData()
fun getAllVoicesFromDB() {
viewModelScope.launch(Dispatchers.IO) {
voiceLiveData.postValue(mDBVoiceRepository.getTotalOfVoice())
}
}
Now call it where ever you want to get your voice data from database and also remember do your further work inside your voiceLiveData observer where you get your response of voices :)

Live data is designed to be lazy, when the value of the live data changes internally it emits and wherever you are observing it, the onChange function will be invoked. It is designed to fire and forget.
Because room uses background thread to run the query.
You can't expect live data to behave like sharedpreference where you store key value pair.
If you want to achieve something like that.
I would suggest you to use
Paper Db or Realm.

If you need your Room result synchronously, your code should be execute in IO thread. In case of coroutines, you can use Dispatchers.IO. Your code can be changed to this to pass the error.
class HomeViewModel(val mApplication: Application, private val mDBVoiceRepository: DBVoiceRepository) : AndroidViewModel(mApplication) {
fun getTotalOfVoice():Long {
viewModelScope.launch(Dispatchers.IO) { // here
return mDBVoiceRepository.getTotalOfVoice()
}
}
}

If you must run the queries in the main thread, then:
Allow android room to execute queries in main thread.
val dbInstance = Room
.databaseBuilder(ctx, YourDBClass::class.java, "YourDBName")
.allowMainThreadQueries()
.build()
Define the dao method as follows
#Dao
interface DBVoiceDao{
#Query("SELECT count(id) FROM voice_table")
fun getTotalOfVoice(): Long
}
Access the method in the repository
fun getTotalOfVoice():Long {
return dao.getTotalOfVoice()
}

How to enqueue sequential coroutines blocks

What I'm trying to do
I have an app that's using Room with Coroutines to save search queries in the database. It's also possible to add search suggestions and later on I retrieve this data to show them on a list. I've also made it possible to "pin" some of those suggestions.
My data structure is something like this:
#Entity(
tableName = "SEARCH_HISTORY",
indices = [Index(value = ["text"], unique = true)]
)
data class Suggestion(
#PrimaryKey(autoGenerate = true)
#ColumnInfo(name = "suggestion_id")
val suggestionId: Long = 0L,
val text: String,
val type: SuggestionType,
#ColumnInfo(name = "insert_date")
val insertDate: Calendar
)
enum class SuggestionType(val value: Int) {
PINNED(0), HISTORY(1), SUGGESTION(2)
}
I have made the "text" field unique to avoid repeated suggestions with different states/types. E.g.: A suggestion that's a pinned item and a previously queried text.
My Coroutine setup looks like this:
private val parentJob: Job = Job()
private val IO: CoroutineContext
get() = parentJob + Dispatchers.IO
private val MAIN: CoroutineContext
get() = parentJob + Dispatchers.Main
private val COMPUTATION: CoroutineContext
get() = parentJob + Dispatchers.Default
And my DAOs are basically like this:
#Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(obj: Suggestion): Long
#Insert(onConflict = OnConflictStrategy.REPLACE)
suspend fun insert(objList: List<Suggestion>): List<Long>
I also have the following public functions to insert the data into the database:
fun saveQueryToDb(query: String, insertDate: Calendar) {
if (query.isBlank()) {
return
}
val suggestion = Suggestion(
text = query,
insertDate = insertDate,
type = SuggestionType.HISTORY
)
CoroutineScope(IO).launch {
suggestionDAO.insert(suggestion)
}
}
fun addPin(pin: String) {
if (pin.isBlank()) {
return
}
val suggestion = Suggestion(
text = pin,
insertDate = Calendar.getInstance(),
type = SuggestionType.PINNED
)
CoroutineScope(IO).launch {
suggestionDAO.insert(suggestion)
}
}
fun addSuggestions(suggestions: List<String>) {
addItems(suggestions, SuggestionType.SUGGESTION)
}
private fun addItems(items: List<String>, suggestionType: SuggestionType) {
if (items.isEmpty()) {
return
}
CoroutineScope(COMPUTATION).launch {
val insertDate = Calendar.getInstance()
val filteredList = items.filterNot { it.isBlank() }
val suggestionList = filteredList.map { History(text = it, insertDate = insertDate, suggestionType = suggestionType) }
withContext(IO) {
suggestionDAO.insert(suggestionList)
}
}
}
There are also some other methods, but let's focus on the ones above.
EDIT: All of the methods above are part of a lib that I made, they're are not made suspend because I don't want to force a particular type of programming to the user, like forcing to use Rx or Coroutines when using the lib.
The problem
Let's say I try to add a list of suggestions using the addSuggestions() method stated above, and that I also try to add a pinned suggestion using the addPin() method. The pinned text is also present in the suggestion list.
val list = getSuggestions() // Getting a list somewhere
addSuggestions(list)
addPin(list.first())
When I try to do this, sometimes the pin is added first and then it's overwritten by the suggestion present in the list, which makes me think I might've been dealing with some sort of race condition. Since the addSuggestions() method has more data to handle, and both methods will run in parallel, I believe the addPin() method is completing first.
Now, my Coroutines knowledge is pretty limited and I'd like to know if there's a way to enqueue those method calls and make sure they'll execute in the exact same order I invoked them, that must be strongly guaranteed to avoid overriding data and getting funky results later on. How can I achieve such behavior?

I'd follow the Go language slogan "Don't communicate by sharing memory; share memory by communicating", that means instead of maintaining atomic variables or jobs and trying to synchronize between them, model your operations as messages and use Coroutines actors to handle them.
sealed class Message {
data AddSuggestions(val suggestions: List<String>) : Message()
data AddPin(val pin: String) : Message()
}
And in your class
private val parentScope = CoroutineScope(Job())
private val actor = parentScope.actor<Message>(Dispatchers.IO) {
for (msg in channel) {
when (msg) {
is Message.AddSuggestions -> TODO("Map to the Suggestion and do suggestionDAO.insert(suggestions)")
is Message.AddPin -> TODO("Map to the Pin and do suggestionDAO.insert(pin)")
}
}
}
fun addSuggestions(suggestions: List<String>) {
actor.offer(Message.AddSuggestions(suggestions))
}
fun addPin(pin: String) {
actor.offer(Message.AddPin(pin))
}
By using actors you'll be able to queue messages and they will be processed in FIFO order.

By default when you call .launch{}, it launches a new coroutine without blocking the current thread and returns a reference to the coroutine as a Job. The coroutine is canceled when the resulting job is canceled.
It doesn't care or wait for other parts of your code it just runs.
But you can pass a parameter to basically tell it to run immediately or wait for other Coroutine to finish(LAZY).
For Example:
val work_1 = CoroutineScope(IO).launch( start = CoroutineStart.LAZY ){
//do dome work
}
val work_2 = CoroutineScope(IO).launch( start = CoroutineStart.LAZY ){
//do dome work
work_1.join()
}
val work_3 = CoroutineScope(IO).launch( ) {
//do dome work
work_2.join()
}
When you execute the above code first work_3 will finish and invoke work_2 when inturn invoke Work_1 and so on,
The summary of coroutine start options is:
DEFAULT -- immediately schedules coroutine for execution according to its context
LAZY -- starts coroutine lazily, only when it is needed
ATOMIC -- atomically (in a non-cancellable way) schedules coroutine for execution according to its context
UNDISPATCHED -- immediately executes coroutine until its first suspension point in the current thread.
So by default when you call .launch{} start = CoroutineStart.DEFAULT is passed because it is default parameter.

Don't launch coroutines from your database or repository. Use suspending functions and then switch dispatchers like:
suspend fun addPin(pin: String) {
...
withContext(Dispatchers.IO) {
suggestionDAO.insert(suggestion)
}
}
Then from your ViewModel (or Activity/Fragment) make the call:
fun addSuggestionsAndPinFirst(suggestions: List<Suggestion>) {
myCoroutineScope.launch {
repository.addSuggestions(suggestions)
repository.addPin(suggestions.first())
}
}
Why do you have a separate addPin() function anyways? You can just modify a suggestion and then store it:
fun pinAndStoreSuggestion(suggestion: Suggestion) {
myCoroutineScope.launch {
repository.storeSuggestion(suggestion.copy(type = SuggestionType.PINNED)
}
}
Also be careful using a Job like that. If any coroutine fails all your coroutines will be cancelled. Use a SupervisorJob instead. Read more on that here.
Disclaimer: I do not approve of the solution below. I'd rather use an old-fashioned ExecutorService and submit() my Runnable's
So if you really want to synchronize your coroutines in a way that the first function called is also the first one to write to your database. (I'm not sure it is guaranteed since your DAO functions are also suspending and Room uses it's own threads too). Try something like the following unit test:
class TestCoroutineSynchronization {
private val jobId = AtomicInteger(0)
private val jobToRun = AtomicInteger(0)
private val jobMap = mutableMapOf<Int, () -> Unit>()
#Test
fun testCoroutines() = runBlocking {
first()
second()
delay(2000) // delay so our coroutines finish
}
private fun first() {
val jobId = jobId.getAndIncrement()
CoroutineScope(SupervisorJob() + Dispatchers.Default).launch {
delay(1000) // intentionally delay your first coroutine
withContext(Dispatchers.IO) {
submitAndTryRunNextJob(jobId) { println(1) }
}
}
}
private fun second() {
val jobId = jobId.getAndIncrement()
CoroutineScope(SupervisorJob()).launch(Dispatchers.IO) {
submitAndTryRunNextJob(jobId) { println(2) }
}
}
private fun submitAndTryRunNextJob(jobId: Int, action: () -> Unit) {
synchronized(jobMap) {
jobMap[jobId] = action
tryRunNextJob()
}
}
private fun tryRunNextJob() {
var action = jobMap.remove(jobToRun.get())
while (action != null) {
action()
action = jobMap.remove(jobToRun.incrementAndGet())
}
}
}
So what I do on each call is increment a value (jobId) that is later used to prioritize what action to run first. Since you are using suspending function you probably need to add that modifier to the action submitted too (e.g. suspend () -> Unit).

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.