Develop Reference

How to use collectAsState() when getting data from Firestore?

A have a screen where I display 10 users. Each user is represented by a document in Firestore. On user click, I need to get its details. This is what I have tried:
fun getUserDetails(uid: String) {
LaunchedEffect(uid) {
viewModel.getUser(uid)
}
when(val userResult = viewModel.userResult) {
is Result.Loading -> CircularProgressIndicator()
is Result.Success -> Log.d("TAG", "You requested ${userResult.data.name}")
is Result.Failure -> Log.d("TAG", userResult.e.message)
}
}
Inside the ViewModel class, I have this code:
var userResult by mutableStateOf<Result<User>>(Result.Loading)
private set
fun getUser(uid: String) = viewModelScope.launch {
repo.getUser(uid).collect { result ->
userResult = result
}
}
As you see, I use Result.Loading as a default value, because the document is heavy, and it takes time to download it. So I decided to display a progress bar. Inside the repo class I do:
override fun getUser(uid: String) = flow {
try {
emit(Result.Loading)
val user = usersRef.document(uid).get().await().toObject(User::class.java)
emit(Result.Success(user))
} catch (e: Exception) {
emit(Result.Failure(e))
}
}
I have two questions, if I may.
Is there something wrong with this code? As it works fine when I compile.
I saw some questions here, that recommend using collectAsState() or .collectAsStateWithLifecycle(). I tried changing userResult.collectAsState() but I cannot find that function. Is there any benefit in using collectAsState() or .collectAsStateWithLifecycle() than in my actual code? I'm really confused.

If you wish to follow Uncle Bob's clean architecture you can split your architecture into Data, Domain and Presentation layers.
For android image below shows how that onion shape can be simplified to
You emit your result from Repository and handle states or change data, if you Domain Driven Model, you store DTOs for data from REST api, if you have db you keep database classes instead of passing classes annotated with REST api annotation or db annotation to UI you pass a UI.
In repository you can pass data as
override fun getUser(uid: String) = flow {
val user usersRef.document(uid).get().await().toObject(User::class.java)
emit(user)
}
In UseCase you check if this returns error, or your User and then convert this to a Result or a class that returns error or success here. You can also change User data do Address for instance if your business logic requires you to return an address.
If you apply business logic inside UseCase you can unit test what you should return if you retrieve data successfully or in case error or any data manipulation happens without error without using anything related to Android. You can just take this java/kotlin class and unit test anywhere not only in Android studio.
In ViewModel after getting a Flow< Result<User>> you can pass this to Composable UI.
Since Compose requires a State to trigger recomposition you can convert your Flow with collectAsState to State and trigger recomposition with required data.
CollectAsState is nothing other than Composable function produceState
#Composable
fun <T : R, R> Flow<T>.collectAsState(
initial: R,
context: CoroutineContext = EmptyCoroutineContext
): State<R> = produceState(initial, this, context) {
if (context == EmptyCoroutineContext) {
collect { value = it }
} else withContext(context) {
collect { value = it }
}
}
And produceState
#Composable
fun <T> produceState(
initialValue: T,
key1: Any?,
key2: Any?,
#BuilderInference producer: suspend ProduceStateScope<T>.() -> Unit
): State<T> {
val result = remember { mutableStateOf(initialValue) }
LaunchedEffect(key1, key2) {
ProduceStateScopeImpl(result, coroutineContext).producer()
}
return result
}

As per discussion in comments, you can try this approach:
// Repository
suspend fun getUser(uid: String): Result<User> {
return try {
val user = usersRef.document(uid).get().await().toObject(User::class.java)
Result.Success(user)
} catch (e: Exception) {
Result.Failure(e)
}
}
// ViewModel
var userResult by mutableStateOf<Result<User>?>(null)
private set
fun getUser(uid: String) {
viewModelScope.launch {
userResult = Result.Loading // set initial Loading state
userResult = repository.getUser(uid) // update the state again on receiving the response
}
}

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

How to wait for multiple jobs in Android ViewModel?

Given the following components
data class Account(val name: String)
data class GetAccountRequest(val name: String)
#Dao
interface AccountDao {
#Query("SELECT * FROM accounts ORDER BY name ASC")
fun all(): LiveData<List<Account>>
}
interface AccountOperations {
#GET("/foo/account")
suspend fun getAccount(#Body request: GetAccountRequest): Account
}
class AccountRepository(private val dao: AccountDao, private val api: AccountOperations) {
val accounts: LiveData<List<Account>> = dao.all()
suspend fun refresh(name: String) {
val account = api.getAccount(GetAccountRequest(name))
dao.insert(account)
}
}
I am working on an Android application that is using these components (powered by Room for the database and Retrofit for API access).
In my ViewModel I maintain a RecyclerView that lists all accounts. I enable users to refresh that list manually. The respective (part of the) ViewModel looks like this:
fun refresh() {
viewModelScope.launch {
repository.accounts.value?.forEach {
launch { repository.refresh(it.name) }
}
}
Timber.i("Done refreshing!")
}
I do want the refresh to update all accounts in parallel, this is why I am using launch. I have also decided to do this in the ViewModel, rather than in the repository, since that would have required to launch a new coroutine in the repository. Which per this post is discouraged since repositories don't have a natural lifecycle.
The above function, refresh, is invoked from the UI and shows a refresh-indicator while the RecyclerView is updated. So I want to stop this indicator once all accounts have been updated.
My code as shown above doesn't do this, since it will launch all the updates and then print the log statement before all updates have been finished. As a result the refresh-indicator disappears although there are still updates.
So my question (finally) is: how can I refactor the code so that it runs all updates in parallel, but makes sure refresh doesn't return before all of them have finished?
EDIT #1
Going back to what I want to achieve: showing the refresh-indicator while the view is updating, I came up with the following (changed the refresh function in the ViewModel):
fun refresh() {
viewModelScope.launch {
try {
coroutineScope {
_refreshing.value = true
repository.accounts.value?.map { account ->
async {
repository.refresh(account.name)
}
}
}
} catch (cause: CancellationException) {
throw cause
} catch (cause: Exception) {
Timber.e(cause)
} finally {
_refreshing.value = false
}
}
}
The ViewModel exposes a LiveData for when it is refreshing and the fragment can observe it to show or hide the spinner. This seems to do the trick. However, it still doesn't feel right and I appreciate any improved solutions.

In order to await for all of your parallel refresh() operations, simply use awaitAll():
coroutineScope.launch {
_refreshing.value = true
repository.accounts.value?.map { account ->
async {
repository.refresh(account.name)
}
}.awaitAll()
_refreshing.value = false
}
Furthermore, It's not advised to wrap coroutines with try/catch.
You can read more on this here.

Flakiness in tests on Android using LiveData, RxJava/RxKotlin and Spek

Setup:
In our project (at work - I cannot post real code), we have implemented clean MVVM. Views communicate with ViewModels via LiveData. ViewModel hosts two kinds of use cases: 'action use cases' to do something, and 'state updater use cases'. Backward communication is asynchronous (in terms of action reaction). It's not like an API call where you get the result from the call. It's BLE, so after writing the characteristic there will be a notification characteristic we listen to. So we use a lot of Rx to update the state. It's in Kotlin.
ViewModel:
#PerFragment
class SomeViewModel #Inject constructor(private val someActionUseCase: SomeActionUseCase,
someUpdateStateUseCase: SomeUpdateStateUseCase) : ViewModel() {
private val someState = MutableLiveData<SomeState>()
private val stateSubscription: Disposable
// region Lifecycle
init {
stateSubscription = someUpdateStateUseCase.state()
.subscribeIoObserveMain() // extension function
.subscribe { newState ->
someState.value = newState
})
}
override fun onCleared() {
stateSubscription.dispose()
super.onCleared()
}
// endregion
// region Public Functions
fun someState() = someState
fun someAction(someValue: Boolean) {
val someNewValue = if (someValue) "This" else "That"
someActionUseCase.someAction(someNewValue)
}
// endregion
}
Update state use case:
#Singleton
class UpdateSomeStateUseCase #Inject constructor(
private var state: SomeState = initialState) {
private val statePublisher: PublishProcessor<SomeState> =
PublishProcessor.create()
fun update(state: SomeState) {
this.state = state
statePublisher.onNext(state)
}
fun state(): Observable<SomeState> = statePublisher.toObservable()
.startWith(state)
}
We are using Spek for unit tests.
#RunWith(JUnitPlatform::class)
class SomeViewModelTest : SubjectSpek<SomeViewModel>({
setRxSchedulersTrampolineOnMain()
var mockSomeActionUseCase = mock<SomeActionUseCase>()
var mockSomeUpdateStateUseCase = mock<SomeUpdateStateUseCase>()
var liveState = MutableLiveData<SomeState>()
val initialState = SomeState(initialValue)
val newState = SomeState(newValue)
val behaviorSubject = BehaviorSubject.createDefault(initialState)
subject {
mockSomeActionUseCase = mock()
mockSomeUpdateStateUseCase = mock()
whenever(mockSomeUpdateStateUseCase.state()).thenReturn(behaviorSubject)
SomeViewModel(mockSomeActionUseCase, mockSomeUpdateStateUseCase).apply {
liveState = state() as MutableLiveData<SomeState>
}
}
beforeGroup { setTestRxAndLiveData() }
afterGroup { resetTestRxAndLiveData() }
context("some screen") {
given("the action to open the screen") {
on("screen opened") {
subject
behaviorSubject.startWith(initialState)
it("displays the initial state") {
assertEquals(liveState.value, initialState)
}
}
}
given("some setup") {
on("some action") {
it("does something") {
subject.doSomething(someValue)
verify(mockSomeUpdateStateUseCase).someAction(someOtherValue)
}
}
on("action updating the state") {
it("displays new state") {
behaviorSubject.onNext(newState)
assertEquals(liveState.value, newState)
}
}
}
}
}
At first we were using an Observable instead of the BehaviorSubject:
var observable = Observable.just(initialState)
...
whenever(mockSomeUpdateStateUseCase.state()).thenReturn(observable)
...
observable = Observable.just(newState)
assertEquals(liveState.value, newState)
instead of the:
val behaviorSubject = BehaviorSubject.createDefault(initialState)
...
whenever(mockSomeUpdateStateUseCase.state()).thenReturn(behaviorSubject)
...
behaviorSubject.onNext(newState)
assertEquals(liveState.value, newState)
but the unit test were being flaky. Mostly they would pass (always when ran in isolation), but sometime they would fail when running the whole suit. Thinking it is to do with asynchronous nature of the Rx we moved to BehaviourSubject to be able to control when the onNext() happens. Test are now passing when we run them from AndroidStudio on the local machine, but they are still flaky on the build machine. Restarting the build often makes them pass.
The tests which fail are always the ones where we assert the value of LiveData. So the suspects are LiveData, Rx, Spek or their combination.
Question: Did anyone have similar experiences writing unit tests with LiveData, using Spek or maybe Rx, and did you find ways to write them which solve these flakiness issues?
....................
Helper and extension functions used:
fun instantTaskExecutorRuleStart() =
ArchTaskExecutor.getInstance().setDelegate(object : TaskExecutor() {
override fun executeOnDiskIO(runnable: Runnable) {
runnable.run()
}
override fun isMainThread(): Boolean {
return true
}
override fun postToMainThread(runnable: Runnable) {
runnable.run()
}
})
fun instantTaskExecutorRuleFinish() = ArchTaskExecutor.getInstance().setDelegate(null)
fun setRxSchedulersTrampolineOnMain() = RxAndroidPlugins.setInitMainThreadSchedulerHandler { Schedulers.trampoline() }
fun setTestRxAndLiveData() {
setRxSchedulersTrampolineOnMain()
instantTaskExecutorRuleStart()
}
fun resetTestRxAndLiveData() {
RxAndroidPlugins.reset()
instantTaskExecutorRuleFinish()
}
fun <T> Observable<T>.subscribeIoObserveMain(): Observable<T> =
subscribeOnIoThread().observeOnMainThread()
fun <T> Observable<T>.subscribeOnIoThread(): Observable<T> = subscribeOn(Schedulers.io())
fun <T> Observable<T>.observeOnMainThread(): Observable<T> =
observeOn(AndroidSchedulers.mainThread())

I didn't used Speck for unit-testing. I've used java unit-test platform and it works perfect with Rx & LiveData, but you have to keep in mind one thing. Rx & LiveData are async and you can't do something like someObserver.subscribe{}, someObserver.doSmth{}, assert{} this will work sometimes but it's not the correct way to do it.
For Rx there's TestObservers for observing Rx events. Something like:
#Test
public void testMethod() {
TestObserver<SomeObject> observer = new TestObserver()
someClass.doSomethingThatReturnsObserver().subscribe(observer)
observer.assertError(...)
// or
observer.awaitTerminalEvent(1, TimeUnit.SECONDS)
observer.assertValue(somethingReturnedForOnNext)
}
For LiveData also, you'll have to use CountDownLatch to wait for LiveData execution. Something like this:
#Test
public void someLiveDataTest() {
CountDownLatch latch = new CountDownLatch(1); // if you want to check one time exec
somethingTahtReturnsLiveData.observeForever(params -> {
/// you can take the params value here
latch.countDown();
}
//trigger live data here
....
latch.await(1, TimeUnit.SECONDS)
assert(...)
}
Using this approach your test should run ok in any order on any machine. Also the wait time for latch & terminal event should be as low as possible, the tests should run fast.
Note1: The code is in JAVA but you can change it easily in kotlin.
Note2: Singleton are the biggest enemy of unit-testing ;). (With static methods by their side).

The issue is not with LiveData; it is the more common problem - singletons. Here the Update...StateUseCases had to be singletons; otherwise if observers got a different instance they would have a different PublishProcessor and would not get what was published.
There is a test for each Update...StateUseCases and there is a test for each ViewModel into which Update...StateUseCases is injected (well indirectly via the ...StateObserver).
The state exists within the Update...StateUseCases, and since it is a singleton, it gets changed in both tests and they use the same instance becoming dependent on each other.
Firstly try to avoid using singletons if possible.
If not, reset the state after each test group.

Kotlin Coroutine to escape callback hell

I'm trying to use Kotlin's coroutines to avoid callback hell, but it doesnt look like I can in this specific situation, I would like some thougths about it.
I have this SyncService class which calls series of different methods to send data to the server like the following:
SyncService calls Sync Student, which calls Student Repository, which calls DataSource that makes a server request sending the data through Apollo's Graphql Client.
The same pattern follows in each of my features:
SyncService -> Sync Feature -> Feature Repository -> DataSource
So every one of the method that I call has this signature:
fun save(onSuccess: ()-> Unit, onError:()->Unit) {
//To Stuff here
}
The problem is:
When I sync and successfully save the Student on server, I need to sync his enrollment, and if I successfully save the enrollment, I need to sync another object and so on.
It all depends on each other and I need to do it sequentially, that's why I was using callbacks.
But as you can imagine, the code result is not very friendly, and me and my team starting searching for alternatives to keep it better. And we ended up with this extension function:
suspend fun <T> ApolloCall<T>.execute() = suspendCoroutine<Response<T>> { cont ->
enqueue(object: ApolloCall.Callback<T>() {
override fun onResponse(response: Response<T>) {
cont.resume(response)
}
override fun onFailure(e: ApolloException) {
cont.resumeWithException(e)
}
})
}
But the function in DataSource still has a onSuccess() and onError() as callbacks that needs to be passed to whoever call it.
fun saveStudents(
students: List<StudentInput>,
onSuccess: () -> Unit,
onError: (errorMessage: String) -> Unit) {
runBlocking {
try {
val response = GraphQLClient.apolloInstance
.mutate(CreateStudentsMutation
.builder()
.students(students)
.build())
.execute()
if (!response.hasErrors())
onSuccess()
else
onError("Response has errors!")
} catch (e: ApolloException) {
e.printStackTrace()
onError("Server error occurred!")
}
}
}
The SyncService class code changed to be like:
private fun runSync(onComplete: () -> Unit) = async(CommonPool) {
val syncStudentProcess = async(coroutineContext, start = CoroutineStart.LAZY) {
syncStudents()
}
val syncEnrollmentProcess = async(coroutineContext, start = CoroutineStart.LAZY) {
syncEnrollments()
}
syncStudentProcess.await()
syncEnrollmentProcess.await()
onComplete()
}
It does execute it sequentially, but I need a way to stop every other coroutine if any got any errors. Error that might come only from Apollo's
So I've been trying a lot to find a way to simplify this code, but didn't get any good result. I don't even know if this chaining of callbacks can be simplify at all. That's why I came here to see some thoughts on it.
TLDR: I want a way to execute all of my functions sequentially, and still be able to stop all coroutines if any got an exception without a lot o chaining callbacks.