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

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
}
}

Related

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 can I get data and initialize a field in viewmodel using kotlin coroutines and without a latenite of null field

I have a common situation of getting data. I use the Kotlin Coroutines.
1 variant:
class SomeViewModel(
private val gettingData: GetDataUseCase
) : ViewModel() {
lateinit var data: List<String>
init {
viewModelScope.launch {
data = gettingData.get()
}
}
}
2 variant:
class SomeViewModel(
private val gettingData: GetDataUseCase
) : ViewModel() {
val data = MutableStateFlow<List<String>?>(null)
init {
viewModelScope.launch {
data.emit(gettingData.get())
}
}
}
How can I initialize a data field not delayed, but immediately, with the viewModelScope but without a lateinit or nullble field? And without LiveData, my progect uses Coroutine Flow
I can't return a result of viewModelScope job in .run{} or by lazy {}.
I cant return a result drom fun:
val data: List<String> = getData()
fun getData(): List<String> {
viewModelScope.launch {
data = gettingData.get()
}
return ???
}
Also I can't make suspend fun getData() because I can't create coroutineScope in initialisation'
You're describing an impossibility. Presumably, gettingData.get() is defined as a suspend function, meaning the result literally cannot be retrieved immediately. Since it takes a while to retrieve, you cannot have an immediate value.
This is why apps and websites have loading indicators in their UI.
If you're using Flows, you can use a Flow with a nullable type (like in your option 2 above), and in your Activity/Fragment, in the collector, you show either a loading indicator or your data depending on whether it is null.
Your code 2 can be simplified using the flow builder and stateIn with a null default value:
class SomeViewModel(
private val gettingData: GetDataUseCase
) : ViewModel() {
val data = flow<List<String>?> { emit(gettingData.get()) }
.stateIn(viewModelScope, SharingStarted.Eagerly, null)
}
In your Activity or Fragment:
viewLifecycleOwner.lifecycleScope.launch {
viewModel.data
.flowWithLifecycle(viewLifecycleOwner.lifecycle, Lifecycle.State.STARTED)
.collect { list ->
if(list == null) {
// Show loading indicator in UI
} else {
// Show the data
}
}
}
If your data loads pretty quickly, instead of making the type nullable, you can just make the default value emptyList(). Then your collector can just not do anything when the list is empty. This works if the data loads quickly enough that the user isn't going to wonder if something is wrong because the screen is blank for so long.
You have to use SharedFlow with replay 1 (to store last value and replay it for a new subscriber) to implement it.
My sample:
interface DataSource {
suspend fun getData(): Int
}
class DataViewModel(dataSource: DataSource): ViewModel() {
val dataField =
flow<Int> {
emit(dataSource.getData())
}.shareIn(viewModelScope, SharingStarted.WhileSubscribed(1000), 1)
}

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 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

Communication between view and ViewModel in MVVM with LiveData

What is a proper way to communicate between the ViewModel and the View, Google architecture components give use LiveData in which the view subscribes to the changes and update itself accordingly, but this communication not suitable for single events, for example show message, show progress, hide progress etc.
There are some hacks like SingleLiveEvent in Googles example but it work only for 1 observer.
Some developers using EventBus but i think it can quickly get out of control when the project grows.
Is there a convenience and correct way to implement it, how do you implement it?
(Java examples welcome too)
Yeah I agree, SingleLiveEvent is a hacky solution and EventBus (in my experience) always lead to trouble.
I found a class called ConsumableValue a while back when reading the Google CodeLabs for Kotlin Coroutines, and I found it to be a good, clean solution that has served me well (ConsumableValue.kt):
class ConsumableValue<T>(private val data: T) {
private var consumed = false
/**
* Process this event, will only be called once
*/
#UiThread
fun handle(block: ConsumableValue<T>.(T) -> Unit) {
val wasConsumed = consumed
consumed = true
if (!wasConsumed) {
this.block(data)
}
}
/**
* Inside a handle lambda, you may call this if you discover that you cannot handle
* the event right now. It will mark the event as available to be handled by another handler.
*/
#UiThread
fun ConsumableValue<T>.markUnhandled() {
consumed = false
}
}
class MyViewModel : ViewModel {
private val _oneShotEvent = MutableLiveData<ConsumableValue<String>>()
val oneShotEvent: LiveData<ConsumableValue<String>>() = _oneShotData
fun fireEvent(msg: String) {
_oneShotEvent.value = ConsumableValue(msg)
}
}
// In Fragment or Activity
viewModel.oneShotEvent.observe(this, Observer { value ->
value?.handle { Log("TAG", "Message:$it")}
})
In short, the handle {...} block will only be called once, so there's no need for clearing the value if you return to a screen.
What about using Kotlin Flow?
I do not believe they have the same behavior that LiveData has where it would alway give you the latest value. Its just a subscription similar to the workaround SingleLiveEvent for LiveData.
Here is a video explaining the difference that I think you will find interesting and answer your questions
https://youtu.be/B8ppnjGPAGE?t=535
try this:
/**
* Used as a wrapper for data that is exposed via a LiveData that represents an event.
*/
open class Event<out T>(private val content: T) {
var hasBeenHandled = false
private set // Allow external read but not write
/**
* Returns the content and prevents its use again.
*/
fun getContentIfNotHandled(): T? {
return if (hasBeenHandled) {
null
} else {
hasBeenHandled = true
content
}
}
/**
* Returns the content, even if it's already been handled.
*/
fun peekContent(): T = content
}
And wrapper it into LiveData
class ListViewModel : ViewModel {
private val _navigateToDetails = MutableLiveData<Event<String>>()
val navigateToDetails : LiveData<Event<String>>
get() = _navigateToDetails
fun userClicksOnButton(itemId: String) {
_navigateToDetails.value = Event(itemId) // Trigger the event by setting a new Event as a new value
}
}
And observe
myViewModel.navigateToDetails.observe(this, Observer {
it.getContentIfNotHandled()?.let { // Only proceed if the event has never been handled
startActivity(DetailsActivity...)
}
})
link reference: Use an Event wrapper
For showing/hiding progress dialogs and showing error messages from a failed network call on loading of the screen, you can use a wrapper that encapsulates the LiveData that the View is observing.
Details about this method are in the addendum to app architecture:
https://developer.android.com/jetpack/docs/guide#addendum
Define a Resource:
data class Resource<out T> constructor(
val state: ResourceState,
val data: T? = null,
val message: String? = null
)
And a ResourceState:
sealed class ResourceState {
object LOADING : ResourceState()
object SUCCESS : ResourceState()
object ERROR : ResourceState()
}
In the ViewModel, define your LiveData with the model wrapped in a Resource:
val exampleLiveData = MutableLiveData<Resource<ExampleModel>>()
Also in the ViewModel, define the method that makes the API call to load the data for the current screen:
fun loadDataForView() = compositeDisposable.add(
exampleUseCase.exampleApiCall()
.doOnSubscribe {
exampleLiveData.setLoading()
}
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe(
{
exampleLiveData.setSuccess(it)
},
{
exampleLiveData.setError(it.message)
}
)
)
In the View, set up the Observer on creation:
viewModel.exampleLiveData.observe(this, Observer {
updateResponse(it)
})
Here is the example updateResponse() method, showing/hiding progress, and showing an error if appropriate:
private fun updateResponse(resource: Resource<ExampleModel>?) {
resource?.let {
when (it.state) {
ResourceState.LOADING -> {
showProgress()
}
ResourceState.SUCCESS -> {
hideProgress()
// Use data to populate data on screen
// it.data will have the data of type ExampleModel
}
ResourceState.ERROR -> {
hideProgress()
// Show error message
// it.message will have the error message
}
}
}
}
You can easily achieve this by not using LiveData, and instead using Event-Emitter library that I wrote specifically to solve this problem without relying on LiveData (which is an anti-pattern outlined by Google, and I am not aware of any other relevant alternatives).
allprojects {
repositories {
maven { url "https://jitpack.io" }
}
}
implementation 'com.github.Zhuinden:event-emitter:1.0.0'
If you also copy the LiveEvent class , then now you can do
private val emitter: EventEmitter<String> = EventEmitter()
val events: EventSource<String> get() = emitter
fun doSomething() {
emitter.emit("hello")
}
And
override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
super.onViewCreated(view, savedInstanceState)
viewModel = getViewModel<MyViewModel>()
viewModel.events.observe(viewLifecycleOwner) { event ->
// ...
}
}
// inline fun <reified T: ViewModel> Fragment.getViewModel(): T = ViewModelProviders.of(this).get(T::class.java)
For rationale, you can check out my article I wrote to explain why the alternatives aren't as valid approaches.
You can however nowadays also use a Channel(UNLIMITED) and expose it as a flow using asFlow(). That wasn't really applicable back in 2019.

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