I would like to convert my rxJava Code to Kotlin CoRoutine.
Below is the code makes both the api and db call and returns the data to UI whatever comes first. Let us say if DB response happens to be quicker than the api. In that case still, the api response would continue until it receives the data to sync with db though it could have done the UI update earlier.
How Would I do it?
class MoviesRepository #Inject constructor(val apiInterface: ApiInterface,
val MoviesDao: MoviesDao) {
fun getMovies(): Observable<List<Movie>> {
val observableFromApi = getMoviesFromApi()
val observableFromDb = getMoviesFromDb()
return Observable.concatArrayEager(observableFromApi, observableFromDb)
}
fun getMoviesFromApi(): Observable<List<Movie>> {
return apiInterface.getMovies()
.doOnNext { it ->
it.data?.let { it1 -> MoviesDao.insertAllMovies(it1) }
println("Size of Movies from API %d", it.data?.size)
}
.map({ r -> r.data })
}
fun getMoviesFromDb(): Observable<List<Movie>> {
return MoviesDao.queryMovies()
.toObservable()
.doOnNext {
//Print log it.size :)
}
}
}
As the first step you should create suspend funs for your ApiInterface and MovieDao calls. If they have some callback-based API, you can follow these official instructions.
You should now have
suspend fun ApiInterface.suspendGetMovies(): List<Movie>
and
suspend fun MoviesDao.suspendQueryMovies(): List<Movie>
Now you can write this code:
launch(UI) {
val fromNetwork = async(UI) { apiInterface.suspendGetMovies() }
val fromDb = async(UI) { MoviesDao.suspendQueryMovies() }
select<List<Movie>> {
fromNetwork.onAwait { it }
fromDb.onAwait { it }
}.also { movies ->
// act on the movies
}
}
The highlight is the select call which will simultaneously await on both Deferreds and act upon the one that gets completed first.
If you want to ensure you act upon the result from the network, you'll need some more code, for example:
val action = { movies: List<Movie> ->
// act on the returned movie list
}
var gotNetworkResult = false
select<List<Movie>> {
fromNetwork.onAwait { gotNetworkResult = true; it }
fromDb.onAwait { it }
}.also(action)
if (!gotNetworkResult) {
action(fromNetwork.await())
}
This code will act upon the DB results only if they come in before the network results, which it will process in all cases.
Something along those lines should work:
data class Result(val fromApi: ???, val fromDB: ???)
fun getMovies(): Result {
val apiRes = getMoviesFromApiAsync()
val dbRes = getMoviesFromDbAsync()
return Result(apiRes.await(), dbRes.await())
}
fun getMoviesFromApiAsync() = async {
return apiInterface.getMovies()
.doOnNext { it ->
it.data?.let { it1 -> MoviesDao.insertAllMovies(it1) }
println("Size of Movies from API %d", it.data?.size)
}
.map({ r -> r.data })
}
fun getMoviesFromDbAsync() = async {
return MoviesDao.queryMovies()
}
I don't know what you're returning, so I just put ??? instead.
Related
Let me use a simple image to illustrate what I want to get:
I don't want to use SharedFlow's replayCache to achieve this because if a new observer observes that SharedFlow, it will get 2 emissions instead of one latest emission.
Or if I write it in code:
val sharedFlow = MutableSharedFlow(replay = 1)
val theFlowThatIWant = sharedFlow.unknownOperator { … }
sharedFlow.emit(1)
sharedFlow.emit(2)
sharedFlow.collect {
println(it)
}
Expected output:
2
theFlowThatIWant.collect {
println(it)
}
Expected output:
1
We can create such operator by ourselves. We can generalize it to more items than only the last one and use circular buffer to keep postponed items:
suspend fun main() {
val f = flow {
repeat(5) {
println("Emitting $it")
emit(it)
delay(1000)
}
}
f.postponeLast()
.collect { println("Collecting $it") }
}
fun <T> Flow<T>.postponeLast(count: Int = 1): Flow<T> = flow {
val buffer = ArrayDeque<T>(count)
collect {
if (buffer.size == count) {
emit(buffer.removeFirst())
}
buffer.addLast(it)
}
}
Note that this solution never emits postponed items. If you like to emit them at the end, just add this after collect { }:
while (buffer.isNotEmpty()) {
emit(buffer.removeFirst())
}
var responseMap = mutableMapOf<VendorType, ChargeResponse>()
requests.forEach {
val response = when (it.vendorType) {
VendorType.Type1 -> service.chargeForType1()
VendorType.Type2 -> service.chargeForType2()
else -> {
throw NotImplementedError("${it.vendorType} does not support yet")
}
}
responseMap[it.vendorType] = response
}
responseMap
So I want all the service.charge function run in separate thread. Return the map when all is done
Hope to solve your problem:
Assume your service and request like this:
interface Service {
suspend fun chargeForType1(): ChargeResponse
suspend fun chargeForType2(): ChargeResponse
}
data class Request(val vendorType: VendorType)
suspend fun requestAll(requests: List<Request>): Map<VendorType, ChargeResponse> {
return coroutineScope {
requests
.map { request ->
async {
request.vendorType to when (request.vendorType) {
VendorType.Type1 -> service.chargeForType1()
VendorType.Type2 -> service.chargeForType2()
else -> throw NotImplementedError("${request.vendorType} does not support yet")
}
}
}
.awaitAll()
.toMap()
}
}
I have a function that conditionally fetches some data and runs some tasks concurrently on that data. Each task depends on different sets of data and I would like to avoid fetching the data that's not needed. Moreover, some of the data can have already been prefetched and given to the function. See the code I've come up with below.
suspend fun process(input: SomeInput, prefetchedDataX: DataX?, prefetchedDataY: DataY?) = coroutineScope {
val dataXAsync = lazy {
if (prefetchedDataX == null) {
async { fetchDataX(input) }
} else CompletableDeferred(prefetchedDataX)
}
val dataYAsync = lazy {
if (prefetchedDataY == null) {
async { fetchDataY(input) }
} else CompletableDeferred(prefetchedDataY)
}
if (shouldDoOne(input)) launch {
val (dataX, dataY) = awaitAll(dataXAsync.value, dataYAsync.value)
val modifiedDataX = modifyX(dataX)
val modifiedDataY = modifyY(dataY)
doOne(modifiedDataX, modifiedDataY)
}
if (shouldDoTwo(input)) launch {
val modifiedDataX = modifyX(dataXAsync.value.await())
doTwo(modifiedDataX)
}
if (shouldDoThree(input)) launch {
val modifiedDataY = modifyY(dataYAsync.value.await())
doThree(modifiedDataY)
}
}
Any improvements that could be made to this code? One, I don't like having to fakely wrap the prefetched data into a CompletableDeferred. Two, I don't like having to call modifyX, modifyY inside each task, I wish I could apply it at the fetching stage, but I haven't come up with a nice way to do that. Alternatively I could do
val modifiedDataXAsync = lazy {
async { modifyX(prefetchedDataX ?: fetchDataX(input)) }
}
but it feels wasteful to be spawning a new coroutine when the data is already prefetched. Am I over-optimizing?
How about this? This code is pretty similar to yours, I just simplified it a bit.
suspend fun process(input: SomeInput, prefetchedDataX: DataX?, prefetchedDataY: DataY?) = coroutineScope {
val modifiedDataX by lazy {
async { modifyX(prefetchedDataX ?: fetchDataX(input)) }
}
val modifiedDataY by lazy {
async { modifyY(prefetchedDataY ?: fetchDataY(input)) }
}
if (shouldDoOne(input)) launch {
val (dataX, dataY) = awaitAll(modifiedDataX, modifiedDataY)
doOne(dataX, dataY)
}
if (shouldDoTwo(input)) launch {
doTwo(modifiedDataX.await())
}
if (shouldDoThree(input)) launch {
doThree(modifiedDataY.await())
}
}
I have such code and i want to collect results of api call inside coroutine and then join this job and return it from function
private suspend fun loadRangeInternal(offset: Int, limit: Int): List<Activity> {
// load data from Room database
// calling Retrofit request
// and caching them if there is no data available
var activities: List<Activity> = listOf()
val job = GlobalScope.launch {
repo.loadActivitiesOf(settings.companyId, offset, limit)
.collect {
networkError.send(it.error)
when (it.status) {
Resource.Status.SUCCESS -> {
activities = it.data ?: listOf()
isLoading.send(false)
}
Resource.Status.LOADING -> {
isLoading.send(true)
}
Resource.Status.ERROR -> {
isLoading.send(false)
}
}
}
}
job.join()
Timber.d("Activities loaded: $activities")
return activities
}
I've also tried async instead of launch, and await instead of join
Calculation execution time by using measureTimeMillis{} and delay your function at that time.
private suspend fun loadRangeInternal(offset: Int, limit: Int): List<Activity> {
// load data from Room database
// calling Retrofit request
// and caching them if there is no data available
var activities: List<Activity> = listOf()
val executionTime = measureTimeMillis {
async {
repo.loadActivitiesOf(settings.companyId, offset, limit)
.collect {
networkError.send(it.error)
when (it.status) {
Resource.Status.SUCCESS -> {
activities = it.data ?: listOf()
isLoading.send(false)
}
Resource.Status.LOADING -> {
isLoading.send(true)
}
Resource.Status.ERROR -> {
isLoading.send(false)
}
}
}
}.await()
}
delay(executionTime)
Timber.d("Activities loaded: $activities")
return activities
}
Try in rxJava2 Kotlin combine Single with Flowable but nothing not happening:
Does not undrstand what wrong
Flowable.create<Int>({ emmit ->
loadNewListener = object :Listener {
override fun onEmit(id: Int) {
emmit.onNext(id)
}
}
}, BackpressureStrategy.LATEST)
.debounce(500, TimeUnit.MILLISECONDS)
.flatMapSingle {
loadNew(id = it.id)
}
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe({ (data:Data) ->
}, {
Timber.e("Failed load data ${it.message}")
})
my method is returning Single:
private fun loadNew(id: Int): Single<Data> {
return when (pdfType) {
CASE_0 -> {
Single.create<Data> { emmit ->
service.get("data")
.enqueue(
object : Callback<Void> {
override fun onFailure(call: Call<Void>?, t: Throwable?) {
// failure
}
override fun onResponse(call: Call<Void>?, response: Response<Void>?) {
emmit.onSuccess(it.data)
}
}
}//single
}//case_0
CASE_1 -> 1Repository.loadsome1Rx(id = id).map { it.getData() }
CASE_2 -> 2Repository.loadsom2LocalRx(id = id).map { it.getData() }
else -> {
throw java.lang.RuntimeException("$this is not available type!")
}
}
What is wrong im my code?
Need Maby call Single in Flowable subscribe() seppurate
like this?
Flowable.create<Int>({ emmit ->
loadNewListener = object :Listener {
override fun onEmit(id: Int) {
emmit.onNext(id)
}
}
}, BackpressureStrategy.LATEST)
.debounce(500, TimeUnit.MILLISECONDS)
.subscribe({
loadNew(id = it.id)
}, {
Timber.e("")
})
This code is workin but looks not simple as via combine try.
This simple example based on your code is working
var i = 0
fun foo() {
Flowable.create<Int>({ emmit ->
emmit.onNext(i)
i++
}, BackpressureStrategy.LATEST)
.debounce(500, TimeUnit.MILLISECONDS)
.flatMapSingle {
Single.create<String> { emmit ->
emmit.onSuccess("onSuccess: $it")
}
}
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe({
Log.i("RX", "Subscribe: $it")
}, {
it.printStackTrace()
})
}
Check SingleEmitter.onSuccess() and SingleEmitter.onError() is called in all cases in when (pdfType)...
As #Stas Bondar said in answer below This simple example based on your code is working!!
Problem was in loadNewListener .
It does not init in time and has null value when need. Call create Flowable on init ViewModel but loadNewListener did not have time to create when i call him from fragment.
loadNewListener = object :Listener{...}
Becuse need some time mutch for init rxJava expression!
And combine flowable with single via flatMapSingle spent more time than just call single on flowable dubscrinbe!
So use temp field:
private var temp: Temp? = null
fun load(id: Int) {
loadNewListener.apply {
when {
this != null -> load(id = id)
else -> userEmitPdfTemp = Temp(id = id)
}
}
}
Flowable.create<Data>({ emmit ->
userEmitPdfTemp?.let {id->
emmit.onNext(Data(id))
userEmitPdfTemp =null
}
loadNewListener = object :Listener {
override fun load(id: Int) {
emmit.onNext(Data(id))
}
}
}