You know that Array and List only store the same data struction.
I run the Code A and get the Result A.
It seems that the Flow can emit both Int value and String value, why?
Code A
import kotlinx.coroutines.*
import kotlinx.coroutines.flow.*
suspend fun performRequest(request: Int): Int {
delay(1000) // imitate long-running asynchronous work
return request
}
fun main() = runBlocking<Unit> {
(1..3).asFlow() // a flow of requests
.transform { request ->
emit("Making request $request")
if (request >1) {
emit(performRequest(request))
}
}
.collect { response -> println(response) }
}
Result A
Making request 1
Making request 2
2
Making request 3
3
This is not a question of Flow but Java/Kotling generics and type safety.
The type this flow returns is Comperable<*>
val flow: Flow<Comparable<*>> = (1..3).asFlow() // a flow of requests
.transform { request ->
emit("Making request $request")
if (request > 1) {
emit(performRequest(request))
}
If you explicitly specify which value you want to return Flow you can restrict the types.
About generics you can refer here or check any document about generics in java/kotlin, type safety you can refer this question
Also when you are in doubt what your specified type is use alt + enter with Android Studio to see avaialble options and select Specify type explicitly.
Disregarding the nature of this request, you can have the functionality you want by making your flow emit instances of some algebraic data type that is basically a "sum" (from the type-theoretic POV) of your constituent types:
sealed interface Record
data class IntData(val get: Int) : Record
data class Metadata(val get: String) : Record
// somewhere later (flow is of type Flow<Record>)
fun main() = runBlocking<Unit> {
(1..3).asFlow() // a flow of requests
.transform { request ->
emit(Metadata("Making request $request"))
if (request > 1) {
emit(IntData(performRequest(request)))
}
// probably want to handle the `else` case too
}
.collect { response -> println(response) }
}
This would be a good solution since it's extendable (i.e. you can add the other cases later on if you need to).
In your specific case though, since you just want to debug the flow, you might not want to actually emit the "metadata" and just go for the tests of your code directly.
Related
I am learning coroutines and need some help to understand a basic use case.
Implement a non-blocking method that:
Fetches a single item from a (reactive) DB
Determines a range (i.e. the month that the item lives in) based on that item's timestamp
Fetches all items in that month
Returns the items as Flow
Approach
Because it must return a Flow I will not use suspend (like I would when returning a single item). Returning Flow and suspend (which kind of returns a Mono) are most commonly mutually exclusive, right?
So I came up with this signature:
override fun getHistory(beforeUtcMillisExclusive: Long): Flow<Item>
Trying an implementation:
val itemInNextPeriod = itemRepository.findOneByTimestampLessThan(beforeUtcMillisExclusive)
if (itemInNextPeriod == null) {
return emptyFlow()
} else {
val range = calcRange(itemInNextPeriod.timestamp)
return itemRepository.findByTimestampGreaterThanEqualAndTimestampLessThan(range.start, range.end)
}
This gives me on the very first line:
Suspend function 'findOneByTimestampLessThan' should be called only
from a coroutine or another suspend function
I understand the problem that we are not allowed to call a suspend function here and the proposed solution by IntelliJ "adding suspend" does not make sense, when already returning a flow.
So, from this question I got the idea of using a return flow {...}:
return flow {
val itemInNextPeriod = itemRepository.findOneByTimestampLessThan(beforeUtcMillisExclusive)
if (itemInNextPeriod == null) {
return#flow
} else {
val range = calcRange(itemInNextPeriod.timestamp)
return#flow itemRepository.findByTimestampGreaterThanEqualAndTimestampLessThan(range.start,
range.end)
}
}
The second repository call findByTimestampGreaterThanEqualAndTimestampLessThan returns Flow<Item> and I do not understand why I cannot return it.
This function must return a value of type Unit
Type mismatch.
Required:
Unit
Found:
Flow
return#flow returns from the lambda, not from enclosing function.
You need to reemit items from Flow returned by findByTimestampGreaterThanEqualAndTimestampLessThan call into Flow you're building with flow function:
return flow {
val itemInNextPeriod = itemRepository.findOneByTimestampLessThan(beforeUtcMillisExclusive)
if (itemInNextPeriod != null) {
val range = calcRange(itemInNextPeriod.timestamp)
emitAll(itemRepository.findByTimestampGreaterThanEqualAndTimestampLessThan(range.start, range.end))
}
}
I have difficulties making sequential calls of RxJava Single observerable. What I mean is that I have a function that makes http request using retrofit that returns a Single.
fun loadFriends(): Single<List<Friend>> {
Log.d("msg" , "make http request")
return webService.getFriends()
}
and if I subscribe from several places at the same time:
loadFriends().subscribeOn(Schedulers.io()).subscribe()
loadFriends().subscribeOn(Schedulers.io()).subscribe()
I want that loadFriends() makes only one https request but in this case I have two http request
I know how to solve this problem in blocking way:
The solution is to make loadFriends() blocking.
private val lock = Object()
prival var inMemoryCache: List<Friends>? = null
fun loadFriends(): Single<List<Friend>> {
return Single.fromCallable {
if(inMemoryCache == null) {
synchronize(lock) {
if(inMemoryCache == null) {
inMemoryCache = webService.getFriends().blockingGet()
}
}
}
inMemoryCache
}
But I want to solve this problem in a reactive way
You can remedy this by creating one common source for all your consumers to subscribe to, and that source will have the cache() operator invoked against it. The effect of this operator is that the first subscriber's subscription will be delegated downstream (i.e. the network request will be invoked), and subsequent subscribers will see internally cached results produced as a result of that first subscription.
This might look something like this:
class Friends {
private val friendsSource by lazy { webService.getFriends().cache() }
fun someFunction() {
// 1st subscription - friends will be fetched from network
friendsSource
.subscribeOn(Schedulers.io())
.subscribe()
// 2nd subscription - friends will be fetched from internal cache
friendsSource
.subscribeOn(Schedulers.io())
.subscribe()
}
}
Note that the cache is indefinite, so if periodically refreshing the list of friends is important you'll need to come up with a way to do so.
I understand that in Kotlin there is no such thing as "Non-local variables" or "Global Variables" I am looking for a way to modify variables in another "Scope" in Kotlin by using the function below:
class Listres(){
var listsize = 0
fun gatherlistresult(){
var listallinfo = FirebaseStorage.getInstance()
.getReference()
.child("MainTimeline/")
.listAll()
listallinfo.addOnSuccessListener {
listResult -> listsize += listResult.items.size
}
}
}
the value of listsize is always 0 (logging the result from inside of the .addOnSuccessListener scope returns 8) so clearly the listsize variable isn't being modified. I have seen many different posts about this topic on other sites , but none fit my usecase.
I simply want to modify listsize inside of the .addOnSuccessListener callback
This method will always be returned 0 as the addOnSuccessListener() listener will be invoked after the method execution completed. The addOnSuccessListener() is a callback method for asynchronous operation and you will get the value if it gives success only.
You can get the value by changing the code as below:
class Demo {
fun registerListResult() {
var listallinfo = FirebaseStorage.getInstance()
.getReference()
.child("MainTimeline/")
.listAll()
listallinfo.addOnSuccessListener {
listResult -> listsize += listResult.items.size
processResult(listsize)
}
listallinfo.addOnFailureListener {
// Uh-oh, an error occurred!
}
}
fun processResult(listsize: Int) {
print(listResult+"") // you will get the 8 here as you said
}
}
What you're looking for is a way to bridge some asynchronous processing into a synchronous context. If possible it's usually better (in my opinion) to stick to one model (sync or async) throughout your code base.
That being said, sometimes these circumstances are out of our control. One approach I've used in similar situations involves introducing a BlockingQueue as a data pipe to transfer data from the async context to the sync context. In your case, that might look something like this:
class Demo {
var listSize = 0
fun registerListResult() {
val listAll = FirebaseStorage.getInstance()
.getReference()
.child("MainTimeline/")
.listAll()
val dataQueue = ArrayBlockingQueue<Int>(1)
listAll.addOnSuccessListener { dataQueue.put(it.items.size) }
listSize = dataQueue.take()
}
}
The key points are:
there is a blocking variant of the Queue interface that will be used to pipe data from the async context (listener) into the sync context (calling code)
data is put() on the queue within the OnSuccessListener
the calling code invokes the queue's take() method, which will cause that thread to block until a value is available
If that doesn't work for you, hopefully it will at least inspire some new thoughts!
I would like to use a Flow as a return type for all functions in my repository. For ex:
suspend fun create(item:T): Flow<Result<T>>
This function should call 2 data sources: remote(to save data on the server) and local(to save returned data from the server locally). The question is how I can implement this scenario:
try to save data with RemoteDataSource
if 1. fails - try it N times with M timeout
if data has finally returned from the server - same them locally with LocalDataSource
return flow with locally saved data
RemoteDataSource and LocalDataSource both have fun create with the same signature:
suspend fun create(item:T): Flow<Result<T>>
So they both return flow of data. If you have any ideas about how to implement it, I will be grateful.
------ Update #1 ------
a part of a possible solution:
suspend fun create(item:T): Flow<T> {
// save item remotely
return remoteDataSource.create(item)
// todo: call retry if fails
// save to local a merge two flows in one
.flatMapConcat { remoteData ->
localDataSource.create(remoteData)
}
.map {
// other mapping
}
}
Is it a working idea?
I think you have the right idea but you are trying to do everything at once.
What I found works best (and easily) is to have:
an exposed flow of data coming from your local datasource (easy with Room)
one or more exposed suspend functions like create or refresh that operate on the remote data source and save to the local one (if there is no error)
For ex I have a repository that fetches vehicles in my project (the isCurrent info is only local and isLeft/isRight is because I use Either but any error handling applies):
class VehicleRepositoryImpl(
private val localDataSource: LocalVehiclesDataSource,
private val remoteDataSource: RemoteVehiclesDataSource
) : VehicleRepository {
override val vehiclesFlow = localDataSource.vehicleListFlow
override val currentVehicleFlow = localDataSource.currentVehicleFLow
override suspend fun refresh() {
remoteDataSource.getVehicles()
.fold(
ifLeft = { /* handle errors, retry, ... */ },
ifRight = { reset(it) }
)
}
private suspend fun reset(vehicles: List<VehicleEntity>) {
val current = currentVehicleFlow.first()
localDataSource.reset(vehicles)
if (current != null) localDataSource.setCurrentVehicle(current)
}
override suspend fun setCurrentVehicle(vehicle: VehicleEntity) =
localDataSource.setCurrentVehicle(vehicle)
override suspend fun clear() = localDataSource.clear()
}
Hope this helps and you can adapt it to your case :)
I am trying to make a class that would take incoming user events, process them and then pass the result to whoever subscribed to it:
class EventProcessor
{
val flux: Flux<Result>
fun onUserEvent1(e : Event)
{
val result = process(e)
// Notify flux that I have a new result
}
fun onUserEvent2(e : Event)
{
val result = process(e)
// Notify flux that I have a new result
}
fun process(e : Event): Result
{
...
}
}
Then the client code can subscribe to EventProcessor::flux and get notified each time a user event has been successfully processed.
However, I do not know how to do this. I tried to construct the flux with the Flux::generate function like this:
class EventProcessor
{
private var sink: SynchronousSink<Result>? = null
val flux: Flux<Result> = Flux.generate{ sink = it }
fun onUserEvent1(e : Event)
{
val result = process(e)
sink?.next(result)
}
fun onUserEvent2(e : Event)
{
val result = process(e)
sink?.next(result)
}
....
}
But this does not work, since I am supposed to immediately call next on the SynchronousSink<Result> passed to me in Flux::generate. I cannot store the sink as in the example:
reactor.core.Exceptions$ErrorCallbackNotImplemented:
java.lang.IllegalStateException: The generator didn't call any of the
SynchronousSink method
I was also thinking about the Flux::merge and Flux::concat methods, but these are static and they create a new Flux. I just want to push things into the existing flux, such that whoever holds it, gets notified.
Based on my limited understanding of the reactive types, this is supposed to be a common use case. Yet I find it very difficult to actually implement it. This brings me to a suspicion that I am missing something crucial or that I am using the library in an odd way, in which it was not intended to be used. If this is the case, any advice is warmly welcome.