I'm trying to do a simple search UI, where the text change triggers a search in the service and that gets mapped to a ViewState. It would seem easy, but the following code doesn't work:
queryText.filter { it.length > 3 }
.switchMap { service.search(it) }
.onErrorReturn { SearchResponse(null, it.message) }
.map { SearchViewState(items = it.items, error = it.error) }
.startWith { SearchViewState(loading = true) }
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe { viewState.onNext(it) }
I've no idea what I did wrong, but through debugging I can see that the stream throws a NetworkOnMainThreadException and then terminates so new events are no longer processed.
What is the correct way to do this?
I assume queryText is the source of textchanges which happen on the main thread. Therefore subscribeOn has no effect on it. You should apply subscribeOn to the actual network call:
queryText.filter { it.length > 3 }
.switchMap {
service.search(it)
.subscribeOn(Schedulers.io())
.onErrorReturn { SearchResponse(null, it.message) }
.map { SearchViewState(items = it.items, error = it.error) }
.startWith ( SearchViewState(loading = true) )
}
.observeOn(AndroidSchedulers.mainThread())
.subscribe { viewState.onNext(it) }
In addition, I think you have to do the error recovery and state changes associated with the particular network call, otherwise a failure will stop the entire sequence.
Related
I have a chain of API calls in RxJava, and when one fails I need to abort the chain and handle the error. But each failure needs to be handled differently. I tried this:
netRequestOne()
.onErrorResumeNext {
handleErrorOne()
Single.error(it)
}
.flatMap {
netRequestTwo()
}
.onErrorResumeNext {
handleErrorTwo()
Single.error(it)
}
// more flatMaps with requests...
.subscribeOn(Schedulers.io())
.observeOn(AndroidSchedulers.mainThread())
.subscribe(
{
// deal with success
},
{
// no-op
}
)
But if a request throws an exception, all of the subsequent onErrorResumeNext()'s are called, not just the one tied to that request.
You can achieve the requested behavior for example with this:
val requestOne = Single.just("Response 1")
//.doOnSuccess { throw RuntimeException("Fail second request") } // (1)
.doOnError {
println("handleErrorOne")
}
val requestTwo = Single.just(10)
//.doOnSuccess { throw RuntimeException("Fail second request") } // (2)
.doOnError {
println("handleErrorTwo")
}
requestOne
.flatMap { oneResult -> requestTwo.map { twoResult -> Pair(oneResult, twoResult) } }
.doOnSuccess { responses: Pair<String, Int> ->
println(responses)
}
.flatMap { Single.just("More flatMaps") }
.subscribe({}, {})
You can uncomment (1) and/or (2) to simulate a fail in the first or second request. In case, both requests end successfully, responses are combined and you do some other processing.
so i tried to use onErrorReturn to return the result that i wanted but it will complete the stream afterwards, how do i catch the error return as Next and still continue the stream?
with code below, it wont reach retryWhen when there is error and if i flip it around it wont re-subscribe with retryWhen if there is an error
fun process(): Observable<State> {
return publishSubject
.flatMap { intent ->
actAsRepo(intent) // Might return error
.map { State(data = it, error = null) }
}
.onErrorReturn { State(data = "", error = it) } // catch the error
.retryWhen { errorObs ->
errorObs.flatMap {
Observable.just(State.defaultState()) // continue subscribing
}
}
}
private fun actAsRepo(string: String): Observable<String> {
if (string.contains('A')) {
throw IllegalArgumentException("Contains A")
} else {
return Observable.just("Wrapped from repo: $string")
}
}
subscriber will be
viewModel.process().subscribe(this::render)
onError is a terminal operator. If an onError happens, it will be passed along from operator to operator. You could use an onError-operator which catches the onError and provides a fallback.
In your example the onError happens in the inner-stream of the flatMap. The onError will be propagated downstream to the onErrorReturn opreator. If you look at the implementation, you will see that the onErrorReturn lambda will be invoked, the result will be pushed downstream with onNext following a onComplete
#Override
public void onError(Throwable t) {
T v;
try {
v = valueSupplier.apply(t);
} catch (Throwable e) {
Exceptions.throwIfFatal(e);
downstream.onError(new CompositeException(t, e));
return;
}
if (v == null) {
NullPointerException e = new NullPointerException("The supplied value is null");
e.initCause(t);
downstream.onError(e);
return;
}
downstream.onNext(v); // <--------
downstream.onComplete(); // <--------
}
What is the result of your solution?
Your stream completes because of: #retryWhen JavaDoc
If the upstream to the operator is asynchronous, signalling onNext followed by onComplete immediately may result in the sequence to be completed immediately. Similarly, if this inner {#code ObservableSource} signals {#code onError} or {#code onComplete} while the upstream is active, the sequence is terminated with the same signal immediately.
What you ought to do:
Place the onErrorReturn behind the map opreator in the flatMap. With this ordering your stream will not complete, when the inner-flatMap stream onErrors.
Why is this?
The flatMap operator completes, when the outer (source: publishSubject) and the inner stream (subscription) both complete. In this case the outer stream (publishSubject) emits onNext and the inner-stream will complete after sending { State(data = "", error = it) } via onNext. Therefore the stream will remain open.
interface ApiCall {
fun call(s: String): Observable<String>
}
class ApiCallImpl : ApiCall {
override fun call(s: String): Observable<String> {
// important: warp call into observable, that the exception is caught and emitted as onError downstream
return Observable.fromCallable {
if (s.contains('A')) {
throw IllegalArgumentException("Contains A")
} else {
s
}
}
}
}
data class State(val data: String, val err: Throwable? = null)
apiCallImpl.call will return an lazy observable, which will throw an error on subscription, not at observable assembly time.
// no need for retryWhen here, except you want to catch onComplete from the publishSubject, but once the publishSubject completes no re-subscription will help you, because the publish-subject is terminated and onNext invocations will not be accepted anymore (see implementation).
fun process(): Observable<State> {
return publishSubject
.flatMap { intent ->
apiCallImpl.call(intent) // Might return error
.map { State(data = it, err = null) }
.onErrorReturn { State("", err = it) }
}
}
Test
lateinit var publishSubject: PublishSubject<String>
lateinit var apiCallImpl: ApiCallImpl
#Before
fun init() {
publishSubject = PublishSubject.create()
apiCallImpl = ApiCallImpl()
}
#Test
fun myTest() {
val test = process().test()
publishSubject.onNext("test")
publishSubject.onNext("A")
publishSubject.onNext("test2")
test.assertNotComplete()
.assertNoErrors()
.assertValueCount(3)
.assertValueAt(0) {
assertThat(it).isEqualTo(State("test", null))
true
}
.assertValueAt(1) {
assertThat(it.data).isEmpty()
assertThat(it.err).isExactlyInstanceOf(IllegalArgumentException::class.java)
true
}
.assertValueAt(2) {
assertThat(it).isEqualTo(State("test2", null))
true
}
}
Alternative
This alternative behaves a little bit different, than the first solution. The flatMap-Operator takes a boolean (delayError), which will result in swallowing onError messages, until the sources completes. When the source completes, the errors will be emitted.
You may use delayError true, when the exception is of no use and must not be logged at the time of appearance
process
fun process(): Observable<State> {
return publishSubject
.flatMap({ intent ->
apiCallImpl.call(intent)
.map { State(data = it, err = null) }
}, true)
}
Test
Only two values are emitted. The error will not be transformed to a fallback value.
#Test
fun myTest() {
val test = process().test()
publishSubject.onNext("test")
publishSubject.onNext("A")
publishSubject.onNext("test2")
test.assertNotComplete()
.assertNoErrors()
.assertValueAt(0) {
assertThat(it).isEqualTo(State("test", null))
true
}
.assertValueAt(1) {
assertThat(it).isEqualTo(State("test2", null))
true
}
.assertValueCount(2)
}
NOTE: I think you want to use switchMap in this case, instead of flatMap.
I have edit text with value "11491992"
sometimes when try to edit it, app is freezed and logcat has this
Timeout waiting for IME to handle input event after 2500 ms: com.google.android.inputmethod.latin/com.android.inputmethod.latin.LatinIME
[Update]
I have some EditText views and use RxBinding to control enable/disable submit button based on these EditText views
val bag = CompositeDisposable()
RxTextView.textChanges(edFirstName)
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.map { it.toString().trim() }
.subscribe {
btnSubmit.isEnabled = it.isNotBlank()
updateRequest.firstName = it
}.addTo(bag)
RxTextView.textChanges(edLastName)
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.map { it.toString().trim() }
.subscribe {
btnSubmit.isEnabled = it.isNotBlank()
updateRequest.lastName = it
}.addTo(bag)
This code is OK.
val bag = CompositeDisposable()
RxTextView.textChanges(edFirstName)
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.map { it.toString().trim() }
.subscribe {
btnSubmit.isEnabled = it.isNotBlank()
}.apply { bag.add(this) }
RxTextView.textChanges(edLastName)
.observeOn(AndroidSchedulers.mainThread())
.subscribeOn(Schedulers.io())
.map { it.toString().trim() }
.subscribe {
btnSubmit.isEnabled = it.isNotBlank()
}.apply { bag.add(this) }
}
ANR happens when a long operation is taking place on the main thread. If this thread is busy, Android cannot process any further GUI events in the application, and thus throws up an ANR Application Not Responding dialog.
From the source code of android.view.inputmethod.InputMethodManager see this function void finishedInputEvent(int seq, boolean handled, boolean timeout) { ... }
if (timeout) {
Log.w(TAG, "Timeout waiting for IME to handle input event after "
+ INPUT_METHOD_NOT_RESPONDING_TIMEOUT + " ms: " + p.mInputMethodId);
} else {
mH.removeMessages(MSG_TIMEOUT_INPUT_EVENT, p);
}
Also always try to handle all timeconsuming operations on any thread other than the main thread.
Update 1:
see How an app hanged without an ANR?
You should use profiler screen.
LeakCanary if memory leak.
I'm using a travel API which I first hit with a request to create a session and then I use the session URL returned from that URL to then call until its status parameter returns UpdatesComplete.
Here's what I have so far:
lateinit var pollUrl: String
travelInteractor.createSession("LHR", "AKL", "2018-04-20", "2018-04-22")
.doOnSubscribe {
loading.postValue(true)
}
.flatMap { url ->
pollUrl = url
travelInteractor.pollResults(pollUrl)
.retryWhen {
it.delay(1000, TimeUnit.MILLISECONDS)
}
}
.doOnNext {
if (it.status != "UpdatesComplete") travelInteractor.pollResults(pollUrl)
.retryWhen {
it.delay(1000, TimeUnit.MILLISECONDS)
}
}
.subscribe({
// Subscription stuff
)}
What's currently happening is that it will call doOnNext() and then it will make the network poll but I won't be capturing the subscription and also won't chain another poll. Is there a more efficient way I can be writing this?
Solution
Thanks to iagreen I managed to achieve this with:
lateinit var pollUrl: String
travelInteractor.createSession("LHR", "AKL", "2018-04-20", "2018-04-22")
.doOnSubscribe {
loading.postValue(true)
}
.flatMap { url ->
travelInteractor.pollResults(url)
.retryWhen {
it.delay(1000, TimeUnit.MILLISECONDS)
}
.repeatWhen {
it.delay(1000, TimeUnit.MILLISECONDS)
}
.filter {
it.itineraries.map { ... } // Use response here appropriately and then check status
it.status == "UpdatesComplete"
}
.take(1)
}
.subscribe({
// Subscription stuff
)}
I am assuming your pollResults(url) method returns a Single or an Observable that behaves like a single -- it returns one result and then onComplete. If that is truly the case, you can use repeatWhen to retry the request on success and retryWhen to retry on error. See the code below.
skyScannerInteractor.createSession("LHR", "AKL", "2018-04-20", "2018-04-22")
.doOnSubscribe {
loading.postValue(true)
}
.flatMap { url ->
skyScannerInteractor.pollResults(url)
.repeatWhen { complete -> complete.delay(1, TimeUnit.SECONDS) }
.retryWhen { errors -> errors.delay(1, TimeUnit.SECONDS) }
.filter({ it.status == "UpdatesComplete" })
.take(1) // Take the first valid value and complete
}
.subscribe({
// Subscription stuff
)}
A little explanation -
repeatWhen/retryWhen will try the request every second.
filter will cause elements with the wrong status to be ignored.
When you get the first status == "UpdatesComplete" element, take(1) will emit that value and complete -- this will have the effect of cancelling the retries.
Note: In the case of an error, retrying a network request forever is usually the wrong thing to do. I recommend you modify the retryWhen above to suit you use case to terminate in the event of network failure. For example, you could retry three times and then propagate the error. See this article for some examples on how you could do that. It is also a good reference on repeatWhen/retryWhen.
retry() and retryWhen() both respond to an onError event in the Observable, that is why it isn't actually retrying; you're not receiving those onError events in your pollResults() Observable. Right now, your retrying code doesn't actually depend on the JSON response.
There are two ways I would think about going about this:
Throw an exception in your pollResults() Observable if the JSON response is unsatisfactory. This should trigger the retryWhen(). You'll need to test for it in the Observable somewhere.
Reorganize your Observable like this:
`
lateinit var pollUrl: String
skyScannerInteractor.createSession("LHR", "AKL", "2018-04-20", "2018-04-22")
.doOnSubscribe {
loading.postValue(true)
}
.flatMap { url ->
pollUrl = url
skyScannerInteractor.pollResults(pollUrl)
}
.doOnNext {
if (it.status != "UpdatesComplete") {
throw IOException("Updates not complete.") //Trigger onError
}
}
.retryWhen { //Retry the Observable (createSession) when onError is called
it.delay(1000, TimeUnit.MILLISECONDS)
}
.subscribe({
// Will give result only when UpdatesComplete
}
I have a simple case i'm trying to do with rxJava 2 but i'm stuck.
I have a locationProvider which returns a Maybe (some model with LatLng). Each time a user clicks on the button, I want to get his current location and save the location to the db.
Just to be clear,
The RxView.clicks(save_btn) should be on the MainThread, the location and db save should be on an async thread, and response should come back to mainThread.
How should I do this?
addDisposeable(RxView.clicks(save_btn)
.flatMap { locationProvider.getLastKnowLocation().toObservable() }
.map {
val place = Place(UUID.randomUUID().toString(), "test-address", it.latLng)
db.placeDao().insertAll(place)
}
.observeOn(AndroidSchedulers.mainThread())
.subscribe({
Toast.makeText(this#AddPlaceActivity, "saved", Toast.LENGTH_SHORT).show()
}, { throwable -> Timber.e(throwable) }))
I've also tried to simplify it to this:
RxView.clicks(save_btn).share()
.flatMap { locationProvider.getLastKnowLocation().toObservable() }
.subscribe({
val place = Place(UUID.randomUUID().toString(), "test-address", it.latLng)
db.placeDao().insertAll(place)
Timber.d("place-saved")
}, { throwable -> Timber.e(throwable) }))
But this code only execute for the first click and doesn't continue after.
Is it due to the Maybe.toObservable()? how should it be resolved?
Thanks for your help.
This is the locationProvider's code, i'm using RxLocation:
fun getLastKnowLocation(): Maybe<LocationData> {
return rxLocation.location()
.lastLocation()
.map {
val address = geocoder.getFromLocation(it.latitude, it.longitude, 1).first()
val latlng = LatLng(it.latitude, it.longitude)
LocationData(latlng, address)
}
}
Unfortunately,the user who set me in the correct path deleted his answer :(
This is what I ended up with
addDisposeable(
RxView.clicks(save_btn).share()
.observeOn(Schedulers.computation())
.withLatestFrom(locationProvider.getLastKnowLocation().toObservable(), BiFunction { _:Any, l:LocationData -> l })
.map {
val place = Place(UUID.randomUUID().toString(), "test-address", it.latLng)
db.placeDao().insertAll(place)
}
.observeOn(AndroidSchedulers.mainThread())
.subscribe({
Timber.d("place-saved")
}, { throwable -> Timber.e(throwable) }))
I couldn't find a nicer way for the 'BiFunction' part, if anyone has something nicer instead.
Also note that you need to call observeOn twice for the thread switching part.