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    Dorus
    @Dorus
    observeOn is merely a hotfix that will ensure the main thread isnt tied up long while you process an event.

    Oh and to come back to your question

    Should the library enforce its clients to always call an .observeOn() after any call to that method?

    No, instead it would be best practice for clients to not do any long computations on the event dispatcher. If you dont do anything long running, it's way more efficient to simply borrow the already active thread, as context switching is expensive on itself. If you do need to do long running computations, it's always a smart idea to schedule these in the background, preferably in parallelle.

    Renan Ferrari
    @renanferrari
    @Dorus I'm aware this is not a problem with RxJava, I just want to know how to make RxJava work, properly, with this kind of listener.
    Dorus
    @Dorus
    Oh and in Rx it's simple to do that: source.flatMap(e => longRunning(e), computationScheduler)
    David Karnok
    @akarnokd
    subscribeOn is provided as the means to move the subscription side effects to another thread. Many sources, such as most listener APIs don't have subscription side effects and subscribeOn is completely ineffective. When these sources emit, that can happen from any thread. UI-like sources emit from the main thread, dedicated sources emit from their own background thread. In order to process these the required place, you should use observeOn. In addition, you may want to run your own single-threaded scheduler via Schedulers.from(Executors.newSingleThreadedExecutor()) which guarantees observing on it from multiple stages will end up on the same thread in a serialized manner.
    Dorus
    @Dorus
    ^^ on the RxJs gitter people are always impressed with my knowledge, but in here @akarnokd words things so much better.
    David Karnok
    @akarnokd
    @Dorus how does that work in RxJS? Whenever a source signals, it queues that value and schedules a task to drain that particular queue on the given scheduler, right?
    Dorus
    @Dorus
    @akarnokd Well the Js people care surprisingly little about threading :)
    They always tell me Js is single-threaded.
    I'm a bit of a weirdo there too, because i know a lot about Rx so i'm good help there, but my Js knowledge is limited as i'm more of a Java/C# programmer in origine.
    David Karnok
    @akarnokd
    There is a logical evolution in the Rx ecosystem that works the other direction as well. For example, if you know the fusion-enabled RxJava 2 deep enough, you can leave off "features" and end up with Rx.NET or RxJS.
    Renan Ferrari
    @renanferrari
    @akarnokd Great explanation of .subscribeOn()! Thanks for that. I'm just not so sure if I understood your suggested solution with .observeOn() and also what you meant by "guarantees observing from multiple stages".
    David Karnok
    @akarnokd
    When you have observeOn() multiple times in a sequence because you route computation back and forth. Schedulers.computation() will hand out a Scheduler that provides separate thread (from a fixed set) to each use of observeOn and it is very unlikely two observeOn will run on the same thread.
    Serban Balamaci
    @balamaci
    Hi guys, just to confirm my understanding of the backpressure operators:
        Flowable<Integer> flowable = subject
                    .toFlowable(BackpressureStrategy.MISSING)
                    .onBackpressureBuffer(5)
                    .onBackpressureDrop(val -> log.info("Dropped {}", val));
            flowable = flowable.observeOn(Schedulers.io(), false, 3);
            subscribeWithSlowSubscriber(flowable);
    this is not working in a way like buffer 5 elements on overflow and then start dropping events
    because backpressureDrop subscribes to the previous backpressureBuffer operator and requests Long.MAX_VALUE from it, so backpressureBuffer always sees that the downstream is ready for all it has, so it never overflows
    Serban Balamaci
    @balamaci
    so the only backpressure action happens in onBackpressureDrop
    David Karnok
    @akarnokd
    Serban Balamaci
    @balamaci
    Hi @akarnokd , I know about the overloaded onBackpressureBuffer, I just wanted to validate that it makes no sense to chain onBackpresureXXX one after another
    and I also think it makes no sense to have any BackpressureStrategy other than MISSING in Flowable.create() if you plan to follow it with an onBackpressureXXX.
    Serban Balamaci
    @balamaci
    Incidently it seem in reactor-core there is no equivalent of the rxjava's variant of onBackpressure with and Action and an overflowStrategy
    David Karnok
    @akarnokd
    They are a bit behind with appropriating features from RxJava 2, even so they have now two dedicated and financed persons for that.
    huirong628
    @huirong628
    hello,everyone
    Wolfhard Prell
    @Cir0X

    Hey! Are there some operators with which I can achieve something described in the following?

    For example I have a inheritance heriachy like: Condition as parent and ConditionA, ConditionB, ConditionC are children of Condition.
    Than I have a Method which looks like this:

    public Observable<Condition> getCondition() {...}

    which returns indefinitely Condition's.

    The goal would be a chaining an operator which caches the Condition's and when there is one available of each (ConditionA, ConditionB, ConditionC),
    it should should filter them as described in the filter.
    Maybe something like this:

    getCondition()
        .cacheFilter<ConditionA, ConditionB, ConditionC>((a, b, c) -> a.value == 0 && b.value == 0 && c.value == 0)
            .do(somethingA())
        .cacheFilter<ConditionA, ConditionB, ConditionC>((a, b, c) -> a.value == 0 && b.value == 1 && c.value == 1)
            .do(somethingB())
        .cacheFilter<ConditionA, ConditionB, ConditionC>((a, b, c) -> a.value == 1 && b.value == 0 && c.value == 0)
            .do(somethingB())
        .subscribe();
    Ann
    @WeiWW
    Hello!
    Dorus
    @Dorus
    @Cir0X Instead of emitting all conditions on 1 stream, you should have 3 streams and combine these streams. Could be done with a number of operators, my gut feeling is combineLatest(conditionA, conditionB, conditionC) would work best. You also seem to be doing a.value everywhere, you could add in a .map(a -> a.value) so you can look at the value directly later.
    Next there are a few options to act on this stream. I wouldn't filter if you want to do all operations on the same stream, as filter takes out elements and you wont be able to act on them after that. Instead you can make a large do or subscribe block where you test all conditions one by one, or you can simply subscribe to the condition stream multiple times, and filter out the correct elements. Myself i would then do .filter((arr) -> !arr[0]).filter((arr) -> !arr[1]).filter((arr) -> !arr[2]) instead of !arr[0] && !arr[1] && !arr[2].
    If you subscribe multiple times, that means the source stream will also run multiple times. Depending on the source, you might want to multicast instead. You can do that with share().
    Another interesting solution would be to use .publish(selector), like this:
    getCondition().publish(_conditions -> Observable.merge(
        _conditions.filter(a -> a[0] == 0).filter(a -> a[1] == 0).filter(a -> a[2] == 0).do(() -> sometihngA()),
        _conditions.filter(a -> a[0] == 0).filter(a -> a[1] == 1).filter(a -> a[2] == 1).do(() -> sometihngB()),
        _conditions.filter(a -> a[0] == 0).filter(a -> a[1] == 1).filter(a -> a[2] == 0).do(() -> sometihngC())
      )).subscribe();
    Mmm looking back i think the && style would be just as good :)
    Alex Reisberg
    @a-reisberg
    Quick question: the rxjava 1.* has this .asObservable for subjects
    rxjava 2.* doesn't have that anymore
    Thanks!
    so if I have a subject and I want to turn it to an observable, what's a good way to do it?
    Serban Balamaci
    @balamaci
    you can make it a Flowable which is basically an Observable with a backpressure strategy by doing
                .toFlowable(BackpressureStrategy.MISSING)
    or whatever overflow strategy you prefer maybe .toFlowable(BackpressureStrategy.BUFFER)
    Alex Reisberg
    @a-reisberg
    Thanks!
    I just found hide
    can I use that too?
    Serban Balamaci
    @balamaci
    I don't know what hide does, I think it prevents rxjava to do some optimizations like operator fusion, so it should not relate to what you want to do.
    Alex Reisberg
    @a-reisberg
    I see. All I really want to do is to hide the publish aspect of my Subject
    Serban Balamaci
    @balamaci
    I don't understand, both Subject, Observable, Flowables are some kind of Publishers as they allow subscribing to them. I understand that Observables are kind of deprecated in rxjava2 in favor of Flowables which force you to think about backpressure upfront(you need to specify a backpressure strategy when you create them), so why would you need an Observable. Anyway looks like a Flowable can simply be turned into an Observable by doing flowable.toObservable
    Alex Reisberg
    @a-reisberg
    I guess I'm trying to move from Rx 1 and haven't fully understood exactly what the difference is
    also my question was unclear. On a Subject you can do a onNext
    (which is essentially publishing to other Observers)
    and I wanted to hide the onNext
    I didn't know that Observables are in the process of being deprecated?
    Justin Tuchek
    @justintuchek
    I highly doubt Observable is on any path to being deprecated. It’s just different from Flowable, where it wouldn’t make sense to discard events (such of cursor movements).
    Serban Balamaci
    @balamaci
    I'd say not deprecated, but not much different than Flowable as I do not see reasons where I'd want to use Observables instead of Flowables(which have the benefit that you are aware of backpressure and what the backpressure strategy is and you won't be surprised at runtime by a MissingBackpressuException)
    Justin Tuchek
    @justintuchek
    From reading the Observable source code from 2.x.x it seems to be utilizing an unbounded amount for input events - and from the docs of 2.0 it seems like you are going to hit an OOM instead.
    Serban Balamaci
    @balamaci
    I think so, then it would be equivalent to a Flowable if we'd do a .toFlowable(BackpressureStrategy.BUFFER)
    which is also unbounded