Develop Reference

How can I use data from another flow data in flow? (Kotlin Flow)

I wrote the code as below.
suspend fun getDataByRegion(): Flow<Result?> {
// getRegion() return Flow<Region>
return getRegion().map { region: Region ->
repository.requestDataFromServer(region)
}
}
The problem is that repository.requestDataFromServer(region) called twice.
So I think I should use operators like zip or combine.
When using these operators, how can the second flow use the data of the first flow?

With combine and zip operators you can not depend on the other's result. So in general your chaining approach with map is OK.
There is several options you have:
Assuming your repository method is not called from anywhere else, the reason for it being called twice is that the region Flow is emitting twice. So try to find out why this is the case.
Anyhow if your region Flow method returns the same region twice you can fix it by simply adding
.distinctUntilChanged() after getRegion() like:
getRegion().distinctUntilChanged().map { region: Region ->
repository.requestDataFromServer(region)
}
It will make sure your region Flow doesn't emit redundantly with the same data. Alternatively add distinctUntilChanged() directly to the repository method, if this is always the expected behavior.
Ask yourself if this method really needs to return a stream (Flow). I guess you need a stream since the region can change at runtime and you want something in your app to update automatically? But if not you could simply convert the stream to a single result:
val region = getRegion().first()
repository.requestDataFromServer(region)

BehaviorSubject vs PublishSubject

I'm trying to get my head around the golden rule (if any) about:
When to use BehaviorSubject ?
and
When to use PublishSubject ?
The difference between them is very clear
There are many kinds of subjects. For this specific requirement, a PublishSubject works well because we wish to continue the sequence from where it left off. So assuming events 1,2,3 were emitted in (B), after (A) connects back we only want to see 4, 5, 6. If we used a ReplaySubject we would see [1, 2, 3], 4, 5, 6; or if we used a BehaviorSubject we would see 3, 4, 5, 6 etc.
(source : How to think about Subjects in RxJava (Part 1))
I have seen that Subject's are used in two contexts (at least), UI context and listener context.
UI context (MVVM as example)
For example here a BehaviorSubject is used, and it's clear why they use Subject and not Observable but I have changed the BehaviorSubject to PublishSubject but the app behavior still the same.
Listener context
Why they make project field a BehaviorSubject and not PublishSubject ?

The main difference between PublishSubject and BehaviorSubject is that the latter one remembers the last emitted item. Because of that BehaviorSubject is really useful when you want to emit states.
Why they make project field a BehaviorSubject and not PublishSubject ?
Probably because they want to be able to retrieve the last emitted project with this method:
#Override public #NonNull Observable<Project> project() {
return this.project;
}

PublishSubject: Starts empty and only emits new elements to subscribers.
There is a possibility that one or more items may be lost between the time the Subject is created and the observer subscribes to it because PublishSubject starts emitting elements immediately upon creation.
BehaviorSubject: It needs an initial value and replays it or the latest element to new subscribers. As BehaviorSubject always emits the latest element, you can’t create one without giving a default initial value.
BehaviorSubject is helpful for depicting "values over time". For example, an event stream of birthdays is a Subject, but the stream of a person's age would be a BehaviorSubject.

Publish Subject: Here, if a student entered late into the classroom, he just wants to listen from that point of time when he entered the classroom. So, Publish will be the best for this use-case.
Behavior Subject: Here, if a student entered late into the classroom, he wants to listen the most recent things(not from the beginning) being taught by the professor so that he gets the idea of the context. So, here we will use Behavior.

The difference on BehaviourSubject and PublishSubject relies on how long they keep the data they captures, in instance the PublishSubject only keeps the data available at moment and keeps updating on every entry while BehaviourSubject keeps the last data inserted, so you may use for example to confirm password on a signup form and as an example for PublishSubject, performing a search and it has to update the data constantly in order to give accurate results and there's no too much necessity to compare data that are being inserted.
As reference i leave this two photos from http://reactivex.io/documentation/subject.html
PublishSubject
BehaviourSubject

Manually trigger a RxJava combinelatest flowable

So i have a scenario in which i want to combine the newest results of two flowables and do something with it.
Flowable.combineLatest(
info,
list,
BiFunction { ... }
)
In certain conditions, i need to be able to get the the results again, and do some different stuff from before. So i could manually store the results of combinelatest somewhere, and then just reuse them but i was thinking, maybe there is a way to add a third flowable, and trigger onNext manually so the results are propagated again. Is this possible?

There are two approaches to keeping the computed value around for later use. You can create a BehaviorSubject that acts as an intermediate variable, that when defined will have the computed value, or you can publish() the observable so that newer subscribers will get the most recent results.
BehaviorSubject intermediateResult = BehaviorSubject.create();
Flowable.combineLatest(info, list, ...)
.subscribe( intermediateResult );
Alternatively,
Observable<Type> intermediateResult = Flowable.combineLatest(info, list, ...)
.replay(1)
.publish();
In either case, subscribing to intermediateResult will get the most recent computed value, if it is present.
Edit: make the function selectable on the fly:
Observable<FunctionSelector> fnSelector;
Observable<Type> intermediateResult =
Flowable.combineLatest(info, list, fnSelector,
(information, listToUse, selector) ->
getFunction(selector).apply(information, listToUse))
.replay(1)
.publish(1);

RxJava: How to wait for all subscriptions to complete?

I am fairly new to rxJava, trying stuff by my own. I would like to get some advice if I'm doing it right.
Usecase: On the first run of my app, after a successful login I have to download and save in a local database several dictionaries for the app to run with. The user has to wait till the downloading process finishes.
Current solution: I am using retrofit 2 with rxjava adapter in order to get the data. I am bundling all Observables into one using the zip operator. After all downloads are done the callback triggers and saving into database begins.
Nothing speaks better than some code:
Observable<List<OrderType>> orderTypesObservable = backendService.getOrderTypes();
Observable<List<OrderStatus>> orderStatusObservable = mockBackendService.getOrderStatuses();
Observable<List<Priority>> prioritiesObservable = backendService.getPriorities();
return Observable.zip(orderTypesObservable,
orderStatusObservable,
prioritiesObservable,
(orderTypes, orderStatuses, priorities) -> {
orderTypeDao.deleteAll();
orderTypeDao.insertInTx(orderTypes);
orderStatusDao.deleteAll();
orderStatusDao.insertInTx(orderStatuses);
priorityDao.deleteAll();
priorityDao.insertInTx(priorities);
return null;
});
Questions:
Should I use the zip operator or is there a better one to fit my cause?
It seems a bit messy doing it this way. This is only a part of the code, I have currently 12 dictionaries to load. Is there a way to refactor it?
I would like to insert a single dictionary data as soon as it finishes downloading and have a retry mechanism it the download fails. How can I achieve that?

I think in your case it's better to use Completable, because for you matter only tasks completion.
Completable getAndStoreOrderTypes = backendService.getOrderTypes()
.doOnNext(types -> *store to db*)
.toCompletable();
Completable getAndStoreOrderStatuses = backendService.getOrderStatuses()
.doOnNext(statuses -> *store to db*)
.toCompletable();
Completable getAndStoreOrderPriorities = backendService.getOrderPriorities()
.doOnNext(priorities -> *store to db*)
.toCompletable();
return Completable.merge(getAndStoreOrderTypes,
getAndStoreOrderStatuses,
getAndStoreOrderPriorities);
If you need serial execution - use Completable.concat() instead of merge()
a retry mechanism if the download fails
Use handy retry() operator

It is not good, to throw null value object into Rx Stream (in zip your return null, it is bad).
Try to not doing that.
In your case, you have 1 api call and 2 actions to save response into the database, so you can create the chain with flatMap.
It will look like:
backendService.getOrderTypes()
.doOnNext(savingToDatabaseLogic)
.flatMap(data -> mockBackendService.getOrderStatuses())
.doOnNext(...)
.flatMap(data -> backendService.getPriorities())
.doOnNext(...)
if you want to react on error situation, in particular, observable, you can add onErrorResumeNext(exception->Observable.empty()) and chain will continue even if something happened
Also, you can create something like BaseDao, which can save any Dao objects.

RxJava and Cached Data

I'm still fairly new to RxJava and I'm using it in an Android application. I've read a metric ton on the subject but still feel like I'm missing something.
I have the following scenario:
I have data stored in the system which is accessed via various service connections (AIDL) and I need to retrieve data from this system (1-n number of async calls can happen). Rx has helped me a ton in simplifying this code. However, this entire process tends to take a few seconds (upwards of 5 seconds+) therefore I need to cache this data to speed up the native app.
The requirements at this point are:
Initial subscription, the cache will be empty, therefore we have to wait the required time to load. No big deal. After that the data should be cached.
Subsequent loads should pull the data from cache, but then the data should be reloaded and the disk cache should be behind the scenes.
The Problem: I have two Observables - A and B. A contains the nested Observables that pull data from the local services (tons going on here). B is much simpler. B simply contains the code to pull the data from disk cache.
Need to solve:
a) Return a cached item (if cached) and continue to re-load the disk cache.
b) Cache is empty, load the data from system, cache it and return it. Subsequent calls go back to "a".
I've had a few folks recommend a few operations such as flatmap, merge and even subjects but for some reason I'm having trouble connecting the dots.
How can I do this?

Here are a couple options on how to do this. I'll try to explain them as best I can as I go along. This is napkin-code, and I'm using Java8-style lambda syntax because I'm lazy and it's prettier. :)
A subject, like AsyncSubject, would be perfect if you could keep these as instance states in memory, although it sounds like you need to store these to disk. However, I think this approach is worth mentioning just in case you are able to. Also, it's just a nifty technique to know.
AsyncSubject is an Observable that only emits the LAST value published to it (A Subject is both an Observer and an Observable), and will only start emitting after onCompleted has been called. Thus, anything that subscribes after that complete will receive the next value.
In this case, you could have (in an application class or other singleton instance at the app level):
public class MyApplication extends Application {
private final AsyncSubject<Foo> foo = AsyncSubject.create();
/** Asynchronously gets foo and stores it in the subject. */
public void fetchFooAsync() {
// Gets the observable that does all the heavy lifting.
// It should emit one item and then complete.
FooHelper.getTheFooObservable().subscribe(foo);
}
/** Provides the foo for any consumers who need a foo. */
public Observable<Foo> getFoo() {
return foo;
}
}
Deferring the Observable. Observable.defer lets you wait to create an Observable until it is subscribed to. You can use this to allow the disk cache fetch to run in the background, and then return the cached version or, if not in cache, make the real deal.
This version assumes that your getter code, both cache fetch and non- catch creation, are blocking calls, not observables, and the defer does work in the background. For example:
public Observable<Foo> getFoo() {
Observable.defer(() -> {
if (FooHelper.isFooCached()) {
return Observable.just(FooHelper.getFooFromCacheBlocking());
}
return Observable.just(FooHelper.createNewFooBlocking());
}).subscribeOn(Schedulers.io());
}
Use concatWith and take. Here we assume our method to get the Foo from the disk cache either emits a single item and completes or else just completes without emitting, if empty.
public Observable<Foo> getFoo() {
return FooHelper.getCachedFooObservable()
.concatWith(FooHelper.getRealFooObservable())
.take(1);
}
That method should only attempt to fetch the real deal if the cached observable finished empty.
Use amb or ambWith. This is probably one the craziest solutions, but fun to point out. amb basically takes a couple (or more with the overloads) observables and waits until one of them emits an item, then it completely discards the other observable and just takes the one that won the race. The only way this would be useful is if it's possible for the computation step of creating a new Foo to be faster than fetching it from disk. In that case, you could do something like this:
public Observable<Foo> getFoo() {
return Observable.amb(
FooHelper.getCachedFooObservable(),
FooHelper.getRealFooObservable());
}
I kinda prefer Option 3. As far as actually caching it, you could have something like this at one of the entry points (preferably before we're gonna need the Foo, since as you said this is a long-running operation) Later consumers should get the cached version as long as it has finished writing. Using an AsyncSubject here may help as well, to make sure we don't trigger the work multiple times while waiting for it to be written. The consumers would only get the completed result, but again, that only works if it can be reasonably kept around in memory.
if (!FooHelper.isFooCached()) {
getFoo()
.subscribeOn(Schedulers.io())
.subscribe((foo) -> FooHelper.cacheTheFoo(foo));
}
Note that, you should either keep around a single thread scheduler meant for disk writing (and reading) and use .observeOn(foo) after .subscribeOn(...), or otherwise synchronize access to the disk cache to prevent concurrency issues.

I’ve recently published a library on Github for Android and Java, called RxCache, which meets your needs about caching data using observables.
RxCache implements two caching layers -memory and disk, and it counts with several annotations in order to configure the behaviour of every provider.
It is highly recommended to use with Retrofit for data retrieved from http calls. Using lambda expression, you can formulate expression as follows:
rxCache.getUser(retrofit.getUser(id), () -> true).flatmap(user -> user);
I hope you will find it interesting :)

Take a look at the project below. This is my personal take on things and I have used this pattern in a number of apps.
https://github.com/zsiegel/rxandroid-architecture-sample
Take a look at the PersistenceService. Rather than hitting the database (or MockService in the example project) you could simply have a local list of users that are updated with the save() method and just return that in the get().
Let me know if you have any questions.