RxJava

Introducing ReactiveAirplaneMode

2017-08-15 Android, Open source, RxJava No comments

I’m continuing Rxfication of the Android. Recently I released brand new library called ReactiveAirplaneMode. As you may guess, it allows listening Airplane mode on Android device with RxJava observables. A usual I’ve hidden all implementation details, BroadcastReceivers and rest of the Android related stuff behind RxJava abstraction layer, so API is really simple. Just take a look on that:

ReactiveAirplaneMode.create()
    .observe(context)
    .subscribeOn(Schedulers.io())
    .observeOn(AndroidSchedulers.mainThread())
    .subscribe(isOn -> textView.setText(String.format("Airplane mode on: %s", isOn.toString())));

In the code above subscriber will be notified only when airplane mode changes.

If you want to read airplane mode and then listen to it, you can use the following method:

ReactiveAirplaneMode.create()
    .getAndObserve(context)
    .subscribeOn(Schedulers.io())
    .observeOn(AndroidSchedulers.mainThread())
    .subscribe(isOn -> textView.setText(String.format("Airplane mode on: %s", isOn.toString())));

If you want to check airplane mode only once, you can use get(context) method, which returns Single<Boolean> value:

ReactiveAirplaneMode.create()
    .get(context)
    .subscribeOn(Schedulers.io())
    .observeOn(AndroidSchedulers.mainThread())
    .subscribe(isOn -> textView.setText(String.format("Airplane mode on: %s", isOn.toString())));

If you want to check airplane mode only once without using Reactive Streams, just call isAirplaneModeOn(context) method:

boolean isOn = ReactiveAirplaneMode.create().isAirplaneModeOn(context);

You can add this library to your project via Gradle:

dependencies {
  compile 'com.github.pwittchen:reactiveairplanemode:0.0.1'
}

If you want to know more details, see sample app, documentation & tests, check repository with the source code at: https://github.com/pwittchen/ReactiveAirplaneMode.

Releasing ReactiveNetwork v. 0.10.0

2017-07-20 Android, Open source, RxJava No comments

I’ve recently released ReactiveNetwork library v. 0.10.0 for RxJava1.x and RxJava2.x.
ReactiveNetwork is an Android library listening network connection state and Internet connectivity with RxJava Observables, which I’m developing for approximately 2 years now.

In this version, I’ve done a few bug fixes and added new features for RxJava2.x version.

Below, you can find the release notes:

Release for RxJava1.x

  • bumped RxJava1 version to 1.3.0
  • bumped test dependencies
  • created Code of Conduct
  • updated Kotlin version in sample apps
  • added retrolambda to the sample Java app – issue #163
  • fixed behavior of network observing in disconnected state – issue #159

Release for RxJava2.x

  • bumped RxJava2 version to 2.1.1
  • bumped test dependencies
  • created Code of Conduct
  • updated unit tests
  • updated Kotlin version in sample apps
  • added retrolambda to the sample Java app – issue #163
  • fixed behavior of network observing in disconnected state – issue #159
  • added the following methods to ReactiveNetwork class:
    • Single<Boolean> checkInternetConnectivity()
    • Single<Boolean> checkInternetConnectivity(InternetObservingStrategy strategy)
    • Single<Boolean> checkInternetConnectivity(String host, int port, int timeoutInMs)
    • Single<Boolean> checkInternetConnectivity(String host, int port,
      int timeoutInMs, ErrorHandler errorHandler)
    • Single<Boolean> checkInternetConnectivity(InternetObservingStrategy strategy,
      String host, int port, int timeoutInMs,
      ErrorHandler errorHandler)

You can add it to your project via Gradle:

RxJava1.x:

dependencies {
  compile 'com.github.pwittchen:reactivenetwork:0.10.0'
}

RxJava2.x:

dependencies {
  compile 'com.github.pwittchen:reactivenetwork-rx2:0.10.0'
}

Now, in RxJava2.x version, we have the possibility to check Internet connectivity once without any pooling with new Single type. It may be helpful in the specific use-cases when we’re focusing on smaller battery usage, a smaller amount of data being sent over the network and lower number of network connections.

I’m planning to publish more real life usage examples of this library in the future articles on this blog.

I have plans for a few updates in the next version. If you’re interested in this project or you’re using it, please stay tuned and keep an eye on it at GitHub.

Release of prefser v. 2.1.0 with RxJava2 support

2017-06-19 Android, Java, Open source, RxJava 2 comments

I’ve recently released new version of prefser library for Android. In case you don’t know, it’s a wrapper for Android SharedPreferences with object serialization and RxJava Observables. This version has the new artifact, which has codebase migrated to RxJava2.x. As usual, I kept backward compatibility with RxJava1.x.

You can find more details about the project at https://github.com/pwittchen/prefser.

If you want to use it in your mobile project, you need the following dependencies in the build.gradle file:

dependencies {
  compile 'com.github.pwittchen:prefser-rx2:2.1.0'
  compile 'io.reactivex:rxandroid:2.0.1'
}

Short release notes can be found at https://github.com/pwittchen/prefser/releases.

This update was requested by at least two developers on GitHub and it’s my second most popular project, so I hope you’ll find it useful if you’re in the process of migrating from RxJava1.x to RxJava2.x. I still have 4 remaining RxJava1.x libraries waiting for the upgrade. If you want to perform any updates via Pull Requests, you’re more than welcome.

New reactive data types in RxJava2

2017-05-31 DSP2017, Java, RxJava No comments

Introduction

I’m still exploring reactive programming world and RxJava library. Recently, I’ve migrated a few of my open-source libraries from RxJava1 to RxJava2 and written yet another project in RxJava2 from the beginning. Nevertheless, I’m still learning this library and its concept. It’s very wide topic. In RxJava1 we simply had one reactive data type called Observable. In RxJava2, we have more data types like Observable, Flowable, Single, Maybe & Completable. In this article, I’ll briefly explain their purpose and tell you when to use which. The general idea behind these types is code semantics. We should tell consumer of our code, what he or she can expect from our API. Introducing more reactive data types can increase readability and stability of our code base.

Observable

Observable is basically the same Reactive type, we had in RxJava1. It doesn’t have backpressure support.

We should use Observable, when:

  • our data source emits less than 1000 items, so there’s practically no chance of occurring OutOfMemoryException
  • we are working with GUI events, which usually don’t occurs very often and don’t have to be backpressured
  • we are working with synchronous code on legacy JVM like Java 1.6 and we want to have streams features like in Java 8

Observable

Flowable

Flowable type has very similar semantics to Observable. We can operate on Flowable streams with map, flatmap, filter, etc. in the same way as on the Observable type. The main difference is backpressure support.

We should use Flowable when we are:

  • dealing with 10k+ elements in a stream
  • dealing with frequent events (e.g. sensors readings)
  • reading/parsing files from disk
  • reading values from database through JDBC
  • using network/streaming I/O
  • reading/writing to many blocking or pull-based data sources

To learn more, read note about Observable vs. Flowable on wiki of RxJava2 on GitHub.

Single

Single reactive type has been redesigned from scratch in RxJava 2. It’s designed to handle just one event in an asynchronous manner. Good application of this type is single HTTP request when we expect just one response or error and nothing else. It can emit on onSuccess (single value) or onError event (error).

Single

Maybe

Maybe represents a deferred computation and emission of a maybe value or exception. Maybe is a wrapper around an operation/event that may have either:

  • A single result
  • Error
  • No result

Just take a look at the scheme.

The interface of the main consumer of this type have the following methods: onSuccess, onError, onComplete. Conceptually, Maybe is a union of Single and Completable providing the means to capture an emission pattern where there could be 0 or 1 item or an error signaled by some reactive source.

Maybe

Completable

Completable type can be used when we have an Observable that we don’t care about the value resulted from the operation (result is void). It handles only onComplete and onError events. Conceptually, Maybe is a union of Single and Completable providing the means to capture an emission pattern where there could be 0 or 1 item or an error signalled by some reactive source.

Read more about Maybe type on RxJava wiki.

Summary

As we can see, RxJava2 gives us new types, which can help explain our intentions more clearly. We can adjust concrete type to the specific situation. In addition, we can use backpressure for the data sources, which emit a lot of elements to make our projects more robust and stable. Last, but not least RxJava2 is compatible with Reactive Streams API, which is going to be part of the Java 9 specification.

References

Introducing YaaS Java SDK

2017-05-28 DSP2017, Hybris, Java, Open source, RxJava, YaaS No comments

Introduction

In my company, there’s a concept of so-called “innovation day”. I have the possibility to “use” 1 innovation day per 2 development sprints. Last year, I used only 1 day due to the tight release schedule and a lot of work. Now, we are right after release, so I had time to take innovation day once again. I’ve decided to create YaaS Java SDK. If you don’t know what the YaaS is, check out my previous article about Basic usage of YaaS proxy for the microservice. In a few words, it’s a proxy for the microservices with authorization & monitoring capabilities, which allows using other services available on the YaaS market. SDK created by me is really simple, was created in a short period of time and does not cover all features of the YaaS. This SDK allows performing authorized requests to the microservices hidden behind YaaS proxy.

Tech stack used for this project is as follows:

For unit testing I used:

Quick start

I wanted to make this SDK as simple as possible so the user can add YaaS integration to the Java application within just a few lines of code.

YaaSProject project = new YaaSProject.Builder()
    .withClientId("YOUR_CLIENT_ID")
    .withClientSecret("YOUR_CLIENT_SECRET")
    .withOrganization("YOUR_ORGANIZATION")
    .withService("YOUR_SERVICE")
    .withVersion("v1")
    .withZone(Zone.EU)
    .build();

Client client = new YaaS(project);

client.get("path/to/your/endpoint")
    .subscribe(response -> System.out.println(response.body().string()));

As you can see, it looks really simple and straightforward. In the code snippet above, we’ve done the following thigs:

  1. Defined YaaS Project with YaaS service
  2. Created YaaS Client
  3. Performed HTTP GET request to the endpoint of the microservice asynchronously
  4. Received and printed body of the HTTP response from the microservice on the current thread as a String

All of that was done with Single type from RxJava2, which wraps Response type from OkHttp. We have a reactive stream of HTTP response here and we can do with it whatever RxJava2 offers us. Like filtering, mapping, throttling, combining it with other stream and so on.

For more information, visit repository of the project at: https://github.com/pwittchen/yaas-java-sdk.

Future plans

I have the following plans related to this project, which may be realized when I’ll have time:

  • Add more unit tests (I didn’t have enough time to cover all cases)
  • Add continuous integration
  • Integrate YaaS with SAP Hybris Backoffice or SAP Hybris Core Platform through this SDK (PoC)
  • YaaS Android SDK (copy YaaS Java SDK, downgrade it to Java 7 & optionally migrate to Kotlin and create sample mobile app)
  • Optionally, add more features to YaaS Java SDK
  • Optionally, deploy an artifact to Maven Central repository
  • Optionally, create SDKs for different programming languages (especially those I don’t know well or I don’t know at all – just to learn them)

Links

Interesting links related to this article:

Joining lists of RxJava Observables

2017-05-15 DSP2017, Java, RxJava No comments

In RxJava we have a few operators for joining Observables. The most common are:

Take a look at the documentation in these links. It has interactive marble diagrams showing how the operators work on the streams. You can move marbles along the lines and see how the output stream changes. It really helps to understand how it works.

Code snippets in this article are based on RxJava 2.1.0 with JUnit 4.12 and Google Truth 0.32 for unit tests.

Let’s say, we have the following Observables:

public Observable<String> emitNumbers() {
  return Observable.fromArray("1", "2", "3", "4").delay(1, TimeUnit.SECONDS);
}

public Observable<String> emitLetters() {
  return Observable.fromArray("a", "b", "c", "d");
}

We can merge them in the different ways.

Concat

Concat operator emits the emissions from two or more Observables without interleaving them.

We can perform the following operation:

public Observable<String> concatStreams() {
  return Observable.concat(emitNumbers(), emitLetters());
}

The easiest way to verify, how this operator works, is to create exploratory unit test as follows:

@Test
public void shouldConcatStreams() {
  // given
  Observable<String> observable = playground.concatStreams();
  List<String> expectedValues = Arrays.asList("1","2","3","4","a","b","c","d");
  List<String> joinedValues = new ArrayList<>();

  // when
  observable.blockingSubscribe(s -> joinedValues.add(s));

  // then
  assertThat(joinedValues).isEqualTo(expectedValues);
}

This operation can be represented graphically as well.

         1 --- 2 --- 3 --- 4
                  |
         a --- b --- c --- d
                  |
                  |
                concat
                  |
                 \|/
1 -- 2 -- 3 -- 4 --- a -- b -- c -- d  

As we can see one stream is appended to another regardless of the execution time of both streams.

Merge

Merge operator combines multiple Observables into one by merging their emissions.

Here we have a similar story, but changed operator:

public Observable<String> mergeStreams() {
  return Observable.merge(emitNumbers(), emitLetters());
}

We are writing another unit test:

@Test
public void shouldMergeStreams() {
  // given
  Observable<String> observable = playground.mergeStreams();
  List<String> expectedValues = Arrays.asList("a","b","c","d","1","2","3","4");
  List<String> joinedValues = new ArrayList<>();

  // when
  observable.blockingSubscribe(s -> joinedValues.add(s));

  // then
  assertThat(joinedValues).isEqualTo(expectedValues);
}

Merge operation should look like that:

         1 --- 2 --- 3 --- 4
                  |
         a --- b --- c --- d
                  |
                  |
                merge
                  |
                 \|/
a -- b -- c -- d --- 1 -- 2 -- 3 -- 4

This operator doesn’t synchronize the streams and merges them as values are emitted. Numbers are emitted later than letters, so letters are placed in the beginning of the output stream. Try to manipulate marble on the interactive diagram on the reactivex.io website to see how it should work.

Zip

The last operator, I’d like to discuss in this article is “Zip” operator. Zip combines the emissions of multiple Observables together via a specified function and emit single items for each combination based on the results of this function.

In simple words, it waits until many observables are emitted and then combines them into a pair (or triple Observable, etc. in the case or more Observables).

Now, we need to create a function, which will transform our streams and return combined stream.

public Observable<String> zipStreams() {
  return Observable.zip(emitNumbers(), emitLetters(),
      (s1, s2) -> String.format("(%s,%s)", s1, s2));
}

Next, we can verify it with test as usual:

@Test
public void shouldZipStreams() {
  // given
  Observable<String> observable = playground.zipStreams();
  List<String> expectedValues = Arrays.asList("(1,a)","(2,b)","(3,c)","(4,d)");
  List<String> joinedValues = new ArrayList<>();

  // when
  observable.blockingSubscribe(s -> joinedValues.add(s));

  // then
  assertThat(joinedValues).isEqualTo(expectedValues);
}

and it can be represented graphically like that:

        1 --- 2 --- 3 --- 4
                 |
        a --- b --- c --- d
                 |
                 |
                zip
                 |
                \|/
 (1,a) -- (2,b) --- (3,c) -- (4,d)

Now, we have pairs of merged streams.

Summary

Of course, RxJava is complicated library and these methods are not covering all possibilities of merging and combining the Observable streams. Neverhteless, examples in this article are quite basic and may help you to understand how mentioned operators work. After that we can apply the best operator to appropriate situation.


Reference thread on StackOverflow: http://stackoverflow.com/questions/28843318/android-rxjava-joining-lists

Emitting different RxJava Observables depending on the condition

2017-05-14 DSP2017, Java, RxJava No comments

Sometimes, we may need to emit different RxJava Observables depending on the specific condition dynamically. Moreover, it’s good to do it right without breaking a chain (stream of Observables). We want to combine different Observables together and do not want to nest one subscription inside another subscription because this will lead us to “subscription hell” similar to “callback hell”. Luckily RxJava has mechanisms to deal with such problems. In this article, I’m basing my examples on RxJava 2.1.0.

Let’s say we have two Observables:

public Observable<String> trueObservable() {
  return Observable.fromCallable(() -> "trueObservable");
}

public Observable<String> falseObservable() {
  return Observable.fromCallable(() -> "falseObservable");
}

and we have another Observable wrapping Boolean value:

public Observable<Boolean> createCondition(boolean returnedValue) {
  return Observable.fromCallable(() -> returnedValue);
}

This Observable can emit true or false depending on the provided parameter.

What we want to do is to:

  • emit trueObservable() when createCondition(boolean) returns true
  • emit falseObservable() when createCondition(boolean) returns false
  • emit falseObservable() when createCondition(boolean) emits empty Observable (default behaviour)

We can do it in the following way:

public Observable<String> emitTrueObservableDynamically() {
  return createCondition(true)
      .defaultIfEmpty(false)
      .flatMap(condition -> condition ? trueObservable() : falseObservable());
}

In such case, this method will emit trueObservable(). When we change parameter of the createCondition(boolean) method to false, Observable will emit falseObservable(). When we replace createCondition(boolean) method with Observable.empty(), method will return falseObservable() by default. As we can see, it’s easily solved with flatMap and defaultIfEmpty operators.

This is quite useful technique, which we can apply to reactive applications to control our flow without breaking the chain. Please note, it’s just an example you can create more complicated constructions and handle more complicated types than just boolean and more than two use cases.


Reference thread for this article on StackOverflow: http://stackoverflow.com/questions/34195218/rxjava-exequte-observable-only-if-first-was-empty.

ReactiveNetwork – release v. 0.9.0 with RxJava2.x support

2017-04-11 Android, DSP2017, Java, Open source, RxJava No comments

This time, I upgraded my another reactive Android open-source project called ReactiveNetwork to RxJava2.x. Many thanks goes to @tushar-acharya who performed initial migration to the newer version of RxJava. During migration, I’ve also created new package rx2 to avoid potential import conflicts during migration inside Android apps. Besides migration, I’ve updated sample apps, documentation & JavaDocs on Github pages. You can still use RxJava1.x version and it’s available on the branch with that name.

To use brand new ReactiveNetwork compatible with RxJava2.x, add the following dependency to your build.gradle file:

dependencies {
  compile 'com.github.pwittchen:reactivenetwork-rx2:0.9.0'
}

If you still want or need to use RxJava1.x, use the following dependency:

dependencies {
  compile 'com.github.pwittchen:reactivenetwork:0.9.0'
}

New updates and bug-fixes are on the way. Right now I have a few issues in the project backlog.

Feel free to contribute to this project and report new issues! Any constructive feedback will be appreciated.

ReactiveBeacons – release of v. 0.6.0 with support for RxJava2

2017-04-03 Android, Bluetooth Low Energy, DSP2017, Java, Open source, RxJava No comments

Thanks to @BugsBunnyBR I released new version of ReactiveBeacons library with the RxJava2.x support. It’s an Android library scanning BLE (Bluetooth Low Energy) beacons nearby with RxJava Observables. I also kept backward compatibility with RxJava1.x. Different versions of the libraries are located on the separate git branches. It’s a similar approach to original RxJava project. I have separate builds on Travis CI, separate artifacts and JavaDocs. Such approach generates more overhead, but in such case, RxJava1.x can be kept in a maintenance mode and RxJava2.x can be a subject of the future development.

What has been done in this version?

  • migrated library to RxJava2.x on RxJava2.x branch and released it as reactivebeacons-rx2 artifact
  • kept library compatible with RxJava1.x on a RxJava1.x branch and released it as reactivebeacons artifact
  • removed master branch
  • bumped library dependencies
  • added permission annotations
  • organized Gradle configuration
  • transformed instrumentation unit tests to pure java unit tests
  • started executing unit tests on Travis CI server
  • created separate JavaDoc for RxJava1.x and RxJava2.x

If you want to add RxJava2.x version to your Android project, add the following dependency to build.gradle file:

dependencies {
  compile 'com.github.pwittchen:reactivebeacons-rx2:0.6.0'
}

For RxJava1.x you can use old artifact id:

dependencies {
  compile 'com.github.pwittchen:reactivebeacons:0.6.0'
}

This library was one of the first experiments with my migrations to RxJava2.x. I have plans to migrate rest of my libraries soon.
Thanks to the awesome open-source community on GitHub, this process goes faster and I don’t have to do everything by myself.

ReactiveNetwork – new releases & roadmap

2016-06-10 Android, Java, Open source, RxJava No comments

Recent updates

I’ve recently released version 0.3.0 of ReactiveNetwork library for Android. As you can see in the release notes, it contains a lot of updates.
Highlights:

  • Deprecated methods related to monitoring WiFi Access Points and WiFi Singal level in favor of ReactiveWiFi project, which has this functionality extracted from ReactiveNetwork
  • Deprecated methods and enums related to monitoring connectivity with The Internet
  • Added Observables, which allows monitoring Internet connectivity basing on socket connection with a remote host (we can also monitor specific host with given parameters)

Roadmap for the future versions

Updates planned for 0.4.0:

  • Removing deprecated methods
  • Removing unused permissions from AndroidManifest.xml

Track progress of releasing 0.4.0 on GitHub

Updates planned for 0.5.0:

  • Updating library code with respect to the updates in Android 5 and 6 (especially ConnectivityManager) related to monitoring network connectivity mentioned in issue #62 on GitHub
  • Creating strategy interface to keep backward compatibility with Pre-Lollipop devices, so we’ll be able to monitor network in a different way depending on the given Android version

Track progress of releasing 0.5.0 on GitHub

Another future updates (not related to any version):
These updates are also important, but they’re not related to library API

  • Adding example of library usage with Retrofit (without breaking reactive stream chain)

Track progress of resolving this issue on GitHub

Final thoughts

Currently, it’s my most popular open-source project and people rely on it in production apps, so I’m trying to keep it as simple and as good as I can with respect to the recent updates of Android SDK. I’m getting really good feedback from people on GitHub and seriously considering it during the development process. If something bothers you in that project, don’t hesitate to create an Issue or new Pull Request on GitHub.