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Intro to Functional Reactive Programming Juan Gomez

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• "Original FRP" refers to denotational and continuous-time functional programming using behaviors and events. • Rx is reactive programming combined with functional programming techniques. • Great post about the name controversy by André Staltz https://medium.com/@andrestaltz/why-i-cannot-say-frp- but-i-just-did-d5ffaa23973b Wait, you mean Reactive Programming?

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Agenda • Brief introduction to Rx and why we want to use it. • Observables and useful operators to transform Observables. • Intermediate concepts around RxJava

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What Is Functional Reactive Programming? • A style of programming based on two key ideas: continuous time-varying behaviors, and event-based reactivity. • Popularized by Erik Meijer when he created the Rx library for .NET while at Microsoft.

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What are Reactive Extensions? • It’s a library that allows you to use FRP in many Programming Language • Allows you to represent asynchronous data streams with “Observables” • And to parameterize the concurrency in those asynchronous data streams using “Schedulers”.

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What are Reactive Extensions? • Abstracts away concerns about things like: ✦ low-level threading ✦ synchronization ✦ thread-safety ✦ concurrent data structures.

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Rx Family • C#: Rx.NET • JavaScript: RxJS • RxJava (Java, Scala, Groovy, Clojure, Kotlin) • Ruby: Rx.rb • Python: RxPY • More at: http://reactivex.io/

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Why Functional Reactive Programming • Writing concurrent programs correctly is difficult. • You can transform & compose asynchronous operations. • High-level abstractions • Standard error handling

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Multithreading is hard! This is a lesson I seem to learn every few years: multithreading is hard.
 Once you think you now understand it and are an expert, you are heading soon to another painful lesson that multithreading is hard. Dianne Hackborn April 2012

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Push vs Pull

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Observables event Iterable (pull) Observable (push) retrieve data T next() onNext(T) discover error throws Exception onError(Exception) complete !hasNext() onCompleted() Using the concept of “duality” we can derive the Observable type from an Iterable

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onNext, onCompleted, onError An Observer implements a subset of the following methods: • onNext: We call this method whenever the Observable emits an item. • onError: Call this method to indicate that the Observable has failed and will not make further calls to onNext or onCompleted. • onCompleted: Call this method after you have called onNext for the final time and if we have not encountered any errors.

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The “Subscribe” method

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No Magic! • “Make the Magic go away” By Uncle Bob Martin: http://blog.8thlight.com/uncle-bob/2015/08/06/let- the-magic-die.html • Write a primitive Rx framework in JavaScript: http://reactivex.io/learnrx/

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RxJava • It’s a JVM implementation of Reactive Extensions • Started at Netflix but now Open Sourced • Supports Java 6+ & Android 2.3+ • Java 8 lambda support

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RxJava on Java 7 aObservable.filter(new Func1() { public Boolean call(Integer n) { return n % 2 == 0; } }) .map(new Func1() { public Integer call(Integer n) { return n * n; } }) .subscribe(new Action1() { public void call(Integer n) { System.out.println(n); } });

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Retrolambda Retrolambda lets you take advantage of Java 8 features like lambda expressions, method references and try-with-resources statements on Java 7, 6 or 5. • Retrolambda • https://github.com/orfjackal/retrolambda • Gradle plugin • https://github.com/evant/gradle-retrolambda

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RxJava using Retrolambda aObservable.filter(n -> n % 2 == 0) .map(n -> n * n) .subscribe(System.out::println);

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Taken from https://gist.github.com/staltz/868e7e9bc2a7b8c1f754 by André Staltz

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Operators in RxJava aObservable.map(x -> x*x) //Square .reduce((a, b) -> a+b) //Sum .subscribe(x -> println(x)); //Show

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Marble diagrams Check out http://rxmarbles.com

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Creating an Observable

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Creating an Observable List aList = ...; ob = Observable.create(subscriber -> { try { for (String s : aList) { if (subscriber.isUnsubscribed()) return; subscriber.onNext(s); } subscriber.onCompleted(); } catch (Exception e) { subscriber.onError(e); } });

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Creating an Observable List aList = ...; Observable ob = Observable.from(aList);

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Creating an Observable Observable> ob = Observable.just(aList); Observable ob2 = Observable.just("Some String");

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Creating an Observable • repeat( ) • range( ) • interval( ) • timer( ) • empty( ) • error( ) • More at: https://github.com/ReactiveX/RxJava/wiki/Creating- Observables

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Transforming Observables

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Transforming Observables Observable.range(0, 5) .map(x -> toBinaryString(x*x)) .subscribe(s -> println(s), err -> err.printStackTrace(), () -> println("done")); 0 1 100 1001 10000 done

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Transforming Observables

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Transforming Observables 1 2 2 3 3 3 Observable.range(1, 3) .flatMap(x -> Observable.just(x).repeat(x)) .subscribe(System.out::println);

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Filtering Observables

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Filtering Observables 0 2 4 6 8 Observable.range(0, 10) .filter(x -> (x % 2) == 0) .subscribe(System.out::println);

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Filtering Observables • distinct( ) • first( ) • take( ) • skip( ) • elementAt( ) • sample( ) • more... • More at: https://github.com/ReactiveX/RxJava/wiki/Filtering-Observables

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Aggregate Operators

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Aggregate Operators 3628800 Observable.range(1, 10) .reduce((a, b) -> a*b) .subscribe(System.out::println);

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Combining Observables

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Combining Observables a_A b_B c_C Observable lower = Observable.from(new String[]{"a", "b", "c"}); Observable upper = Observable.from(new String[]{"A", "B", "C"}); Observable.zip(lower, upper, Pair::create) .map(pair -> pair.first +"_" +pair.second) .subscribe(System.out::println);

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Schedulers • observeOn • specify on which Scheduler a Subscriber should observe the Observable • subscribeOn • specify which Scheduler an Observable should use when its subscription is invoked • https://github.com/ReactiveX/RxJava/wiki/ Scheduler

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Backpressure • Backpressure is the situation in which an Observable is emitting items more rapidly than an operator or subscriber can consume them. • RxJava offers a variety of strategies like throttling with which you can exercise flow control in order to alleviate the problems caused by backpressure. • https://github.com/ReactiveX/RxJava/wiki/Backpressure

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Hot and Cold Observables • A “cold” Observable waits to start emitting items until an observer subscribes, and so an observer can “observe” the whole sequence. • A “hot” Observable may begins emitting items as soon as it is created.

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RxAndroid • Android specific bindings for RxJava. • https://github.com/ReactiveX/RxAndroid • Scheduler on main UI thread or a given Android Handler thread. • AndroidSchedulers • HandlerScheduler

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RxAndroid

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Summary • Embrace Reactive and Functional Thinking • Manipulating Streams of data simplifies how you think (and build) your apps. • RxJava is a powerful tool to improve your Android Code

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Useful links • Grokking RxJava by Dan Lew: http://blog.danlew.net/2014/09/15/grokking-rxjava-part-1/ • Introduction to Reactive Programming by André Staltz https://gist.github.com/staltz/868e7e9bc2a7b8c1f754 • Guide to Rx Operators: http://reactivex.io/documentation/operators.html • RxJava docs: https://github.com/ReactiveX/RxJava/wiki/

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We’re hiring! Senior Software Engineer - Android http://nflx.io/android-job Many more at: http://netflix.com/jobs

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Thank You! Twitter: @_juandg Email: jgomez@netflix.com Lanyrd: lanyrd.com/profile/juandg/