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Learning RxJava

By : Nield

5 (10)

Learning RxJava

5 (10)

By: Nield

Overview of this book

RxJava is a library for composing asynchronous and event-based programs using Observable sequences for the JVM, allowing developers to build robust applications in less time. Learning RxJava addresses all the fundamentals of reactive programming to help readers write reactive code, as well as teach them an effective approach to designing and implementing reactive libraries and applications. Starting with a brief introduction to reactive programming concepts, there is an overview of Observables and Observers, the core components of RxJava, and how to combine different streams of data and events together. You will also learn simpler ways to achieve concurrency and remain highly performant, with no need for synchronization. Later on, we will leverage backpressure and other strategies to cope with rapidly-producing sources to prevent bottlenecks in your application. After covering custom operators, testing, and debugging, the book dives into hands-on examples using RxJava on Android as well as Kotlin.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

Thinking Reactively

Thinking Reactively

A brief history of ReactiveX and RxJava

Thinking reactively

Why should I learn RxJava?

Setting up

A quick exposure to RxJava

RxJava 1.0 versus RxJava 2.0 - which one do I use?

When to use RxJava

Summary

Observables and Subscribers

Observables and Subscribers

The Observable

The Observer interface

Cold versus hot Observables

Other Observable sources

Single, Completable, and Maybe

Disposing

Summary

Basic Operators

Basic Operators

Suppressing operators

Transforming operators

Reducing operators

Collection operators

Error recovery operators

Action operators

Summary

Combining Observables

Combining Observables

Merging

Concatenation

Ambiguous

Zipping

Combine latest

Grouping

Summary

Multicasting, Replaying, and Caching

Multicasting, Replaying, and Caching

Understanding multicasting

Automatic connection

Replaying and caching

Subjects

Summary

Concurrency and Parallelization

Concurrency and Parallelization

Why concurrency is necessary

Concurrency in a nutshell

Introducing RxJava concurrency

Understanding Schedulers

Understanding subscribeOn()

Understanding observeOn()

Parallelization

unsubscribeOn()

Summary

Switching, Throttling, Windowing, and Buffering

Switching, Throttling, Windowing, and Buffering

Buffering

Windowing

Throttling

Switching

Grouping keystrokes

Summary

Flowables and Backpressure

Flowables and Backpressure

Understanding backpressure

Understanding the Flowable and Subscriber

Creating a Flowable

Using onBackpressureXXX() operators

Using Flowable.generate()

Summary

Transformers and Custom Operators

Transformers and Custom Operators

Transformers

Using to() for fluent conversion

Operators

Custom Transformers and operators for Singles, Maybes, and Completables

Using RxJava2-Extras and RxJava2Extensions

Summary

Testing and Debugging

Testing and Debugging

Configuring JUnit

Blocking subscribers

Blocking operators

Using TestObserver and TestSubscriber

Manipulating time with the TestScheduler

Debugging RxJava code

Summary

RxJava on Android

RxJava on Android

Creating the Android project

Using RxJava and RxAndroid

Other RxAndroid bindings libraries

Life cycles and cautions using RxJava with Android

Summary

Using RxJava for Kotlin New

Using RxJava for Kotlin New

Why Kotlin?

Configuring Kotlin

Kotlin basics

Extension operators

Using RxKotlin

Dealing with SAM ambiguity

Using let() and apply()

Tuples and data classes

Future of ReactiveX and Kotlin

Summary

Appendix

Appendix

Introducing lambda expressions

Functional types

Mixing object-oriented and reactive programming

Materializing and Dematerializing

Understanding Schedulers

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Buffering

The buffer() operator will gather emissions within a certain scope and emit each batch as a list or another collection type. The scope can be defined by a fixed buffer sizing or a timing window that cuts off at intervals or even slices by the emissions of another Observable.

Fixed-size buffering

The simplest overload for buffer() accepts a count argument that batches emissions in that fixed size. If we wanted to batch up emissions into lists of eight elements, we can do that as follows:

import io.reactivex.Observable;

public class Launcher {    
public static void main(String[] args) {
     Observable.range(1,50)
               .buffer(8)
               .subscribe(System.out::println);
   }
}

The output is as...

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