Book Image

Learning RxJava - Second Edition

By : Nick Samoylov, Thomas Nield
Book Image

Learning RxJava - Second Edition

By: Nick Samoylov, Thomas Nield

Overview of this book

RxJava is not just a popular library for building asynchronous and event-based applications; it also enables you to create a cleaner and more readable code base. In this book, you’ll cover the core fundamentals of reactive programming and learn how to design and implement reactive libraries and applications. Learning RxJava will help you understand how reactive programming works and guide you in writing your first example in reactive code. You’ll get to grips with the workings of Observable and Subscriber, and see how they are used in different contexts using real-world use cases. The book will also take you through multicasting and caching to help prevent redundant work with multiple Observers. You’ll then learn how to create your own RxJava operators by reusing reactive logic. As you advance, you’ll explore effective tools and libraries to test and debug RxJava code. Finally, you’ll delve into RxAndroid extensions and use Kotlin features to streamline your Android apps. By the end of this book, you'll become proficient in writing reactive code in Java and Kotlin to build concurrent applications, including Android applications.
Table of Contents (22 chapters)
1
Section 1: Foundations of Reactive Programming in Java
5
Section 2: Reactive Operators
12
Section 3: Integration of RxJava applications
Appendix B: Functional Types
Appendix E: Understanding Schedulers

Understanding observeOn()

The subscribeOn() operator instructs the source Observable which Scheduler to emit emissions on. If subscribeOn() is the only concurrent operation in an Observable chain, the thread from that Scheduler will work the entire Observable chain, pushing emissions from the source all the way to the final Observer. The observeOn() operator, however, will intercept emissions at that point in the Observable chain and switch them to a different Scheduler going forward.

Unlike subscribeOn(), the placement of observeOn() matters. It leaves all operations upstream on the default or subscribeOn()-defined Scheduler, but switches to a different Scheduler downstream. In the following example, an Observable emits a series of strings (that are /-separated values), which are then split on an I/O Scheduler. But after that, the observeOn() operator switches to a computation...