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 Flowable and Subscriber

Pretty much all the Observable factories and operators you learned up to this point also apply to Flowable. On the factory side, there are Flowable.range(), Flowable.just(), Flowable.fromIterable(), and Flowable.interval(). Most of these sources support backpressure. Their usage is generally the same as the Observable equivalent.

However, consider Flowable.interval(), which pushes time-based emissions at fixed time intervals. Can this be backpressured? Contemplate the fact that each emission is tied to the time it emits. If we slowed down Flowable.interval(), our emissions would no longer reflect the specified time interval and become misleading. Therefore, Flowable.interval() is one of those few cases in the standard API that can throw MissingBackpressureException the moment the downstream starts backpressuring. In the following example...