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

Summary

In this chapter, you learned how to leverage buffering, windowing, throttling, and switching to cope with a rapidly emitting Observable. Ideally, we should leverage Flowable and backpressure when we see that an Observable is emitting faster than an Observer can keep up with, which we will learn about in the next chapter. But for situations where backpressure cannot work, such as user inputs or timer events, you can leverage one of the four categories of operationsbuffering, windowing, throttling, or switching—to limit how many emissions are passed downstream.

In the next chapter, we will learn about handling backpressure using Flowable, which provides a more proactive way to cope with a common case of rapid emissions that overwhelm an Observer.