Book Image

Reactive Programming in Kotlin

By : Rivu Chakraborty
Book Image

Reactive Programming in Kotlin

By: Rivu Chakraborty

Overview of this book

In today's app-driven era, when programs are asynchronous, and responsiveness is so vital, reactive programming can help you write code that's more reliable, easier to scale, and better-performing. Reactive programming is revolutionary. With this practical book, Kotlin developers will first learn how to view problems in the reactive way, and then build programs that leverage the best features of this exciting new programming paradigm. You will begin with the general concepts of Reactive programming and then gradually move on to working with asynchronous data streams. You will dive into advanced techniques such as manipulating time in data-flow, customizing operators and provider and how to use the concurrency model to control asynchronicity of code and process event handlers effectively. You will then be introduced to functional reactive programming and will learn to apply FRP in practical use cases in Kotlin. This book will also take you one step forward by introducing you to Spring 5 and Spring Boot 2 using Kotlin. By the end of the book, you will be able to build real-world applications with reactive user interfaces as well as you'll learn to implement reactive programming paradigms in Android.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Dedication
Preface

Parallel execution versus concurrency


The concepts of concurrency and parallelization are not only related, but they are deeply connected to each other; you may think of them as identical twin brothers. They look almost the same, but there are differences. Let's try to discover.

In the previous example, we discussed concurrency, but it seemed to execute in parallel. Now, let's take a better example, which will not only help us understand parallelization, but will allow us to understand the differences between concurrency and parallelization as well.

Think of a hotel with 5 customers who ordered 15 dishes. These 15 dishes represent identical tasks, and each of them require to be cooked by a chef. Now, as with the previous example, think of the cooks as threads (in the previous example, you and your family member were playing the role of a cook in your home), but rather than sharing sub-parts of a dish, they will cook each dish at a time (because, obviously, there are 15 orders!).

Now, if you...