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Reactive Programming in Kotlin

Reactive Programming in Kotlin

By : Rivu Chakraborty
2.3 (3)
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Reactive Programming in Kotlin

Reactive Programming in Kotlin

2.3 (3)
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 (13 chapters)
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BackpressureStrategy.MISSING and onBackpressureXXX()


BackpressureStrategy.MISSING implies that it'll not implement any backpressure strategy, so you need to explicitly tell Flowable which backpressure strategy to follow. The onBackpressureXXX() operators help you achieve the same, while providing you with some additional configuration options.

There are mainly three types of onBackpressureXXX() operators available:

  • onBackpressureBuffer()
  • onBackpressureDrop()
  • onBackpressureLatest()

Operator onBackpressureBuffer()

This operator serves the purpose of BackpressureStrategy.BUFFER; except that here, you'll get some extra configuration options, such as buffer size, bounded or unbounded, and more. You may omit the configurations as well to use the default behavior.

So, let's look at some examples:

    fun main(args: Array<String>) { 
      val source = Observable.range(1, 1000) 
      source.toFlowable(BackpressureStrategy.MISSING)//(1) 
        .onBackpressureBuffer()//(2) 
        .map { MyItem11...
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Reactive Programming in Kotlin
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