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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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Reducing operators


While developing applications, you may face such a situation where you may need to accumulate and consolidate emissions. Note that nearly all the operators under this criteria will only work on a finite producer (Observable/Flowable) that calls onComplete() because typically, we can consolidate only finite datasets. We will explore this behavior as we cover these operators.

Here is a short list of reducing operators, which we will cover in this chapter:

  • count
  • reduce
  • all
  • any
  • contains

Counting emissions (count operator)

The count operator subscribes to a producer, counts the emissions, and emits a Single, containing the count of emissions by the producer.

Here is an example:

    fun main(args: Array<String>) { 
      listOf(1,5,9,7,6,4,3,2,4,6,9).toObservable() 
      .count() 
      .subscribeBy { println("count $it") } 
    } 

The following is the output:

As we can see from the output, this operator counts the emissions from the producer, and emits the count once it receives...

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