Observables, Observers, and Subjects | Reactive Programming in Kotlin

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Reactive Programming in Kotlin

By : Rivu Chakraborty

2.3 (3)

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.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

A Short Introduction to Reactive Programming

A Short Introduction to Reactive Programming

What is reactive programming?

Reasons to adapt functional reactive programming

Reactive Manifesto

Getting started with RxKotlin

The ReactiveCalculator project

Summary

Functional Programming with Kotlin and RxKotlin

Functional Programming with Kotlin and RxKotlin

Introducing functional programming

Fundamentals of functional programming

Applying functional programming to the ReactiveCalculator class

Coroutines

Functional programming – monads

Summary

Observables, Observers, and Subjects

Observables, Observers, and Subjects

Observables

Other Observable factory methods

Hot and Cold Observables

Varieties of Subject

Summary

Introduction to Backpressure and Flowables

Introduction to Backpressure and Flowables

Understanding backpressure

Flowable

When to use Flowables and Observables

Flowable and Subscriber

Creating Flowable from scratch

Creating Flowable from Observable

BackpressureStrategy.MISSING and onBackpressureXXX()

Generating Flowable with backpressure at source

ConnectableFlowable

Processor

Learning Buffer, Throttle, and Window operators

Summary

Asynchronous Data Operators and Transformations

Asynchronous Data Operators and Transformations

Operator

The filtering/suppressing operators

The transforming operators

Reducing operators

The error handling operators

The utility operators

Summary

More on Operators and Error Handling

More on Operators and Error Handling

Combining producers (Observable/Flowable)

Grouping

flatMap, concatMap – In details

Understanding switchMap operator

Skipping and taking emissions

The error handling operators

onErrorReturn – return a default value on error

The onErrorResumeNext operator

An HTTP example

Summary

Concurrency and Parallel Processing in RxKotlin with Schedulers

Concurrency and Parallel Processing in RxKotlin with Schedulers

Introduction to concurrency

Parallel execution versus concurrency

What is a scheduler?

How to use schedulers – subscribeOn and observeOn operators

Summary

Testing RxKotlin Applications

Testing RxKotlin Applications

Introduction to unit testing and its importance

Writing JUnit tests in Kotlin

Testing in RxKotlin

Blocking subscribers

Blocking operators

Introducing TestObserver and TestSubscriber

Understanding TestScheduler

Summary

Resource Management and Extending RxKotlin

Resource Management and Extending RxKotlin

Resource management

Creating your own operators

Composing operators with transformer

Summary

Introduction to Web Programming with Spring for Kotlin Developers

Introduction to Web Programming with Spring for Kotlin Developers

Spring, history, and origin of Spring

Dependency injection and IoC

Spring – AOP

Introduction to Spring Boot

Creating a Rest API with Spring Boot

Summary

REST APIs with Spring JPA and Hibernate

REST APIs with Spring JPA and Hibernate

REST API with Spring Boot, Hibernate, and JPA

Reactive programming with Reactor

Summary

Reactive Kotlin and Android

Reactive Kotlin and Android

Setting up Kotlin in Android Studio

Getting started with ToDoApp on Android

Retrofit 2 for API calls

RxKotlin with Retrofit

Making Android events reactive

Kotlin extensions

Summary

Observables

As we discussed earlier, in reactive programming, Observable has an underlying computation that produces values that can be consumed by a consumer (Observer). The most important thing here is that the consumer (Observer) doesn't pull values here; rather, Observable pushes the value to the consumer. So, we may say, an Observable is a push-based, composable iterator that emits its items through a series of operators to the final Observer, which finally consumes the items. Let's now break things sequentially to understand it better:

Observer subscribes to Observable
Observable starts emitting items that it has in it
Observer reacts to whatever item Observable emits

So, let's delve into how an Observable works through its events/methods, namely, onNext, onComplete, and onError.

How Observable works

As we stated earlier, an Observable has three most important events/methods; let's discuss them one by one:

onNext: Observable passes all items one by one to this method.
onComplete: When all...

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