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Reactive Programming in Kotlin

Rivu Chakraborty 著

更新時間：2021-07-02 22:27:09

開會員，本書免費讀 >

ThisbookisforKotlindeveloperswhowouldliketobuildfault-tolerant,scalable,anddistributedsystems.AbasicknowledgeofKotlinisrequired,butnopriorknowledgeofreactiveprogramming.

目錄(198章)

倒序

封面
版權信息
Credits
About the Author
About the Reviewers
www.PacktPub.com
Why subscribe?
Customer Feedback
Dedication
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
A Short Introduction to Reactive Programming
What is reactive programming?
Reasons to adapt functional reactive programming
Reactive Manifesto
Reactive Streams standard specifications
Reactive Frameworks for Kotlin
Getting started with RxKotlin
Downloading and setting up RxKotlin
Comparing the pull mechanism with the RxJava push mechanism
The ReactiveEvenOdd program
The ReactiveCalculator project
Summary
Functional Programming with Kotlin and RxKotlin
Introducing functional programming
Fundamentals of functional programming
Lambda expressions
Pure function
High-order functions
Inline functions
Applying functional programming to the ReactiveCalculator class
Coroutines
Getting started with coroutines
Building sequences
The ReactiveCalculator class with coroutines
Functional programming – monads
Single monad
Summary
Observables Observers and Subjects
Observables
How Observable works
Understanding the Observable.create method
Understanding the Observable.from methods
Understanding the toObservable extension function
Understanding the Observable.just method
Other Observable factory methods
Subscribers - the Observer interface
Subscribing and disposing
Hot and Cold Observables
Cold Observables
Hot Observables
Introducing the ConnectableObservable object
Subjects
Varieties of Subject
Understanding AsyncSubject
Understanding PublishSubject
Understanding BehaviorSubject
Understanding ReplaySubject
Summary
Introduction to Backpressure and Flowables
Understanding backpressure
Flowable
When to use Flowables and Observables
When to use Flowables?
When to use Observables?
Flowable and Subscriber
Creating Flowable from scratch
Creating Flowable from Observable
BackpressureStrategy.MISSING and onBackpressureXXX()
Operator onBackpressureBuffer()
Operator onBackpressureDrop()
Operator onBackpressureLatest()
Generating Flowable with backpressure at source
ConnectableFlowable
Processor
Learning Buffer Throttle and Window operators
The buffer() operator
The window() operator
The throttle() operators
Summary
Asynchronous Data Operators and Transformations
Operator
The filtering/suppressing operators
The debounce operator
The distinct operators – distinct distinctUntilChanged
The elementAt operator
Filtering emissions - filter operator
The first and last operator
The ignoreElements operator
The transforming operators
The map operator
Casting emissions (cast operator)
The flatMap operator
The defaultIfEmpty operator
The switchIfEmpty operator
The startWith operator
Sorting emissions (sorted operator)
Accumulating data – scan operator
Reducing operators
Counting emissions (count operator)
Accumulating emissions – reduce operator
The collection operators
The error handling operators
The utility operators
Summary
More on Operators and Error Handling
Combining producers (Observable/Flowable)
The startWith operator
Zipping emissions – zip operator
The zipWith operator
The combineLatest operator
Merging Observables/Flowables – merge operator
Concatenating producers (Observable/Flowable)
Ambiguously combining producers
Grouping
flatMap concatMap – In details
When to use flatMap operator
When to use concatMap operator
Understanding switchMap operator
Skipping and taking emissions
Skipping emissions (skip skipLast skipUntil and skipWhile)
Take operators (take takeLast takeWhile and takeUntil)
The error handling operators
onErrorReturn – return a default value on error
The onErrorResumeNext operator
Retrying on error
An HTTP example
Summary
Concurrency and Parallel Processing in RxKotlin with Schedulers
Introduction to concurrency
Parallel execution versus concurrency
What is a scheduler?
Types of scheduler
Schedulers.io() - I/O bound scheduler
Schedulers.computation() - CPU bound schedulers
Schedulers.newThread()
Schedulers.single()
Schedulers.trampoline()
Schedulers.from
How to use schedulers – subscribeOn and observeOn operators
Changing thread on subscription – subscribeOn operator
Observing on a different thread – observeOn operator
Summary
Testing RxKotlin Applications
Introduction to unit testing and its importance
Why is unit testing so important?
Writing JUnit tests in Kotlin
Testing your code
Testing in RxKotlin
Blocking subscribers
Blocking operators
Getting the first emitted item – blockingFirst()
Getting the only item from single or maybe - blockingGet
Getting the last Item - blockingLast
Getting all emissions as iterable - blockingIterable operator
Looping through all emissions - blockingForEach
Introducing TestObserver and TestSubscriber
Understanding TestScheduler
Summary
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
Spring history and origin of Spring
The origin and history of Spring
Dependency injection and IoC
Spring Annotation configuration
Spring – AOP
Introduction to Spring Boot
Creating a Rest API with Spring Boot
Summary
REST APIs with Spring JPA and Hibernate
REST API with Spring Boot Hibernate and JPA
Reactive programming with Reactor
Add Reactor to your project
Understanding Flux and Mono
Summary
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
Introducing RxBinding in Android
Kotlin extensions
Summary 更新時間：2021-07-02 22:27:09

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Reactive Programming in Kotlin