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Reactive Patterns with RxJS for Angular

Reactive Patterns with RxJS for Angular

By : Lamis Chebbi
4.1 (16)
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Reactive Patterns with RxJS for Angular

Reactive Patterns with RxJS for Angular

4.1 (16)
By: Lamis Chebbi

Overview of this book

RxJS is a fast, reliable, and compact library for handling asynchronous and event-based programs. It is a first-class citizen in Angular and enables web developers to enhance application performance, code quality, and user experience, so using reactive patterns in your Angular web development projects can improve user interaction on your apps, which will significantly improve the ROI of your applications. This book is a step-by-step guide to learning everything about RxJS and reactivity. You'll begin by understanding the importance of the reactive paradigm and the new features of RxJS 7. Next, you'll discover various reactive patterns, based on real-world use cases, for managing your application’s data efficiently and implementing common features using the fewest lines of code. As you build a complete application progressively throughout the book, you'll learn how to handle your app data reactively and explore different patterns that enhance the user experience and code quality, while also improving the maintainability of Angular apps and the developer's productivity. Finally, you'll test your asynchronous streams and enhance the performance and quality of your applications by following best practices. By the end of this RxJS Angular book, you'll be able to develop Angular applications by implementing reactive patterns.
Table of Contents (19 chapters)
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1
Part 1 – Introduction
5
Part 2 – A Trip into Reactive Patterns
10
Part 3 – Multicasting Takes You to New Places
16
Part 4 – Final Touch

Understanding the anatomy of an Observable

Understanding the Observable anatomy is crucial in order to learn error handling patterns. Do you remember this marble diagram, explained in Chapter 1, The Power of the Reactive Paradigm?

Figure 5.1 – The marble diagram elements

Let's examine the preceding diagram. If we look closer at the stream's life cycle, we can figure out that a stream has two final statuses:

  • Completion status: When the stream has ended without errors and will not emit any further values. It is a SHUT DOWN.
  • Error status: When the stream has ended with an error and will not emit any further values after the error is thrown. It is also a SHUT DOWN.

Only one of those two states can occur, not both, and every stream can error out once. This is the Observable contract. You may be wondering at this point, how we can recover from an error then?

This is what we will be learning in the following sections.

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