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Reactive Patterns with RxJS and Angular Signals

You're reading from   Reactive Patterns with RxJS and Angular Signals Elevate your Angular 18 applications with RxJS Observables, subjects, operators, and Angular Signals

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835087701
Length 254 pages
Edition 2nd Edition
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Author (1):
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Lamis Chebbi Lamis Chebbi
Author Profile Icon Lamis Chebbi
Lamis Chebbi
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Table of Contents (21) Chapters Close

Preface 1. Part 1:An Introduction to the Reactive World
2. Chapter 1: Diving into the Reactive Paradigm FREE CHAPTER 3. Chapter 2: Walking through Our Application 4. Part 2: A Trip into Reactive Patterns
5. Chapter 3: Fetching Data as Streams 6. Chapter 4: Handling Errors Reactively 7. Chapter 5: Combining Streams 8. Chapter 6: Transforming Streams 9. Chapter 7: Sharing Data between Angular Components 10. Part 3: The Power of Angular Signals
11. Chapter 8: Mastering Reactivity with Angular Signals 12. Part 4: Multicasting Adventures
13. Chapter 9: Demystifying Multicasting 14. Chapter 10: Boosting Performance with Reactive Caching 15. Chapter 11: Performing Bulk Operations 16. Chapter 12: Processing Real-Time Updates 17. Part 5: Final Touches
18. Chapter 13: Testing RxJS Observables 19. Index 20. Other Books You May Enjoy

Combining Streams

So far, we have learned about the reactive pattern to fetch data as streams and have covered error-handling patterns. However, we have only explored the asynchronous data emitted from only one stream. What if we want to work with the asynchronous data emitted from different streams? Do you know how we can proceed?

Luckily, RxJS ships with one of the most powerful concepts: combining streams. Combining streams is the process of bringing together the emissions of multiple Observables in one stream. This allows you to explore multiple sources of asynchronous data as if they were a single stream. The main idea behind combining streams is manipulating asynchronous data in a more structured way.

This chapter revolves around a common use case, which is filtering data; we will resolve this by combining streams. We will start by explaining the filtering requirement, and then we will explore the imperative, classic pattern that can be used to implement this requirement...

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