Book Image

Mastering Reactive JavaScript

By : Erich de Souza Oliveira
Book Image

Mastering Reactive JavaScript

By: Erich de Souza Oliveira

Overview of this book

If you’re struggling to handle a large amount of data and don’t know how to improve your code readability, then reactive programming is the right solution for you. It lets you describe how your code behaves when changes happen and makes it easier to deal with real-time data. This book will teach you what reactive programming is, and how you can use it to write better applications. The book starts with the basics of reactive programming, what Reactive Extensions is, and how can you use it in JavaScript along with some reactive code using Bacon. Next, you’ll discover what an Observable and an Observer are and when to use them.You'll also find out how you can query data through operators, and how to use schedulers to react to changes. Moving on, you’ll explore the RxJs API, be introduced to the problem of data traffic (backpressure), and see how you can mitigate it. You’ll also learn about other important operators that can help improve your code readability, and you’ll see how to use transducers to compose operators. At the end of the book, you’ll get hands-on experience of using RxJs, and will create a real-time web chat using RxJs on the client and server, providing you with the complete package to master RxJs.
Table of Contents (11 chapters)

Going beyond the basics

RxJS supplies a lot more than just operators to do simple transformation in your data, we learned some more complex usages for it and we will review the most important of it.

Dealing with backpressure

Backpressure happens every time you receive data faster than you are able to process for a given time.

Before even starting to code your solution for back pressure you must decide if you are willing to spend memory or lose data.

When you can lose data you can use a lossy strategy; the advantage of this strategy is it has a low consumption of memory, and lets you mitigate the problem using constant memory. The lossy operators that we learned are as follows:

  • throttle()
  • sample()
  • debounce()
  • pausable()

If you cannot lose data, you can use memory to store data while processing it; the strategy you will use to deal with backpressure is the loss-less strategy. We learned the following operators to loss-less operators to deal with backpressure:

  • bufferWithCount()
  • bufferWithTime()
  • bufferWithTimeOrCount...