Book Image

Mastering JavaScript Functional Programming - Second Edition

By : Federico Kereki
Book Image

Mastering JavaScript Functional Programming - Second Edition

By: Federico Kereki

Overview of this book

Functional programming is a paradigm for developing software with better performance. It helps you write concise and testable code. To help you take your programming skills to the next level, this comprehensive book will assist you in harnessing the capabilities of functional programming with JavaScript and writing highly maintainable and testable web and server apps using functional JavaScript. This second edition is updated and improved to cover features such as transducers, lenses, prisms and various other concepts to help you write efficient programs. By focusing on functional programming, you’ll not only start to write but also to test pure functions, and reduce side effects. The book also specifically allows you to discover techniques for simplifying code and applying recursion for loopless coding. Gradually, you’ll understand how to achieve immutability, implement design patterns, and work with data types for your application, before going on to learn functional reactive programming to handle complex events in your app. Finally, the book will take you through the design patterns that are relevant to functional programming. By the end of this book, you’ll have developed your JavaScript skills and have gained knowledge of the essential functional programming techniques to program effectively.
Table of Contents (17 chapters)
Technical Requirements


Now, let's consider a performance problem in JavaScript that happens when we're dealing with large arrays and applying several map/filter/reduce operations. If you start with an array and apply such operations (via chaining, as we saw earlier in this chapter), you get the desired result, but many intermediate arrays are created, processed, and discarded—and that causes delays. If you are dealing with short arrays, the extra time won't make an impact, but if you are processing larger arrays (as in a big data process, maybe in Node, where you're working with the results of a large database query), then you will have cause to look for some optimization. We'll do this by learning about a new tool for composing functions: transducing.

First, let's create some functions and data. We'll make do with a basically nonsensical example...