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Learning Functional Programming in Go

You're reading from   Learning Functional Programming in Go Change the way you approach your applications using functional programming in Go

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787281394
Length 670 pages
Edition 1st Edition
Languages
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Author (1):
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 Sheehan Sheehan
Author Profile Icon Sheehan
Sheehan
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Table of Contents (21) Chapters Close

Title Page
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Pure Functional Programming in Go FREE CHAPTER 2. Manipulating Collections 3. Using High-Order Functions 4. SOLID Design in Go 5. Adding Functionality with Decoration 6. Applying FP at the Architectural Level 7. Functional Parameters 8. Increasing Performance Using Pipelining 9. Functors, Monoids, and Generics 10. Monads, Type Classes, and Generics 11. Category Theory That Applies 12. Miscellaneous Information and How-Tos Index

Understanding functors


A functor is a structure-preserving transformation between categories. In other words, a functor is a mappable type. Let's see what that means with an example.

An imperative versus pure FP example

Suppose we start with a slice of ints, ints := []int{1,2,3}.

In imperative programming, we write all the scaffold code to implement exactly how to process this slice of ints. In pure FP, however, we tell our functor what we want the loop to do:

Here's the output:

imperative loop: [2 3 4]
fp map: [2 3 4]

Let's see how this works.

What did that Map function do for us?  

The Map function abstracted the loop. We don't have to bother writing the same old range/for looping code. We simply pass in our original ints list and tell our functor to map that slice into a slice where each element is one greater than it was before. This is a lot like SQL, where we declare what data we want and let the database engine worry about how to get the data.

What possible benefits can this afford us?

Do we...

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