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Learning Functional Programming in Go

Learning Functional Programming in Go

By : Sheehan
4.1 (8)
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Learning Functional Programming in Go

Learning Functional Programming in Go

4.1 (8)
By: Sheehan

Overview of this book

Lex Sheehan begins slowly, using easy-to-understand illustrations and working Go code to teach core functional programming (FP) principles such as referential transparency, laziness, recursion, currying, and chaining continuations. This book is a tutorial for programmers looking to learn FP and apply it to write better code. Lex guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. The book is divided into four modules. The first module explains the functional style of programming: pure functional programming, manipulating collections, and using higher-order functions. In the second module, you will learn design patterns that you can use to build FP-style applications. In the next module, you will learn FP techniques that you can use to improve your API signatures, increase performance, and build better cloud-native applications. The last module covers Category Theory, Functors, Monoids, Monads, Type classes and Generics. By the end of the book, you will be adept at building applications the FP way.
Table of Contents (13 chapters)
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Monoids


Monoids are the most basic way to combine any values. A monoid is algebra that is closed under an associative binary operation and has an identity element.

We can think of a monoid as a design pattern that allows us to quickly reduce (or fold) on a collection of a single type in a parallel way.

Monoid rules

A monoid is anything that satisfies the following rules:

  • Closure rule
  • Associativity rule
  • Identity rule

Let's discuss these rules in brief.

Closure rule

“If you combine two values of same type, you get another value of the same type.” 

Given two inputs of the same type, a monoid returns one value of the same type as the input.

Closure rule examples

1 + 2 = 3, and 3 is an integer.

1 + 2 + 3 also equals an integer.

1 + 2 + 3 + 4 also equals an integer.

Our binary operation has been extended into an operation that works on lists!

Closure axiom

If a, b ∈ S, then a + b ∈ S.

That says, if a and b are any two values in the set S of integers and if we apply the binary operation + to any two values, then...

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