Book Image

Learning Functional Programming in Go

By : Lex Sheehan
Book Image

Learning Functional Programming in Go

By: Lex 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 (21 chapters)
Title Page
Credits
About the Author
Acknowledgments
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Functors


Go has three predeclared/raw data types: bool, string, numeric (float, int64, and so on). Other data types in Go require type declarations, that is, they require we use the type keyword. Functions fall in the later category of data types along with array, struct, pointer, interface, slice, map, and channel types. In Go, functions are first-class data types, which means that can be passed around as parameters and returned as values. Functions that can take functions as arguments and return functions are called high-order functions.

We can write function factories--functions that return functions--and even function factory factories. We can also write functions that modify functions or create functions for specific purposes.

Note

Functors: A functor is a collection of X variables that can apply a function, f, over itself to create a collection of Y, that is, f (X) → Y. (To see what we're talking about here, take a quick look at the Fingers times 10 functor example in Chapter 9, Functors...