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.

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Table of Contents (21 chapters)
Title Page
Title Page
Credits
Credits
About the Author
About the Author
Acknowledgments
Acknowledgments
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Customer Feedback
Customer Feedback
Preface
Preface
Free Chapter
1
Pure Functional Programming in Go
Pure Functional Programming in Go
Motivation for using FP
Getting the source code
Imperative versus declarative programming
Pure functions
Fibonacci sequence - a simple recursion and two performance improvements
The difference between an anonymous function and a closure
Testing FP using test-driven development
A journey from imperative programming to pure FP and enlightenment
Summary
2
Manipulating Collections
Manipulating Collections
Iterating through a collection
Piping Bash commands
Functors
Predicates
Map and filter
Contains
If Go had generics
Itertools
Functional  packages
Another time of reflection
The cure
Summary
3
Using High-Order Functions
Using High-Order Functions
Characteristics of FP
Sample HOF application
Summary
4
SOLID Design in Go
SOLID Design in Go
Why many Gophers eschew Java
Software design methodology
SOLID design principles
The big reveal
Viva La Duck
Summary
5
Adding Functionality with Decoration
Adding Functionality with Decoration
Interface composition
Decorator pattern
A decorator implementation
Summary
6
Applying FP at the Architectural Level
Applying FP at the Architectural Level
Application architectures
The role of systems engineering
Managing Complexity
FP influenced architectures
Domain Driven Design
Domain Driven Design
A cloud bucket application
FP and Micyoservices
Summary
7
Functional Parameters
Functional Parameters
Refactoring long parameter lists
Functional parameters
Contexts
Summary
8
Increasing Performance Using Pipelining
Increasing Performance Using Pipelining
Introducing the pipeline pattern
Example implementations
Summary
9
Functors, Monoids, and Generics
Functors, Monoids, and Generics
Understanding functors
Solve lack of generics with metaprogramming
Generics code generation tool
Generics implementation options
The shape of a functor
Composition operation
Functional composition in the context of a legal obligation
Build a 12-hour clock functor
The car functor
Monoids
Monoid examples
Summary
10
Monads, Type Classes, and Generics
Monads, Type Classes, and Generics
Mother Teresa Monad
Monadic workflow implementation
Y-Combinator
An alternative workflow option
Business use case scenarios
Y-Combinator re-examined
Type classes
Generics revisited
Summary
11
Category Theory That Applies
Category Theory That Applies
Our goal
Proof theory
The Curry Howard isomorphism
Historical Events in Functional Programming
Programming language categories
The Lambda Calculus
The importance of Type systems to FP
Domains, codomains, and morphisms
Set theory symbols
Category theory
Morphisms
Homomorphism
Composable concurrency
Graph Database Example
Using mathematics and category theory to gain understanding
Fun with Sums, Products, Exponents and Types
Big data, knowledge-driven development, and data visualization
Summary
12
Miscellaneous Information and How-Tos
Miscellaneous Information and How-Tos
How to build and run Go projects
Development workflow summary
A note about Go Dependency Management
A conversation - Java developer, idiomatic Go developer, FP developer
How to propose changes to Go
FP resources
Minggatu - Catalan number
Index
Index

Type classes

Type classes allow us to define behavior on types.

As discussed in Chapter 3, Using High-Order Functions, type classes add an additional layer to our type system.

We accomplish this by:

  1. Defining behavior using Go interfaces (parent type class)
  2. Declaring a new type (base type class) to wrap base types
  3. Implementing behavior on our new type classes

Let’s look at our Equals type class implementation.

Parent class definition:

//4-purely-functional/ch11-monads/05_typeclasss/src/typeclass/equals.go
package typeclass

import (
"strconv"
)
type Equals interface {
   Equals(Equals) bool
}

Equals is our parent type class. All base classes must implement the Equals method.

Base class definitions

We'll define two base types, Int and String.

Int base class

The Equals method of Int will check whether other types are equal, using whatever logic we deem appropriate:

type Int int

func (i Int) Equals(e Equals) bool {
   intVal := int(i)
switch x := e.(type) {
case Int:
return intVal == int(x)
case String:...
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