Monads, Type Classes, and Generics | Learning Functional Programming in Go

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Learning Functional Programming in Go

By : Lex Sheehan

4.1 (8)

Learning Functional Programming in Go

4.1 (8)

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.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

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

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

Using High-Order Functions

Using High-Order Functions

Characteristics of FP

Sample HOF application

Summary

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

Adding Functionality with Decoration

Adding Functionality with Decoration

Interface composition

Decorator pattern

A decorator implementation

Summary

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

Functional Parameters

Functional Parameters

Refactoring long parameter lists

Functional parameters

Contexts

Summary

Increasing Performance Using Pipelining

Increasing Performance Using Pipelining

Introducing the pipeline pattern

Example implementations

Summary

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

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

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

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

Y-Combinator re-examined

Let’s look at another Y-Combinator example in Go to improve our grasp of the topic. Remember the Fibonacci function in Chapter 1, Pure Functional Programming in Go? It looked like this:

func fib(x int) int {
if x == 0 {
return 0
} else if x <= 2 {
return 1
} else {
return fib(x-2) + fib(x-1)
    }
}

If it passes a 0, 1, or 2, it simply returns a value (0 or 1). Otherwise, it will call itself (recursion) with two functions that look like this--fib(x-2) + fib(x-1). Since values are continually being decremented by two or one, processing will eventually complete, at which time the accumulated values will be summed up.

The following diagram illustrates this recursive processing. The orange and red boxes highlight functions that only need to be executed once. Referential integrity allows us to store the value of those functions. Subsequent execution only needs to look up the stored value, rather than re-execute the function:

We define three function types in main.go, as...

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