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Home > Programming > Functional Programming > Learning Functional Programming in Go
Learning Functional Programming in Go
Learning Functional Programming in Go

Learning Functional Programming in Go: Change the way you approach your applications using functional programming in Go

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Learning Functional Programming in Go

Manipulating Collections

Handling lists of items is a common occurrence in life as well as in programming languages. When a list has associated functions that help us manipulate the items in the list, we often call that object a collection.

In this chapter, we will see how high-order functions can be used to greatly simplify the task of manipulating collections. We'll see how we can code using functional programming techniques and open source functional packages to create elegant solutions that are not only insightful, but also performant in today's distributed processing environments.

Our goal in this chapter is to:

  • Iterate through a collection
  • Learn about intermediate and terminal functors
  • Use predicates to filter items in a collection
  • Test using a Mocha-like BDD library
  • Focus on Map functions
  • Grasp the breadth of the collection-manipulating functions in...

Iterating through a collection

In order to implement a collection, we must provide a way to access each element in the collection, which can be accomplished using the int index value shown in the following code. We will implement a first in, first out (FIFO) order queue. We will provide a way to store the elements using a slice data structure. Lastly, we will implement a Next() method to provide a way to traverse the elements in the collection.

In the following code, we define an interface for the Iterator object. It has one method, Next(), which will return the next element in the collection and a Boolean flag to indicate whether it's OK to continue iterating:

type CarIterator interface {
     Next() (value string, ok bool)
}
const INVALID_INT_VAL = -1
const INVALID_STRING_VAL = ""

Next, we define a collection object that has two properties: an int index used to access...

Piping Bash commands

Executing a composition or chain of functions is very much like executing a series of Bash commands, where the output from one command is piped into the next command. For example, we might cat an input a file that contains a list of timestamps and IP addresses in an awk command. The awk command removes all but the seventh column. Next, we sort the list in descending order, and finally, we group that data by unique IP addresses.

Consider the following Bash command:

$ cat ips.log | awk '{print $7}' | sort | uniq -c

Let's give this command the following input:

Sun Feb 12 20:27:32 EST 2017 74.125.196.101
Sun Feb 12 20:27:33 EST 2017 98.139.183.24
Sun Feb 12 20:27:34 EST 2017 151.101.0.73
Sun Feb 12 20:27:35 EST 2017 98.139.183.24
Sun Feb 12 20:27:36 EST 2017 151.101.0.73
>Sun Feb 12 20:27:37 EST 2017 74.125.196.101
Sun Feb 12 20:27:38 EST...

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.

Functors: A functor is a collection of X variables that can apply a function, f, over itself to create a collection of Y,...

Predicates

We can use predicates to perform operations on input data. Predicates can be used to implement many of the functions that we apply to collections to transform input data into the result collection or value.

The predicate function is a function that takes one item as input and returns either true or false, based on whether the item satisfies some condition. They are often used conditionally to determine whether to apply certain operations in the execution chain.

Let's create some predicate functions that we can use to manipulate a collection of cars.

The All() function returns true only if all the values in the collection satisfy the predicate condition:

package predicate

func All(vals []string, predicate func(string) bool) bool {
       for _, val := range vals {
              if !predicate(val) {
                     return false
         ...

Map and filter

The next code example demonstrates the use of a few standard intermediate functions: map and filter.

The code in this example can be copy/pasted into The Go playground, which is a service that takes your Go program, compiles, links, and runs your program with the latest version of Go inside a sandbox and then returns the output to the screen. You can find it at https://play.golang.org/.

Executable commands must always use package main. We can separate each import statement on a separate line for readability.

External packages can be referenced using their remote GitHub repository path. We can preface long package names with a shorter alias. The go_utils package can now be referenced with the u letter. Note that if we aliased a package name with _, its exported functions can be referenced directly in our Go code without indicating which package it...

Iterating through a collection

In order to implement a collection, we must provide a way to access each element in the collection, which can be accomplished using the int index value shown in the following code. We will implement a first in, first out (FIFO) order queue. We will provide a way to store the elements using a slice data structure. Lastly, we will implement a Next() method to provide a way to traverse the elements in the collection.

In the following code, we define an interface for the Iterator object. It has one method, Next(), which will return the next element in the collection and a Boolean flag to indicate whether it's OK to continue iterating:

type CarIterator interface {
     Next() (value string, ok bool)
}
const INVALID_INT_VAL = -1
const INVALID_STRING_VAL = ""

Next, we define a collection object that has two properties: an int index used to access the current element and a slice of strings, that is, the actual data in the collection:

type Collection struct {
       index...

Piping Bash commands

Executing a composition or chain of functions is very much like executing a series of Bash commands, where the output from one command is piped into the next command. For example, we might cat an input a file that contains a list of timestamps and IP addresses in an awk command. The awk command removes all but the seventh column. Next, we sort the list in descending order, and finally, we group that data by unique IP addresses.

Consider the following Bash command:

$ cat ips.log | awk '{print $7}' | sort | uniq -c

Let's give this command the following input:

Sun Feb 12 20:27:32 EST 2017 74.125.196.101
Sun Feb 12 20:27:33 EST 2017 98.139.183.24
Sun Feb 12 20:27:34 EST 2017 151.101.0.73
Sun Feb 12 20:27:35 EST 2017 98.139.183.24
Sun Feb 12 20:27:36 EST 2017 151.101.0.73
>Sun Feb 12 20:27:37 EST 2017 74.125.196.101
Sun Feb 12 20:27:38 EST 2017 98.139.183.24
Sun Feb 12 20:27:39 EST 2017 151.101.0.73
Sun Feb 12 20:27:40 EST 2017 98.139.183.24
Sun Feb 12 20:27:41 EST 2017 151...

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...

Predicates

We can use predicates to perform operations on input data. Predicates can be used to implement many of the functions that we apply to collections to transform input data into the result collection or value.

Note

Thepredicate function is a function that takes one item as input and returns either true or false, based on whether the item satisfies some condition. They are often used conditionally to determine whether to apply certain operations in the execution chain.

Let's create some predicate functions that we can use to manipulate a collection of cars.

The All() function returns true only if all the values in the collection satisfy the predicate condition:

package predicate

func All(vals []string, predicate func(string) bool) bool {
for _, val := range vals {
if !predicate(val) {
return false
              }
       }
return true
}

The Any() function returns true as long as any one of the values in the collection satisfies the predicate condition:

funcAny(vs []string, predicate func...

Map and filter

The next code example demonstrates the use of a few standard intermediate functions: map and filter.

Note

The code in this example can be copy/pasted into The Go playground, which is a service that takes your Go program, compiles, links, and runs your program with the latest version of Go inside a sandbox and then returns the output to the screen. You can find it at https://play.golang.org/.

Executable commands must always use package main. We can separate each import statement on a separate line for readability.

External packages can be referenced using their remote GitHub repository path. We can preface long package names with a shorter alias. The go_utils package can now be referenced with the u letter. Note that if we aliased a package name with _, its exported functions can be referenced directly in our Go code without indicating which package it came from:

package main
import (
   "fmt"
   "log"
   "strings"
   "errors"
   u "github.com/go-goodies/go_utils"
)

Note

iota: A Go...

Contains

Let's consider another common collection operation: contains.

In Go, lists of things are often stored in a slice. Wouldn't it be nice if Go provided a contains method to tell us whether the item we are looking for is contained in the slice? Since there is no generic contains method for working with lists of items in Go, let's implement one to iterate over a collection of car objects.

Iterating over a collection of cars

First, let's create a Car struct that we can use to define the Cars collection as a slice of Car. Later, we'll create a Contains() method to try out on our collection:

package main
type Car struct {
     Make string
     Model string
}
type Cars []*Car

Here's our Contains() implementation. Contains() is a method for Cars. It takes a modelName string, for example, Highlander, and returns true if it was found in the slice of Cars:

func (cars Cars) Contains(modelName string) bool {
     for _, a := range cars {
            if a.Model == modelName {
                   return...

If Go had generics

If Go had generics, we could have written a function signature like the following to replace strings with runes, and we would not have to rewrite the inner logic:

func Map(f func(v <string>) <bool>, vs [] <string>) []<bool>

However, Go does not have generics, so we can use empty interfaces and reflection to achieve the same result.

Map function

Let's create a Map function to transform the contents of a Collection.

First, let's define Object to be the empty interface type and create a Collection type to be a slice of objects:

package main
import "fmt"
type Object interface{}
type Collection []Object
func NewCollection(size int) Collection {
     return make(Collection, size)
}

The NewCollection function creates a new instance of the collection with the given size:

type Callback func(current, currentKey, src Object) Object

The Callback type is a first-class function type that returns the calculated result:

func Map(c Collection, cb Callback) Collection {
...
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Key benefits

  • Write concise and maintainable code with streams and high-order functions
  • Understand the benefits of currying your Golang functions
  • Learn the most effective design patterns for functional programming and learn when to apply each of them
  • Build distributed MapReduce solutions using Go

Description

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.

Who is this book for?

This book is for Golang developers comfortable with OOP and interested in learning how to apply the functional paradigm to create robust and testable apps. Prior programming experience with Go would be helpful, but not mandatory.

What you will learn

  • Learn how to compose reliable applications using high-order functions
  • Explore techniques to eliminate side-effects using FP techniques such as currying
  • Use first-class functions to implement pure functions
  • Understand how to implement a lambda expression in Go
  • Compose a working application using the decorator pattern
  • Create faster programs using lazy evaluation
  • Use Go concurrency constructs to compose a functionality pipeline
  • Understand category theory and what it has to do with FP
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Publication date : Nov 24, 2017
Length: 670 pages
Edition : 1st
Language : English
ISBN-13 : 9781787281394
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Category :
Programming
Languages :
Go
Concepts :
Functional Programming

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Length: 670 pages
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Language : English
ISBN-13 : 9781787281394
Vendor :
Google
Category :
Programming
Languages :
Go
Concepts :
Functional Programming

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Table of Contents

12 Chapters
Pure Functional Programming in Go Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
Using High-Order Functions
Characteristics of FP
Sample HOF application
Summary
SOLID Design in Go Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
Adding Functionality with Decoration
Interface composition
Decorator pattern
A decorator implementation
Summary
Applying FP at the Architectural Level Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
Functional Parameters
Refactoring long parameter lists
Functional parameters
Contexts
Summary
Increasing Performance Using Pipelining Chevron down icon Chevron up icon
Increasing Performance Using Pipelining
Introducing the pipeline pattern
Example implementations
Summary
Functors, Monoids, and Generics Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
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 Chevron down icon Chevron up icon
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

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l3x Nov 30, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
An author providing the first comment?Yes. It's "unconventional" but so is this book.This book tackles the unconventional topic of using functional programming (FP) with Go.I won't steal the thunder of reviewers with details, but I would like to share one thing...---A reviewer just asked me: "Curious, what was your path for learning about functional programming?"My response: A lot of google searches. Reading a lot of mathematics thesis papers. Watching a lot of videos. There was no one good source to learn about category theory especially for programmers. I learned more about category theory from studying Philip Wadler. (He actually is actually quite approachable).---Thank you, Dr. Wadler and all the mathematicians in the chain of discoveries that have shared their wisdom. Thank you, everyone that has written about FP and software design. If what you said is valuable, then you'll likely find it in some form in this book.I hope that my research efforts, discoveries, implementations, and writing style will benefit all readers.FP is pure. Go is simple.Read my book. Take this journey with me and judge for yourself how powerful FP + Go can be.Cheers!Lex
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Akram Ahmad Aug 22, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
- I am simply stunned by the high quality of "Learning Functional Programming in Go" by Lex Sheehan. Take this from someone who—and readers of my popular blog "Programming Digressions" are aware of this—knows a thing or two about Functional Programming (FP). This amazing book could not have come to my attention at a better time: I've dived deep into using the Go programming language this year that is 2018...- If you think about it, in the end, everything is related, simple, and well-designed. The biggest problem, IMHO, especially with FP, is that the smart guys that originally saw how it works, seem to have the hardest time making it easy to understand. But that's not a problem (in the least, whatsoever) with "Learning Functional Programming in Go": This book somehow manages to capture tough ideas (think "essential complexity") and strips them of their complexity. And that's a big deal, if you ask me.- With a nod to the remarkable observation that "A language that doesn’t affect the way you think about programming, is not worth knowing" (by Alan Perlis, the very first recipient of the Turing Award), I am especially pleased to have this book by Lex Sheehan ("Learning Functional Programming in Go") at my side.- Among other things, working intensively with Go has forced me to rethink what it means to leverage a programming paradigm in the service of creating great software that's designed to unfold, to emerge—so to say—and to delight customers. Don't miss this book!
Amazon Verified review Amazon
William Favorite Dec 16, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I am not that far in, but I like the book. Let's get that out of the way.My issues are with the kindle delivery mechanism. So this means that any negativity about the product *delivery* falls on the shoulders of the author. The publisher is like the absentee landlord. So I bump the stars for the author, but good luck with buying it from Kindle.It seems to be formatted differently (scrolls and not page flip) which makes me think this is the reason I can't read it like other IT books I have bought in this manner.I like the "paper edition 'limitations'" better: - Physical possession is the single requirement for access. - No other special 'limitations'.
Amazon Verified review Amazon
J. Kayser Sep 02, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I don't have a background in functional program, so this is an important book for me.If you don't know Go, learn Go from "The Go Programming Language" by Alan A. A. Donovan and Brian W. Kernighan. This is the Golang equivalent of the K&R C book.Then, read this book ("Learning Functional Programming in Go" by Lex Sheehan), Especially valuable for programmers who don't know functional programming. I learned a ton just working through the first example (memoizing a fibonacci function). It helped cement my understanding of first class functions.Thank you Lex for taking the time and effort to write the book. Brilliant job.
Amazon Verified review Amazon
Donam Kim Dec 21, 2017
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
I will postpone my review until I finish it.
Amazon Verified review Amazon

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About the author

Profile icon Sheehan
Sheehan
Matthew Sheehan is the founder and principal of WebMapSolutions (http://www.webmapsolutions.com/). He has over 20 years of experience working with both Esri and open source GIS technologies. Much of his current focus is on helping to expand the understanding and use of GIS. Using web technology, he is working with his technical team to build flexible ArcGIS solutions that can be integrated with existing enterprise systems. Disconnected use of GIS in the browser is a key part of this work. Matthew has a bachelor's degree in geography from University of London and a master's degree in Applied GIS from the University of Utah.
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Disclaimer:
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