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Learning Functional Programming in Go

You're reading from   Learning Functional Programming in Go Change the way you approach your applications using functional programming in Go

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787281394
Length 670 pages
Edition 1st Edition
Languages
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Author (1):
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Lex Sheehan Lex Sheehan
Author Profile Icon Lex Sheehan
Lex Sheehan
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Table of Contents (13) Chapters Close

Preface 1. Pure Functional Programming in Go 2. Manipulating Collections FREE CHAPTER 3. Using High-Order Functions 4. SOLID Design in Go 5. Adding Functionality with Decoration 6. Applying FP at the Architectural Level 7. Functional Parameters 8. Increasing Performance Using Pipelining 9. Functors, Monoids, and Generics 10. Monads, Type Classes, and Generics 11. Category Theory That Applies 12. Miscellaneous Information and How-Tos

Pure functions

"Insanity is doing the same thing over and over again and expecting different results."
- Albert Einstein

We can use this insanity principle to our advantage with pure functions.

Assigning values to variables during an imperative function's execution may result in the modification of a variable in the environment in which it has run. If we run the same imperative function again, using the same input, the result may differ.

Given the results of an imperative function and given the same input, different results may be returned each time it is run. Is that not insanity?

Pure functions:

  • Treat functions as first-class citizens
  • Always return the same result given the same input(s)
  • Have no side effects in the environment in which they run
  • Do not allow an external state to affect their results
  • Do not allow variable values to change over time

Two characteristics of a pure function include referential transparency and idempotence:

  • Referential transparency: This is where a function call can be replaced with its corresponding value without changing the program's behavior
  • Idempotence: This is where a function call can be called repeatedly and produce the same result each time

Referentially transparent programs are more easily optimized. Let's see whether we can perform optimizations using a caching technique and Go's concurrency features.

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