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Scala Functional Programming Patterns

You're reading from   Scala Functional Programming Patterns Grok and perform effective functional programming in Scala

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Product type Paperback
Published in Dec 2015
Publisher
ISBN-13 9781783985845
Length 298 pages
Edition 1st Edition
Languages
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Author (1):
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Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Table of Contents (13) Chapters Close

Preface 1. Grokking the Functional Way FREE CHAPTER 2. Singletons, Factories, and Builders 3. Recursion and Chasing your Own Tail 4. Lazy Sequences – Being Lazy, Being Good 5. Taming Multiple Inheritance with Traits 6. Currying Favors with Your Code 7. Of Visitors and Chains of Responsibilities 8. Traversals – Mapping/Filtering/Folding/Reducing 9. Higher Order Functions 10. Actors and Message Passing 11. It's a Paradigm Shift Index

Monads


Let's say we have a function, X => List[Y]. This function is transformed to another function, List[X] => List[Y]. A higher order function that does this transformation is Monad.

Figure 9.2: Monad translation

Again, choosing the List container for ease of understanding, we go with the following commands:

object Monad extends App {
  def monad[X, Y](f: X => List[Y]): List[X] => List[Y] = {
      def fun : (List[X]) => List[Y] = (arg: List[X]) => arg match { // 1
        case Nil => Nil
        case x :: xs => f(x) ::: fun(xs) // 2
      }
      fun
    }
  def f1(n: Int) = (1 to n).toList // 3
  val f = monad(f1) // 4
  println(f(List(7,8,9)))  // 5 
}

The salient points of the preceding code are as follows:

  • We define a function, fun, that takes an argument, arg, of the type List[X].

  • We iterate each element, x, of the input list. We invoke f(x) and get List[Y]. We flatten each list by concatenating the resulting lists together with the ::: operator.

  • We have a function...

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