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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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 S. Khot S. Khot
Author Profile Icon S. Khot
S. Khot
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Table of Contents (19) Chapters Close

Scala Functional Programming Patterns
Credits
About the Author
Aknowledgement
About the Reviewers
www.PacktPub.com
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

Two forms of recursion


In the previous sections, we saw the tail recursive code to reverse a list. Take a look at this form:

object ReverseAList1 extends App {
 def reverseList(list: List[Int]): List[Int] = list match {
 case head :: tail => reverseList(tail) :+ head
 case Nil => Nil
 }
 val l = (1 to 20000).toList
 println(reverseList(l))
}

I know. This form is not tail recursive. Hence, this form will not benefit from the tail call optimization. Try to put the @tailrec annotation on the reverseList method. You will get a compilation error.

This form is still useful though. There are times when we do not want all the list elements. We just want to look at the first few elements of the result. We want to make the recursive call evaluation deferred. Call is not computed upfront. Instead, it is only evaluated when needed. We are talking of delayed evaluation in this case. Scala's Streams implements lazy lists where elements are only evaluated when they are needed. We will look in detail...

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