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Learning Functional Data Structures and Algorithms

You're reading from   Learning Functional Data Structures and Algorithms Learn functional data structures and algorithms for your applications and bring their benefits to your work now

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781785888731
Length 318 pages
Edition 1st Edition
Languages
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Authors (2):
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Raju Kumar Mishra Raju Kumar Mishra
Author Profile Icon Raju Kumar Mishra
Raju Kumar Mishra
Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Table of Contents (14) Chapters Close

Preface 1. Why Functional Programming? FREE CHAPTER 2. Building Blocks 3. Lists 4. Binary Trees 5. More List Algorithms 6. Graph Algorithms 7. Random Access Lists 8. Queues 9. Streams, Laziness, and Algorithms 10. Being Lazy - Queues and Deques 11. Red-Black Trees 12. Binomial Heaps 13. Sorting

List head and tail


Here is the simplest List method that gets the first element, that is, head of the list:

scala> def head[A](list: List[A]): A = list match { 
     |     case Nil => sys.error("tail of empty list") 
     |     case ::(x, _) => x 
     |   } 
head: [A](list: ch02.mylist.List[A])A 

We perform a pattern match on the list. The first clause case Nil => sys.error("tail of empty list") matches when the list is empty. An empty list will not have a first element so we raise an exception:

case ::(x, _) => x 

This clause matches when there are one or more elements in the list.

The following diagram shows how the pattern match works:

We usually write the second clause as follows:

case x :: _ => x 

This reads better. The expression  ::(x, _) can always be written in infix notation as x :: _. See http://danielwestheide.com/blog/2012/11/21/the-neophytes-guide-to-scala-part-1-extractors.html for more information. Here is the revised head...

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