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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

Recursive streams


We looked at recursion earlier. Recursive forms are defined in terms of themselves. For example, folders can have subfolders, which, in turn, can have subfolders themselves. Another example is recursive methods calling themselves.

We can use a similar form to define recursive streams. To define recursive streams, consider the following case:

scala> lazy val r = Stream.cons(1, Stream.cons(2, Stream.empty)) 
r: Stream.Cons[Int] = <lazy> 
scala> (r take 4) foreach {x => println(x)} 
1
2

How is this useful? The second cons call can be recursive. (Note we don't need any var):

scala> def s(n: Int):Stream[Int]  = 
     |   Stream.cons(n, s(n+1))  // 1
s: (n: Int)Stream[Int] 
scala> lazy val q = s(0) 
q: Stream[Int] = <lazy> 

Here, we construct the lazy list by placing a recursive call to the method, s.

However, the following form is a succinct one:

scala> def succ(n: Int):Stream[Int] = n #:: succ(n+1) 
succ: (n: Int)Stream[Int] 
scala> lazy val r...
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