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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

Laziness and deferred execution

To deal with excessive copying, we can resort to a feature called deferred processing, also known as, lazy collections. A collection is lazy when all of its elements are not realized at the time of creation. Instead, elements are computed on demand.

Let's write a program to generate numbers from 1 to 100. We wish to check which numbers are evenly divisible by 2, 3, 4, and 5.

Let's generate a lazy collection of the input numbers:

scala> val list = (1 to 100).toList.view 
list: scala.collection.SeqView[Int,List[Int]] = SeqView(...) 

We convert an existing Scala collection into a lazy one by calling the view function. Note that the list elements are not printed out, as these are not yet computed.

The following snippet shows a very simple predicate method that checks whether the number n is evenly divisible by d:

scala> def isDivisibleBy(d: Int)(n: Int) = { 
     |   println(s"Checking ${n} by ${d}") 
     |   n % d == 0 
     | } 
isDivisibleBy: (d: Int)(n: Int)Boolean 

We write a method isDivisibleBy in the curried form. We have written the isDivisibleBy as a series of functions, each function taking one argument. In our case, n is 2. We do this so we can partially apply functions to the divisor argument. This form helps us easily generate functions for divisors 2, 3, 4, and 5:

scala> val by2 = isDivisibleBy(2) _ 
by2: Int => Boolean = <function1> 
 
scala> val by3 = isDivisibleBy(3) _ 
by3: Int => Boolean = <function1> 
 
scala> val by4 = isDivisibleBy(4) _ 
by4: Int => Boolean = <function1> 
 
scala> val by5 = isDivisibleBy(5) _ 
by5: Int => Boolean = <function1> 

We can test the preceding functions by entering the code on the REPL, as shown here:

scala> by3(9) 
Checking 9 by 3 
res2: Boolean = true 
 
scala> by4(11) 
Checking 11 by 4 
res3: Boolean = false 

Now we write our checker:

scala> val result = list filter by2 filter by3 filter by4 filter by5 
result: scala.collection.SeqView[Int,List[Int]] = SeqViewFFFF(...) 
scala> result.force 
Checking 1 by 2 
Checking 2 by 2 
Checking 2 by 3 
Checking 3 by 2 
Checking 4 by 2 
... 
Checking 60 by 2 
Checking 60 by 3 
Checking 60 by 4 
Checking 60 by 5 
... 
res1: List[Int] = List(60) 

Note that when 2 is checked by 2 and okayed, it is checked by 3. All the checks happen at the same time and the copying is elided.

Note the force method; this is the opposite of the view method. The force method converts the collection back into a strict one. For a strict collection, all the elements are processed. Once the processing is done, a collection with just the number 60 is returned.

You have been reading a chapter from
Learning Functional Data Structures and Algorithms
Published in: Feb 2017
Publisher: Packt
ISBN-13: 9781785888731
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