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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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Toc

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

No boilerplate

Boilerplate code consists sections of the same code written again and again. For example, writing loops is boilerplate, as is writing getters and setters for private class members.

As the preceding code shows, the loop is implicit:

scala> List(1, 2, 3, 4, 5) partition(_ % 2 == 0) 
res3: (List[Int], List[Int]) = (List(2, 4),List(1, 3, 5)) 

We just wish to separate the odd and even numbers. So we just specify the criteria via a function, an anonymous function in this case. This is shown in the following image:

No boilerplate

What is boilerplate? It is a for loop, for example. In the imperative world, we code the loop ourselves. We need to tell the system how to iterate over a data structure.

Isn't Scala code just to the point? We tell what we need and the loop is implied for us. No need to write a for loop, no need to invent a name for the loop variable, and so on. We just got rid of the boilerplate.

Here is a Clojure snippet that shows how to multiply each element of a vector by 2:

user=> (map * (repeat 2) [1 2 3 4 5]) 
(2 4 6 8 10) 

The map function hides the loop from us. Then (repeat 2) function call generates an infinite sequence.

So we are just saying this: for the input sequence [1 2 3 4 5], create another lazy sequence of 2's. Then use the map function to multiply these two sequences and output the result. The following figure depicts the flow:

No boilerplate

Compare this with an imperative language implementation. We would have needed a loop and a list to collect the result. Instead, we just say what needs to be done.

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Learning Functional Data Structures and Algorithms
Published in: Feb 2017
Publisher: Packt
ISBN-13: 9781785888731
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