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Learning Functional Data Structures and Algorithms
Learning Functional Data Structures and Algorithms

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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Learning Functional Data Structures and Algorithms

Chapter 1.  Why Functional Programming?

What is functional programming (FP)? Why is it talked about so much?

A programming paradigm is a style of programming. FP is a programming paradigm characterized by the absence of side effects.

In FP, functions are the primary means of structuring code. The FP paradigm advocates using pure functions and stresses on immutable data structures. So we don't mutate variables, but pass a state to function parameters. Functional languages give us lazy evaluation and use recursion instead of explicit loops. Functions are first-class citizens like numbers or strings. We pass functions as argument values, just like a numeric or string argument. This ability to pass functions as arguments allows us to compose behavior, that is, cobble together something entirely new from existing functions.

In this chapter, we will take a whirlwind tour of functional programming. We will look at bits of code and images to understand the concepts. This will also lay a nice foundation for the rest of the book. We will use the functional paradigm and see how it changes the way we think about data structures and algorithms.

This chapter starts with a look at the concept of abstraction. We will see why abstractions are important in programming. FP is a declarative style of programming, similar to Structured Query Language (SQL). Because it is declarative, we use it to tell what we want the computer to do, rather how it should do it. We will also see how this style helps us stay away from writing common, repetitive boilerplate code.

Passing functions as arguments to other, higher order functions is the central idea in FP; we look at this next. We will also see how to stay away from null checks. Controlled state change allows us to better reason our code. Being immutable is the key for creating code that would be easier to reason about.

Next, we will see how recursion helps us realize looping without mutating any variables. We will wrap up the chapter with a look at lazy evaluation, copy-on-write, and functional composition.

The imperative way

We keep contrasting FP with the imperative style of programming. What do we mean by imperative style, though?

The imperative programming style is embodied by a sequence of commands modifying a program's state. A simple example of this is a for loop. Consider the following pseudo code snippet to print all the elements of an array:

  x = [1,2,3,4...] // an array, x.size tells the number of array elements  
  for( int i = 0; i < x.size; ++i ) { 
         println(x[i]) 
      } 

Here is a pictorial rendering of the concepts:

The imperative way

As the figure shows, the for loop establishes an initial state by setting the variable i to 0. The variable is incremented every time the loop is repeated; this is what we mean by the state being modified. We keep reading and modifying the state, that is, the loop variable, until there are no elements left in the array.

FP advocates staying away from any state modification. It gives us tools so we don't worry about how to loop over a collection; instead, we focus on what we need to do with each element of the collection.

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Key benefits

  • Moving from object-oriented programming to functional programming? This book will help you get started with functional programming.
  • Easy-to-understand explanations of practical topics will help you get started with functional data structures.
  • Illustrative diagrams to explain the algorithms in detail.
  • Get hands-on practice of Scala to get the most out of functional programming.

Description

Functional data structures have the power to improve the codebase of an application and improve efficiency. With the advent of functional programming and with powerful functional languages such as Scala, Clojure and Elixir becoming part of important enterprise applications, functional data structures have gained an important place in the developer toolkit. Immutability is a cornerstone of functional programming. Immutable and persistent data structures are thread safe by definition and hence very appealing for writing robust concurrent programs. How do we express traditional algorithms in functional setting? Won’t we end up copying too much? Do we trade performance for versioned data structures? This book attempts to answer these questions by looking at functional implementations of traditional algorithms. It begins with a refresher and consolidation of what functional programming is all about. Next, you’ll get to know about Lists, the work horse data type for most functional languages. We show what structural sharing means and how it helps to make immutable data structures efficient and practical. Scala is the primary implementation languages for most of the examples. At times, we also present Clojure snippets to illustrate the underlying fundamental theme. While writing code, we use ADTs (abstract data types). Stacks, Queues, Trees and Graphs are all familiar ADTs. You will see how these ADTs are implemented in a functional setting. We look at implementation techniques like amortization and lazy evaluation to ensure efficiency. By the end of the book, you will be able to write efficient functional data structures and algorithms for your applications.

Who is this book for?

This book is for those who have some experience in functional programming languages. The data structures in this book are primarily written in Scala, however implementing the algorithms in other functional languages should be straight forward.

What you will learn

  • Learn to think in the functional paradigm
  • Understand common data structures and the associated algorithms, as well as the context in which they are commonly used
  • Take a look at the runtime and space complexities with the O notation
  • See how ADTs are implemented in a functional setting
  • Explore the basic theme of immutability and persistent data structures
  • Find out how the internal algorithms are redesigned to exploit structural sharing, so that the persistent data structures perform well, avoiding needless copying.
  • Get to know functional features like lazy evaluation and recursion used to implement efficient algorithms
  • Gain Scala best practices and idioms

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Publication date : Feb 23, 2017
Length: 318 pages
Edition : 1st
Language : English
ISBN-13 : 9781785885884
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Publication date : Feb 23, 2017
Length: 318 pages
Edition : 1st
Language : English
ISBN-13 : 9781785885884
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Table of Contents

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

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(2 Ratings)
5 star 100%
4 star 0%
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1 star 0%
mloves2travel Jul 09, 2017
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is by far the best Packt publishing book I've ever read. This is comparable to the quality of a Manning Press book. I highly recommend this book and it's especially useful if you are preparing for technical interviews.
Amazon Verified review Amazon
Bookreader Apr 02, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is not a perfect book, but it's really good for being a Packt book. It's a nicer read than all other functional programming books I have. I've never written this about a book before - but reading this one actually makes me happy. It's simply a fun read! Not full of jokes, but fun in the way that every page makes me really curious about what's in the next page. And every chapter makes me curious about what's in the next chapter. I usually only review bad books, to warn others, but I think this one deserves a good review because it stands out so strongly among the competition when it comes to Packt books. Another reviewer said that it's more like a Manning book, but I disagree. I like this one more than I like the Manning books I've read. There are a few errors in the book (not many) and at some points the explanations could be better / clearer. But if you stop and think a bit you will probably manage fine without a perfect explanation. Everything is in there to be able to figure the missing parts out yourself (contrary to the Functional Programming in Scala book from Manning, to take an example of a book with way too many missing explanations).
Amazon Verified review Amazon
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