Learning Functional Data Structures and Algorithms
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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 LearnLearn to think in the functional paradigmUnderstand common data structures and the associated algorithms, as well as the context in which they are commonly usedTake a look at the runtime and space complexities with the O notationSee how ADTs are implemented in a functional settingExplore the basic theme of immutability and persistent data structuresFind 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 algorithmsGain Scala best practices and idiomsIn DetailFunctional 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.
Style and approachStep-by-step topics will help you get started with functional programming. Learn by doing with hands-on code snippets that give you practical experience of the subject.
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Atul S. Khot grew up in Marathwada, a region of the state of Maharashtra, India. A self-taught programmer, he started writing software in C and C++. A Linux aficionado and a command-line guy at heart, Atul has always been a polyglot programmer. Having extensively programmed in Java and dabbled in multiple languages, these days, he is increasingly getting hooked on Scala, Clojure, and Erlang. Atul is a frequent speaker at software conferences, and a past Dr. Dobb's product award judge. In his spare time, he loves to read classic British detective fiction. He is a foodie at heart and a pretty good cook. Atul someday dreams of working as a master chef, serving people with lip-smacking dishes. He was the author of Scala Functional Programming Patterns published by Packt Publishing in December 2015. The book looks at traditional object-oriented design patterns and shows how we could use Scala's functional features instead.
Raju Kumar Mishra is a consultant and corporate trainer for big data and programming. After completing his B.Tech from Indian Institute of Technology (ISM) Dhanbad, he worked for Tata Steel. His deep passion for mathematics, data science, and programming took him to Indian Institute of Science (IISc). After graduating from IISc in computational science, he worked for Oracle as a performance engineer and software developer. He is an Oracle-certified associate for Java 7. He is a Hortonworks-certified Apache Hadoop Java developer, and holds a Developer Certification for Apache Spark (O'Reilly School of Technology and Databriks), and Revolution R Enterprise-certified Specialist Certifications. Apart from this, he has also cleared Financial Risk Manager (FRM I) exam. His interest in mathematics helped him in clearing the CT3 (Actuarial Science) exam.
