This is the code repository for Functional Data Structures and Algorithms [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
Functional data structures have the power to improve the code base 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 a functional setting? Won’t we end up copying too much? Do we trade performance for versioned data structures? This course attempts to answer these questions by looking at functional implementations of traditional algorithms. It begins with a refresher and consolidates 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. Moving on, you will learn about binary trees, where we will be building complete trees, greedy algorithms, and back tracking.
- Learn to think in the functional paradigm
- Learn about the O notation
- Take a look at runtime and space complexities
- Explore the basic themes of immutability and persistent data structures
- Learn to drop and concatenate lists
- Learn to append and prepend lists
- Take a look at building trees
- Learn about the backtracking algorithm.
- Master Scala best practices and idioms
To fully benefit from the coverage included in this course, you will need:
This video course assumes you 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 straightforward.
This course has the following software requirements:
Scala