Book Image

Scala Functional Programming Patterns

By : Atul S. Khot
Book Image

Scala Functional Programming Patterns

By: Atul S. Khot

Overview of this book

Scala is used to construct elegant class hierarchies for maximum code reuse and extensibility and to implement their behavior using higher-order functions. Its functional programming (FP) features are a boon to help you design “easy to reason about” systems to control the growing software complexities. Knowing how and where to apply the many Scala techniques is challenging. Looking at Scala best practices in the context of what you already know helps you grasp these concepts quickly, and helps you see where and why to use them. This book begins with the rationale behind patterns to help you understand where and why each pattern is applied. You will discover what tail recursion brings to your table and will get an understanding of how to create solutions without mutations. We then explain the concept of memorization and infinite sequences for on-demand computation. Further, the book takes you through Scala’s stackable traits and dependency injection, a popular technique to produce loosely-coupled software systems. You will also explore how to currying favors to your code and how to simplify it by de-construction via pattern matching. We also show you how to do pipeline transformations using higher order functions such as the pipes and filters pattern. Then we guide you through the increasing importance of concurrent programming and the pitfalls of traditional code concurrency. Lastly, the book takes a paradigm shift to show you the different techniques that functional programming brings to your plate. This book is an invaluable source to help you understand and perform functional programming and solve common programming problems using Scala’s programming patterns.
Table of Contents (19 chapters)
Scala Functional Programming Patterns
About the Author
About the Reviewers


We had a whirlwind tour of traversals in this chapter. We looked at functional combinators and how looping is way different from the traditional Java for loop. We also played with many examples of map, flatMap, filter, reduce, zip, and fold.

Scala for comprehension is a syntactic sugar that hides the complexity arising out of combining combinators. A running validation example delved into the nitty-gritty of the de-sugaring of the for comprehension.

This know-how prepared us to better appreciate flatMap, the glue that binds a pipeline of computations, aka the monad pattern. We saw how the for comprehension realizes monad and what happens behind the scenes. In addition, we had a detailed look at the reduce combinator and its left and right variants. A peek behind the curtain showed us the differences between reduceLeft and reduceRight.

This is the functional style where we could compose pure functions and reason better and at a higher level of abstraction. Pure functions and combinators...