Book Image

Scala Functional Programming Patterns

By : S. Khot
Book Image

Scala Functional Programming Patterns

By: 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 (13 chapters)
12
Index

Monads

In the above, flatMap binds stuff together. All the combinator blocks are closure blocks. The map block, for example, is accessing variables from its enclosing scopes. And all blocks are returning back a list of strings.

What does a flatMap do? It maps and then flattens the result. For example, the following is a way to pick up numbers from List[Any]. Using a map does not fully cut it:

scala> val l = List(1, "this", 2, 4.4, 'c')
l: List[Any] = List(1, this, 2, 4.4, c)

scala> l map {
     |   case i: Int => Some(i)
     |   case _ => None
     | }
res0: List[Option[Int]] = List(Some(1), None, Some(2), None, None)

We just need the numbers; however, we get them wrapped up in Some or we get them wrapped up in None. We have already seen both how we could collect and a partial function for picking up numbers:

scala> l flatMap {
     |   case i: Int => Some(i)
     |   case _ => None
     | }
res1: List[Int] = List(1, 2)

So, flatMap does both the mapping...