Overview of this book

Functional programming is a paradigm specifically designed to deal with the complexity of software development in large projects. It helps developers to keep track of the interdependencies in the code base and changes in its state in runtime. Mastering Functional Programming provides detailed coverage of how to apply the right abstractions to reduce code complexity, so that it is easy to read and understand. Complete with explanations of essential concepts, practical examples, and self-assessment questions, the book begins by covering the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You’ll also explore some of the more advanced patterns in the world of functional programming such as monad transformers and Tagless Final. In the concluding chapters, you’ll be introduced to the actor model, which you can implement in modern functional languages, and delve into parallel programming. By the end of the book, you will be able to apply the concepts of functional programming and object-oriented programming (OOP)in order to build robust applications.
Preface
Free Chapter
The Declarative Programming Style
Functions and Lambdas
Functional Data Structures
The Problem of Side Effects
Effect Types - Abstracting Away Side Effects
Effect Types in Practice
The Idea of the Type Classes
Basic Type Classes and Their Usage
Libraries for Pure Functional Programming
Introduction to the Actor Model
The Actor Model in Practice
Use Case - A Parallel Web Crawler
Introduction to Scala
Assessments
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Either

Either is an effect that is similar to the Try effect that we encountered in the previous chapters.

If you remember, Try is a structure that can contain either of two values—an exception, or the result of the computation. Let's briefly recall our division by zero example from the previous chapters:

`def functionalDivision(n1: Double, n2: Double): Try[Double] =  if (n2 == 0) Failure(new RuntimeException("Division by zero!"))  else Success(n1 / n2)`

Here, in the case of success, we create a Success data structure. In case of failure, we need to create an exception with a specific error message.

Is it essential to create an exception here? The useful payload is the error message, after all. Exceptions are needed in cases where they are thrown with the throw statement. However, as we discussed in previous chapters, functional programming avoids such a side...