Learning functional programming : managing code complexity by thinking functionally

Learn how to think and write code like a functional programmer. With this practical guide, software developers familiar with object-oriented programming will dive into the core concepts of functional programming and learn how to use both functional and OOP features together on large or complex software projects. Author Jack Widman uses samples from Java, Python, C#, Scala, and JavaScript to help you gain a new perspective and a set of tools for managing the complexity in your problem domain. You'll be able to write code that's simpler, reusable, easier to test and modify, and more consistently correct. This book also shows you how to use patterns from category theory to help bridge the gap between OOP and functional programming. - Learn functional programming fundamentals and explore the way functional programmers approach problems - Understand how FP differs from object-oriented and imperative programming - Use a set of practical, applicable design patterns that model reality in a functional way - Learn how to incorporate FP and OOP features into software projects - Apply functional design patterns appropriately and use them to write correct, robust, and easily modifiable code Preface Who Should Use This Book? How The Book Is Organized Conventions Used in This Book O’Reilly Online Learning How to Contact Us What Is Functional Programming? Immutability Referential Transparency Higher Order Functions Lazy Evaluation Thinking Like a Functional Programmer The Benefits of FP FP Can Improve Productivity FP Is Fun! Scala Conclusion Mathematical Preliminaries Set Theory Functions Kinds of Functions Computer Science Fundamentals Anonymous Functions Functions as First Class Objects Conclusion Category Theory and Patterns Category Theory–Based Patterns A Brief History Objects and Morphisms An Example of a Category The Category Scal Functors Programming Language Formulation of a Functor The Patterns The Functor Pattern Monoids Natural Transformations Monads Conclusion Functional Data Structures The Option Data Structure The Try Data Structure The Either Data Structure Higher Order Functions Monads in for Comprehensions in Scala Traditional Data Structures Immutability and History Laziness Conclusion More on Immutability Mutable and Immutable Variables Recursion A Linked List Example Tail Recursion More Examples of the Power of fold in Scala A Connection Between fold and Monoids More with Higher Order Functions From map to flatMap Conclusion Questions of Concurrency Streams Akka Streams Source Flow Sink More on Streams FS2: Functional Streams for Scala Conclusion Where to from Here? Taking the Pure Route The IO Monad Taking the Middle Route JVM Languages .NET Languages Type Classes Conclusion Scala Assumptions Overview var and val Classes and Objects Functions Functions that Return Functions Case Classes Declaring Functions Currying Anonymous Functions Higher Order Functions Pattern Matching Traits Distinguishing Abstract Classes and Traits Lazy Evaluation Type Parameters The Option Type Future Some Key Higher Order Functions Some Other Important Higher Order Functions Conclusion Index About the Author