Book Image

F# 4.0 Design Patterns

By : Gene Belitski
Book Image

F# 4.0 Design Patterns

By: Gene Belitski

Overview of this book

Following design patterns is a well-known approach to writing better programs that captures and reuses high-level abstractions that are common in many applications. This book will encourage you to develop an idiomatic F# coding skillset by fully embracing the functional-first F# paradigm. It will also help you harness this powerful instrument to write succinct, bug-free, and cross-platform code. F# 4.0 Design Patterns will start off by helping you develop a functional way of thinking. We will show you how beneficial the functional-first paradigm is and how to use it to get the optimum results. The book will help you acquire the practical knowledge of the main functional design patterns, the relationship of which with the traditional Gang of Four set is not straightforward. We will take you through pattern matching, immutable data types, and sequences in F#. We will also uncover advanced functional patterns, look at polymorphic functions, typical data crunching techniques, adjusting code through augmentation, and generalization. Lastly, we will take a look at the advanced techniques to equip you with everything you need to write flawless code.
Table of Contents (20 chapters)
F# 4.0 Design Patterns
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface

Chapter 6.  Sequences - The Core of Data Processing Patterns

In this chapter, we will take a deep dive into one of the most essential and utterly important arrangements of functional programming, that is, sequences. The ability to represent any data transformation as a composition of atomic functions applied to the elements of an arbitrary enumerable data container is a must for a functional programmer. The goal of this chapter is to help you acquire this mental skill. The way towards this goal is paved by the following topics covered here:

  • Review the basic data transformations and partition the immense host of standard library data transformation functions by handful of underlying processing patterns

  • Consider the duality of sequence data generators being at once a data and an on-demand calculation

  • Cover how a sequence generalizes arbitrary collections by enumerating them, which represents the pull data transformation pattern

  • Further consider just another pattern of using generated sequences...