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F# High Performance

You're reading from   F# High Performance Increase your F# programming productivity and focus on performance optimization with best practices, expert techniques, and more

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Product type Paperback
Published in Jan 2017
Publisher Packt
ISBN-13 9781786468079
Length 338 pages
Edition 1st Edition
Languages
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Author (1):
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 Kusumawardhono Kusumawardhono
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Kusumawardhono
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Table of Contents (15) Chapters Close

F# High Performance
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Performing Common Optimizations in F# FREE CHAPTER 2. Performance Measurement 3. Optimizing Data Structures 4. Introduction to Concurrency in F# 5. Advanced Concurrency Support in F# 6. Optimizing Type Provider 7. Language Features and Constructs Optimization 8. Optimizing Computation Expressions

Quick introduction to F# computation expression


One of the quite subtle, but quite common, traits of a functional programming language is the availability of features to combine and compose functions into more sophisticated conceptual techniques that also encapsulate some side effects when combining functions. Some of these techniques are known as Monoids and Monads. These two come from the world of a subset of algebra, the category theory. This mathematical foundation gives the inspiration and also powerful concepts when composing and combining functions, including side effects.

For a more gentle introduction and information to Monads in functional programming, you could watch this MSDN Channel 9 interview with Microsoft's developer Brian Beckman:

https://channel9.msdn.com/Shows/Going+Deep/Brian-Beckman-Dont-fear-the-Monads

The best sample of F# computation expression is the asynchronous workflow. The term workflow in asynchronous workflow comes from the fact that it is implemented from...

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