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F# 4.0 Design Patterns

You're reading from   F# 4.0 Design Patterns Solve complex problems with functional thinking

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Product type Paperback
Published in Nov 2016
Publisher Packt
ISBN-13 9781785884726
Length 318 pages
Edition 1st Edition
Languages
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Author (1):
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Gene Belitski Gene Belitski
Author Profile Icon Gene Belitski
Gene Belitski
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Table of Contents (14) Chapters Close

Preface 1. Begin Thinking Functionally 2. Dissecting F# Origins and Design FREE CHAPTER 3. Basic Functions 4. Basic Pattern Matching 5. Algebraic Data Types 6. Sequences - The Core of Data Processing Patterns 7. Advanced Techniques: Functions Revisited 8. Data Crunching – Data Transformation Patterns 9. More Data Crunching 10. Type Augmentation and Generic Computations 11. F# Expert Techniques 12. F# and OOP Principles/Design Patterns 13. Troubleshooting Functional Code

Lazy evaluation


This concept is very simple. By default, F# follows the eager evaluation (https://en.wikipedia.org/wiki/Eager_evaluation) strategy, or an expression is evaluated as soon as it is bound. The alternative strategy available in other functional programming languages is to postpone the calculations until their result is absolutely necessary. F# can be explicitly told where to use lazy evaluation; by default, it uses lazy evaluations only for sequences. Expressing lazy evaluation if F# is not complicated syntactically, the following binding serves the purpose as shown:

let name = lazy ( expression ) 

Here, name is bound to the result of calculating expression, but the calculation itself is postponed. The type of value name is a special one, that is, Lazy<'T>; it represents a wrapper over 'T, which is the type of the expression per se. The computation gets performed by calling the Force method of type Lazy<'T>, like this name.Force(). This action also unwraps the underlying...

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