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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

Folding


Now is the perfect time to revisit the factorial function that I used at the beginning of this chapter when covering tail recursion. Let's take a sequence of bigint numbers from 1I to a value n represented by the following expression:

Seq.init (n + 1) bigint.op_Implicit |> Seq.skip 1 

Does the factorial(n) function represent nothing else but a product of the factors, each being a member of the preceding sequence? Sure, it can be seen (and implemented) as such. Let me create this implementation in the best traditions of the imperative programming style as shown here (Ch7_3.fsx):

let ``folding factorial (seq)`` n = 
  let fs = Seq.init (n + 1) bigint.op_Implicit |> Seq.skip 1 
  use er = fs.GetEnumerator() 
  let mutable acc = 1I 
  while er.MoveNext() do 
    acc <- acc * er.Current 
  acc 

Expressed in plain words, this implementation can be laid out in the following manner:

  • Take a mutable value that will serve as a result accumulator

  • Enumerate the sequence of factors

  • For each...

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