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Functional Python Programming

You're reading from   Functional Python Programming Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788627061
Length 408 pages
Edition 2nd Edition
Languages
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Toc

Table of Contents (18) Chapters Close

Preface 1. Understanding Functional Programming FREE CHAPTER 2. Introducing Essential Functional Concepts 3. Functions, Iterators, and Generators 4. Working with Collections 5. Higher-Order Functions 6. Recursions and Reductions 7. Additional Tuple Techniques 8. The Itertools Module 9. More Itertools Techniques 10. The Functools Module 11. Decorator Design Techniques 12. The Multiprocessing and Threading Modules 13. Conditional Expressions and the Operator Module 14. The PyMonad Library 15. A Functional Approach to Web Services 16. Optimizations and Improvements 17. Other Books You May Enjoy

Tail recursion optimizations

In Chapter 6, Recursions and Reductions, among many others, we looked at how a simple recursion can be optimized into a for loop. We'll use the following simple recursive definition of factorial as an example:

The general approach to optimizing a recrusion is this:

  • Design the recursion. This means the base case and the recursive cases as a simple function that can be tested and shown to be correct, but slow. Here's the simple definition:
def fact(n: int) -> int:
    if n == 0: return 1
    else: return n*fact(n-1)  
  • If the recursion has a simple call at the end, replace the recursive case with a for loop. The definition is as follows:
def facti(n: int) -> int:
    if n == 0: return 1
    f = 1
    for i in range(2,n):
        f = f*i
    return f

When the recursion appears at the end of a simple function, it's described as...

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