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Functional Python Programming

You're reading from   Functional Python Programming Create succinct and expressive implementations with functional programming in Python

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784396992
Length 360 pages
Edition 1st Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Toc

Table of Contents (18) Chapters Close

Preface 1. Introducing Functional Programming FREE CHAPTER 2. Introducing Some Functional Features 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 Index

Summary

In this chapter, we looked at three optimization techniques. The first technique involves finding the right algorithm and data structure. This has more impact on performance than any other single design or programming decision. Using the right algorithm can easily reduce runtimes from minutes to fractions of a second. Changing a poorly used sequence to a properly used mapping, for example, may reduce run time by a factor of 200.

We should generally optimize all of our recursions to be loops. This will be faster in Python and it won't be stopped by the call stack limit that Python imposes. There are many examples of how recursions are flattened into loops in other chapters, primarily, Chapter 6, Recursions and Reductions. Additionally, we may be able to improve performance in two other ways. First, we can apply memoization to cache results. For numeric calculations, this can have a large impact; for collections, the impact may be less. Secondly, replacing large materialized data...

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