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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 2. Introducing Essential Functional Concepts FREE CHAPTER 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

Specializing memoization

The essential idea of memoization is so simple that it can be captured by the @lru_cache decorator. This decorator can be applied to any function to implement memoization. In some cases, we may be able to improve on the generic idea with something more specialized. There are a large number of potentially optimizable multivalued functions. We'll pick one here and look at another in a more complex case study.

The binomial, , shows the number of ways n different things can be arranged in groups of size m. The value is as follows:

Clearly, we should cache the individual factorial calculations rather than redo all those multiplications. However, we may also benefit from caching the overall binomial calculation, too.

We'll create a Callable object that contains multiple internal caches. Here's a helper function that we'll need:

from functools...
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