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Functional Python Programming

Functional Python Programming

By : Steven F. Lott
4 (9)
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Functional Python Programming

Functional Python Programming

4 (9)
By: Steven F. Lott

Overview of this book

This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.
Table of Contents (18 chapters)
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17
Index

Memoization and caching

As we saw in Chapter 10, The Functools Module, many algorithms can benefit from memoization. We'll start with a review of some previous examples to characterize the kinds of functions that can be helped with memoization.

In Chapter 6, Recursions and Reductions, we looked at a few common kinds of recursions. The simplest kind of recursion is a tail recursion with arguments that can be easily matched to values in a cache. If the arguments are integers, strings, or materialized collections, then we can compare arguments quickly to determine if the cache has a previously computed result.

We can see from these examples that integer numeric calculations such as computing factorial or locating a Fibonacci number will be obviously improved. Locating prime factors and raising integers to powers are more examples of numeric algorithms that apply to integer values.

When we looked at the recursive version of a Fibonacci number calculator, we saw that it contained two tail...

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