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Functional Python Programming, 3rd edition

Functional Python Programming, 3rd edition - Third Edition

By : Steven F. Lott
4.5 (28)
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Functional Python Programming, 3rd edition

Functional Python Programming, 3rd edition

4.5 (28)
By: Steven F. Lott

Overview of this book

Not enough developers understand the benefits of functional programming, or even what it is. Author Steven Lott demystifies the approach, teaching you how to improve the way you code in Python and make gains in memory use and performance. If you’re a leetcoder preparing for coding interviews, this book is for you. Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with Python 3.10+ examples focused on mathematical and statistical algorithms, data cleaning, and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage. You don't have to abandon object-oriented design completely, though – you'll also see how Python's native object orientation is used in conjunction with functional programming techniques. By the end of this book, you'll be well-versed in the essential functional programming features of Python and understand why and when functional thinking helps. You'll also have all the tools you need to pursue any additional functional topics that are not part of the Python language.
Table of Contents (18 chapters)
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Preface
16
Other Books You Might Enjoy
17
Index

 6
Recursions and Reductions

Many functional programming language compilers will optimize a recursive function to transform a recursive call in the tail of the function to an iteration. This tail-call optimization will dramatically improve performance. Python doesn’t do this automatic tail-call optimization. One consequence is pure recursion suffers from limitations. Lacking an automated optimization, we need to do the tail-call optimization manually. This means rewriting recursion to use an explicit iteration. There are two common ways to do this, and we’ll consider them both in this chapter.

In previous chapters, we’ve looked at several related kinds of processing design patterns; some of them are as follows:

  • Mapping and filtering, which create collections from collections

  • Reductions that create a scalar value from a collection

The distinction is exemplified by functions such as map() and filter() that accomplish the first kind of collection processing. There...

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