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Functional Python Programming, 3rd edition

Functional Python Programming, 3rd 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

2.3 Strict and non-strict evaluation

Functional programming’s efficiency stems, in part, from being able to defer a computation until it’s required. There are two similar concepts for avoiding computation. These are:

  • Strictness: Python operators are generally strict and evaluate all sub-expressions from left to right. This means an expression like f(a)+f(b)+f(c) is evaluated as if it was (f(a)+f(b))+f(c). An optimizing compiler might avoid strict ordering to improve performance. Python doesn’t optimize and code is mostly strict. We’ll look at cases where Python is not strict below.

  • Eagerness and laziness: Python operators are generally eager and evaluate all sub-expressions to compute the final answer. This means (3-3) * f(d) is fully evaluated even though the first part of the multiplication—the (3-3) sub-expression—is always zero, meaning the result is always zero, no matter what value is computed by the expression f(d). Generator...

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