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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

10.1 Function tools

We looked at a number of higher-order functions in Chapter 5, Higher-Order Functions. Those functions either accept a function as an argument or return a function (or generator expression) as a result. All those higher-order functions have an essential algorithm that is customized by injecting another function. Functions such as max(), min(), and sorted() accept a key= function to customize their behavior. Functions such as map() and filter() accept a function and an iterable and apply the given function to the argument iterable. In the case of the map() function, the results of the function are simply yielded. In the case of the filter() function, the Boolean result of the function is used to yield or reject values from an iterable source.

All the functions in Chapter 5, Higher-Order Functions, are part of the Python __builtins__ package, meaning these functions are available without the need to use the import statement. They were made ubiquitous because...

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