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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
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Other Books You Might Enjoy
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Index
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4.4 Using len() and sum() on collections

The len() and sum() functions provide two simple reductions—a count of the elements and the sum of the elements in a sequence. These two functions are mathematically similar, but their Python implementation is quite different.

Mathematically, we can observe this cool parallelism:

  • The len() function returns the sum of ones for each value in a collection, X: xX1 = xXx0.

  • The sum() function returns the sum of each value in a collection, X: xXx = xXx1.

The sum() function works for any iterable. The len() function doesn’t apply to iterables; it only applies to sequences. This little asymmetry in the implementation of these functions is a little awkward around the edges of statistical algorithms.

As noted above, for empty sequences, both of these functions return a proper additive identity value of zero:

>>> sum(()) 
0 
>>> len(()) ...

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