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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

12.3 Composite design

The common mathematical notation for a composite function looks as follows:

f ∘g(x) = f(g(x))

The idea is that we can define a new function, f g(x), that combines two other functions, f(y) and g(x).

Python’s multiple-line definition of a composition function can be done through the following code:

@f_deco 
def g(x): 
    something

The resulting function can be essentially equivalent to f g(x). The @f_deco decorator must define and return the composite function by merging an internal definition of f(y) with the provided base function, g(x).

The implementation details show that Python actually provides a slightly more complex kind of composition. The structure of a wrapper makes it helpful to think of Python decorator composition as follows:

 ( ) w ∘g(x) = (wβ ∘g ∘w α)(x) = w β g(w α(x ))

A decorator applied to some application function, g(x), will include a wrapper function, w(y), that has two parts. One portion of the wrapper, wα(y), applies to the arguments of...

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