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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

7.4 Complicated object initialization and property computations

When working with data in unhelpful formats, it often becomes necessary to build Python objects from source data that has a different structure or different underlying object types. There are two overall ways to treat object creation:

  • It’s part of the application as a whole. Data should be decomposed by a parser and recomposed into useful Python objects. This is the approach we’ve taken in previous examples.

  • It’s part of the object’s class definition. Source data should be provided more or less in its raw form, and the class definition will perform the necessary conversions.

This distinction is never simple, nor crisp. Pragmatic considerations will identify the best approach for each unique case of building a Pythonic object from source data. The two examples that point to the distinct choices available are the following:

  • The Point class: The syntax for geographic points is highly variable...

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