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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

12.2 Cross-cutting concerns

One general principle behind decorators is to allow us to build a composite function from the decorator and the original function to which the decorator is applied. The idea is to have a library of common decorators that can provide implementations for common concerns.

We often call these cross-cutting concerns because they apply across several functions. These are the sorts of things that we would like to design once through a decorator and have them applied in relevant classes throughout an application or a framework.

Concerns that are often centralized as decorator definitions include the following:

  • Logging

  • Auditing

  • Security

  • Handling incomplete data

A logging decorator, for example, may write standardized messages to the application’s log file. An audit decorator may write details surrounding a database update. A security decorator may check some runtime context to be sure that the login user has the necessary permissions.

Our example of a null...

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