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You're reading from  Advanced Python Programming - Second Edition

Product typeBook
Published inMar 2022
PublisherPackt
ISBN-139781801814010
Edition2nd Edition
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Author (1)
Quan Nguyen
Quan Nguyen
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Quan Nguyen

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.
Read more about Quan Nguyen

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Summary

This chapter covered the decorator pattern and its relationship to the Python programming language. We used the decorator pattern conveniently to extend the behavior of an object without using inheritance. Python, with its built-in decorator feature, extends the decorator concept even more, by allowing us to extend the behavior of any callable (function, method, or class) without using inheritance or composition.

We have seen a few examples of real-world objects that are decorated, such as cameras. From a software point of view, both Django and Pyramid use decorators to achieve different goals, such as controlling HTTP compression and caching.

The decorator pattern is a great solution for implementing cross-cutting concerns because they are generic and do not fit well into the OOP paradigm. We mentioned several categories of cross-cutting concerns in the Use cases section. In fact, in the Implementation section, a cross-cutting concern was demonstrated: memoization. We...

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Advanced Python Programming - Second Edition
Published in: Mar 2022Publisher: PacktISBN-13: 9781801814010

Author (1)

author image
Quan Nguyen

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.
Read more about Quan Nguyen