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Clean Code in Python

Clean Code in Python - Second Edition

By : Mariano Anaya
4.6 (34)
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Clean Code in Python

Clean Code in Python

4.6 (34)
By: Mariano Anaya

Overview of this book

Experienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code. This second edition has been updated to reflect new best practices in Python 3.9, helping developers write professional, scalable, and maintainable code. It introduces advanced object-oriented design, decorators, descriptors, and refactoring strategies using SOLID principles. Whether modernizing legacy projects or building new applications, this book provides practical techniques to write cleaner and more efficient Python code using the Python standard library and manage your projects successfully. The book begins by describing the basic elements of writing clean code and how it plays a key role in Python programming. The book discusses object-oriented programming in Python and show you the design principles of software testing and how to resolve problems by implementing software design patterns in your code. In the concluding chapter, we break down a monolithic application into a microservices-based one starting from the code as the basis for a solid platform. By the end of this clean code book, you will be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world Python code.
Table of Contents (13 chapters)
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11
Other Books You May Enjoy
12
Index

Getting More Out of Our Objects with Descriptors

This chapter introduces a new concept that is more advanced in Python development since it features descriptors. Moreover, descriptors are not something programmers of other languages are familiar with, so there are no easy analogies or parallelisms to make.

Descriptors are another distinctive feature of Python that take object-oriented programming to another level, and their potential allows users to build more powerful and reusable abstractions. Most of the time, the full potential of descriptors is observed in libraries or frameworks.

In this chapter, we will achieve the following goals that relate to descriptors:

  • Understand what descriptors are, how they work, and how to implement them effectively
  • Analyze the two types of descriptors (data and non-data descriptors) in terms of their conceptual differences and implementation details
  • Reuse code effectively through descriptors
  • Analyze examples of...
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Clean Code in Python
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