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Clean Code in Python

Clean Code in Python

By : Anaya
4.6 (34)
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Clean Code in Python

Clean Code in Python

4.6 (34)
By: Anaya

Overview of this book

Experienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code. With updated code and revised content aligned to the new features of Python 3.9, this second edition of Clean Code in Python will provide you with all the tools you need to overcome these obstacles 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. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. The book discusses object-oriented programming in Python and shows you how to use objects with descriptors and generators. It will also 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

Summary

In this chapter, we have explored the main features of Python, with the goal of understanding its most distinctive features, those that make Python a peculiar language compared to the rest. Along this path, we have explored different methods of Python, protocols, and their internal mechanics.

As opposed to the previous chapter, this one is more Python-focused. A key takeaway of the topics of this book is that clean code goes beyond following the formatting rules (which, of course, are essential to a good code base). They are a necessary condition, but not sufficient. Over the next few chapters, we will see ideas and principles that relate more to the code, with the goal of achieving a better design and implementation of our software solution.

With the concepts and the ideas of this chapter, we explored the core of Python: its protocols and magic methods. It should be clear by now that the best way of having Pythonic, idiomatic code is not only by following the formatting conventions, but also by taking full advantage of all the features Python has to offer. This means that you can write more maintainable code by using a particular magic method, a context manager, or writing more concise statements by using comprehensions and assignment expressions.

We also got acquainted with asynchronous programming, and now we should feel comfortable reading asynchronous code in Python. This is important because asynchronous programming is becoming increasingly popular, and it'll be useful for future topics, explored later in the book.

In the next chapter, we will put these concepts into action, relating general concepts of software engineering with the way they can be written in Python.

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