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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

Design by contract

Some parts of the software we are working on are not meant to be called directly by users, but instead by other parts of the code. Such is the case when we divide the responsibilities of the application into different components or layers, and we have to think about the interaction between them.

We have to encapsulate some functionality behind each component and expose an interface to clients who are going to use that functionality, namely, an Application Programming Interface (API). The functions, classes, or methods we write for that component have a particular way of working under certain considerations that, if they are not met, will make our code crash. Conversely, clients calling that code expect a particular response, and any failure of our function to provide this would represent a defect.

That is to say that if, for example, we have a function that is expected to work with a series of parameters of type integers, and some other function invokes...

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Clean Code in Python
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