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Clean Code in Python

Clean Code in Python

By : Mariano Anaya
3.7 (3)
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Clean Code in Python

Clean Code in Python

3.7 (3)
By: Mariano Anaya

Overview of this book

Python is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into 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 software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code.
Table of Contents (12 chapters)
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Introduction, Code Formatting, and Tools

In this chapter, we will explore the first concepts related to clean code, starting with what it is and what it means. The main point of the chapter is to understand that clean code is not just a nice thing to have or a luxury in software projects. It's a necessity. Without quality code, the project will face the perils of failing due to an accumulated technical debt.

Along the same lines, but going into a bit more detail, are the concepts of formatting and documenting the code. This also might sound like a superfluous requirement or task, but again, we will discover that it plays a fundamental role in keeping the code base maintainable and workable.

We will analyze the importance of adopting a good coding guideline for this project. Realizing that maintaining the code align to the reference is a continuous task, and we will see how we can get help from automated tools that will ease our work. For this reason, we quickly discuss how to configure the main tools so that they automatically run on the project as part of the build.

After reading this chapter, you will have an idea of what clean code is, why it is important, why formatting and documenting the code are crucial tasks, and how to automate this process. From this, you should acquire the mindset for quickly organizing the structure of a new project, aiming for good code quality.

After reading this chapter, you will have learned the following:

  • That clean code really means something far more important than formatting in software construction
  • That even so, having a standard formatting is a key component to have in a software project, for the sake of its maintainability
  • How to make the code self-documenting by using the features that Python provides
  • How to configure tools to help arrange the layout of the code in a consistent way so that team members can focus on the essence of the problem
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Clean Code in Python
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