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This book is a collection of techniques, concepts, best practices, and expertise that many experienced software engineers, programmers, and developers have collected. This book has been written using concise topics, with well laid out chapters, allowing you to discover the foundational concepts early on. You will find well-written Python code featured in every relevant topic so you can recreate the examples and understand the concepts more intricately. Programming is an art, and just as many factors can influence art, this book tries to highlight and improve your programming skills. We will address the many factors that can ruin the sensitive harmony of the different code lines. There are no hard and fast rules that can help explain the concept of “clean code,” but this book features professional expertise and advice that highlights those concepts. When these concepts of clean code are implemented, they can help make your coding more manageable, efficient, effective, and, most of all, easy to read. In this book, you will: Discover detailed techniques and concepts to help you learn how to write clean code. Learn about idioms in Python, understand indices and slices, context managers and underscore conventions. Explore the characteristics of good clean code. Review the principles of clean software code including: Single Responsibility, the Open/Closed principle, Liskov’s Substitution, Interface Segregation and Dependency Inversion Understand and implement decorators to improve the quality of code. And so much more… If you are a looking for an easy-to-understand guide on clean code, or if you are experienced and just need a quick refresher, then this book is written for you. What are you waiting for? Download you copy of this book now to delve into the advanced world of clean code. Introduction Introduction to Clean Code What is a Clean Code? Merits of Clean Code Code Formatting and Its Role Uniform Coding Style Documentation of the Code Configuration of Tools Synopsis Idioms in Python Understanding of Indices and Slices Using Context Managers Underscore Conventions in Python Making Objects That Can Iterate Characteristics of Good and Clean Code Common Characteristics of Great Code The Defensive Programming Code Design Techniques for Error Handling Understanding the Concept of Separation of Concerns Some Useful Programming Acronyms Inheritance Multiple Inheritance The Principles of Clean Software Code The Single Responsibility Principle The Open/Closed Principle A Software Code Without the Open and Closed Principle Making the Code Extensible Liskov’s Substitution Principle Using Mypy to Identify Erroneous Datatypes in Method Signatures Using the ‘Pylint’ Tool to Identify Incompatible Signatures The Interface Segregation Principle The Dependency Inversion Principle Implementing the Decorators to Improve the Quality of the Code Decorators in Python Working with Functions to Implement Decorators Working with Decorator Classes Providing Parameters to Decorators Understanding the Implementation of Decorators in Terms of “Nested Functions” Implementing Decorators Effectively and Avoiding Implementation Mistakes Using Python Generators When Coding The Purpose of Generators Understanding the Use of Generators Using Idioms to Perform Iterations Conclusion References
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Salcedo J. SPSS Statistics For Dummies 4ed 2020.pdf
