Packt - Python Clean Coding

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Packt - Python Clean Coding
English | Size: 442.06 MB
Category: Programming
Learn
Practical examples and case studies to demonstrate effective coding
Set up a programming environment that encourages beautiful code
How to take full advantage of Python features to make your code elegant
Master available tools and modules to improve the cleanliness of your Python code
General stylistic guidelines to make your code readable, maintainable, and extendable
How to program in different stylistic paradigms for maximum code cleanliness depending on the application
How to identify and rewrite bad code

About
Even bad code can function. But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn't have to be that way.
Peter Fisher will teach you Python features that are applicable to writing clean code. First, we will talk about the pros and cons that confront the programmer when trying to write clean Python code. Then, we will explore the structure of a Python program and highlight features that will help us clean up and simplify our code. We will explore some good editors with built-in code analysis and linters to help guide you. We will also talk about some very helpful modules that will keep your code clean and prevent you from reinventing the wheel. Then, we will discuss some general code cleaning guidelines that aren't exclusively applicable to Python, including naming conventions and programming styles.
Finally, we will apply what we've learned in the previous videos to rewriting and reorganizing real-world Python programs into clean and beautiful code that can be more easily understood, debugged, and extended.
The Github Link to this video course is: [url=https://github.com/PacktPublishing/Writing-Clean-Python-Code]https://github.com/PacktPublishing/Writing-Clean-Python-Code
Features

Make your organization more effective with efficient and clean coding practices
Identify good code and bad code, and learn to convert bad code into good
Detailed examples of Python features that will enable you to write descriptive, elegant code

Course Length2 hours 8 minutes
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