Python Clean Coding

Python Clean Coding

Discover simple practices for writing clean and efficient Python code

Created By: Peter Fisher
15.87 9.52

About This Course

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:
This course uses Python 3.6 while not the latest version available, it provides relevant and informative content for legacy users of Python.

Other Information

  • Certificate will provided in this course on Completion
  • Full lifetime access
  • Available on Mobile & Laptop

What Students Will Learn In Your Course?

  • 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

Are There Any Course Requirements Or Prerequisites?

A basic understanding of programming is assumed.

Who Are Your Target Students?

This course will appeal to Python developers and programmers, software engineers, project managers, team leads, and systems analysts with an interest in producing better Python code.

Course Content

  • 19 lectures
  • 02:08:47
  • The Course Overview
  • We Read Code More than We Write Code
  • Complicated Code Is Equal to Bad Code
  • How to Write Clean Code in Python?
  • Not Invented Here (NIH) Principle
  • Keep Things Simple Stupid
  • Python Dictionaries
  • Python Decorators
  • Python Context Managers
  • What Are Python Coding Standards?
  • How to Follow Python Coding Standards?
  • Tools versus Reporters
  • Naming Things Is Hard
  • Context Matters
  • How to Write Cleaner Functions?
  • Comments VS Code
  • Test Driven Development (TDD) and Clean Code
  • Cleaning Up a Legacy Application
  • Course Summary

Packt Publication

  • 4.48 (25)
  • 13 Reviews
  • 25 Students
  • 935 Courses