More Information
  • Refactor your Python code and make it clean and easy to manage
  • Identify Python anti-patterns and remove them with easy-to-follow steps
  • Practice refactoring methods and get to grips with real-world scenarios
  • Refactor classes and objects by making them easier to understand, maintain, and more efficient
  • Implementing pattern-based refactoring
  • Make major progress by using third-party refactoring tools to speed up your refactoring work

Even the most well-planned code can develop anti-patterns over the years. These make the codebase difficult to maintain. Small changes can break major features because Python anti-patterns are a symptom of deeper problems in your code base.

Learn to resolve Python anti-patterns with techniques and methods to improve the design of your existing code. Tackle bugs by understanding the principles of refactoring, and learn to spot opportunities by identifying code that requires refactoring. We will also show you how to build test-driven processes to make refactoring easier. This course will show you how to remove Python anti-patterns from your programs in simple steps. We cover specific techniques for refactoring and improving sloppy Python code.

Take this course if you want to have a legacy Python code base with a lot of issues. Apply real-world refactoring techniques, and turn your code into clean, efficient, and maintainable projects.

All the code and supporting files of this course are available on GitHub at -

Style and Approach

This course will help you understand the principles of refactoring. With our expert guidance, you will learn to identify code that requires refactoring. Benefit from our authors' extensive experience and learn to build a test-driven process to make refactoring easier.

  • Learn techniques and methods to improve the design of your existing code
  • Identify code that requires refactoring and apply the techniques you've learned
  • Use the techniques you've learned to bring your legacy code up-to-date using refactoring
Course Length 2 hour and 47 minutes
ISBN 9781788836418
Date Of Publication 28 Sep 2018


Rudy Lai


Over the past few years, they have worked with some of the World's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways.

Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails for prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance—key analytics that all feed back into how our AI generates content.

Prior to founding QuantCopy, Rudy ran HighDimension.IO, a machine learning consultancy, where he experienced first-hand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with HighDimension.IO's Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye.

In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform from which you can learn about reinforcement learning and supervised learning topics in depth and in a commercial setting.

Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean's List, and received awards such as the Deutsche Bank Artificial Intelligence prize.