Synopsis
Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes.
In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code.
- Learn why types are essential in modern development ecosystems
- Understand how type choices such as classes, dictionaries, and enums reflect specific intents
- Make Python extensible for the future without adding bloat
- Use popular Python tools to increase the safety and robustness of your codebase
- Evaluate current code to detect common maintainability gotchas
- Build a safety net around your codebase with linters and tests
"synopsis" may belong to another edition of this title.
About the Author
Patrick Viafore has been working in the software industry for 13+ years, working on mission critical software systems, including in lightning detection, telecommunications and operating systems. His work in static typed languages has influenced his approach to dynamic languages and how we can make them safer and more robust. He also is an organizer of the HSV.py meetup, where he can observe common Python obstacles, from beginners to experts. His goal is to make computer science/software engineering topics more approachable to the developer community.
Patrick currently works at Cloud Software Group, working on desktop and application virtualization. He also does software consulting and contracting through his business, Kudzera, LLC.
"About this title" may belong to another edition of this title.
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Robust Python: Write Clean and Maintainable Code
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