Python Programming with Design Patterns
Description:
About the Author James W. Cooper holds a PhD in chemistry and worked in academia, for the scientific instrument industry, and for IBM for 25 years, primarily as a computer scientist at IBM's Thomas J. Watson Research Center. Now retired, he is the author of 20 books, including 3 on design patterns in various languages. His most recent books are Flameout: The Rise and Fall of IBM Instruments (2019) and Food Myths Debunked (2014). James holds 11 patents and has written 60 columns for JavaPro Magazine. He has also written nearly 1,000 columns for the now vanished Examiner.com on foods and chemistry, and he currently writes his own blog: FoodScienceInstitute.com. Recently, he has written columns on Python for Medium.com and Substack. He is also involved in local theater groups and is the treasurer for Troupers Light Opera, where he performs regularly. Product Description Learn how to write Python code that's more robust, efficient, maintainable, and elegant―whether you're new to the language or you've been coding for years. Python Programming with Design Patterns combines a clear, modern introduction to modern Python with visual, example-driven explanations of 23 proven patterns for writing outstanding object-oriented code. Through these patterns and examples, best-selling patterns author James W. Cooper introduces modern techniques for creating Python objects that interact effectively to make powerful, flexible programs.Cooper's wide-ranging coverage includes abstract classes, multiple inheritance, GUI programming and widgets, graphical classes, drawing and plotting, math libraries, database programming, Python decorators, images, threads, iterators, creating executable code from Python programs, and much more. He covers the use of six leading Python development environments, and provides complete downloadable code on Github for every example program.Throughout, Cooper's informal, visual presentation makes patterns easier than ever to understand and use―so you can confidently build large, complex programs that benefit from everything Python has to offer.
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