Search results for ""author david mertz""

Move Beyond Python Code That "Mostly Works" to Code That Is Expressive, Robust, and Efficient Python is arguably the most-used programming language in the world, with applications from primary school education to workaday web development, to the most advanced scientific research institutes. While there are many ways to perform a task in Python, some are wrong, inelegant, or inefficient. Better Python Code is a guide to "Pythonic" programming, a collection of best practices, ways of working, and nuances that are easy to miss, especially when ingrained habits are borrowed from other programming languages. Author David Mertz presents concrete and concise examples of various misunderstandings, pitfalls, and bad habits in action. He explains why some practices are better than others, based on his 25+ years of experience as an acclaimed contributor to the Python community. Each chapter thoroughly covers related clusters of concepts, with chapters sequenced in ascending order of sophistication. Whether you are starting out with Python or are an experienced developer pushing through the limitations of your Python code, this book is for all who aspire to be more Pythonic when writing better Python code. Use the right kind of loops in Python Learn the ins and outs of mutable and immutable objects Get expert advice to avoid Python "gotchas" Examine advanced Python topics Navigate the "attractive nuisances" that exist in Python Learn the most useful data structures in Python and how to avoid misusing them Avoid security mistakes Understand the basics of numeric computation, including floating point numbers and numeric datatypes "My high expectations for this engaging Python book have been exceeded: it offers a great deal of insight for intermediate or advanced programmers to improve their Python skills, includes copious sharing of precious experience practicing and teaching the language, yet remains concise, easy to read, and conversational."--From the Foreword by Alex Martelli Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

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Learn how AI-assisted coding using ChatGPT and GitHub Copilot can dramatically increase your productivity (and fun) in writing regular expressions and other programmes. "How these tools can be both so very amazing in what they produce, and simultaneously so utterly doltish in their numerous failures, is the main thing this book tries to understand. For reasons I attempt to elucidate throughout, of all the domains of computer programming, games with regular expressions are particularly well suited for getting a grasp on the peculiar behaviors of AI." From the Preface For programmers of any experience level – no experience with AI coding tools is required. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On the one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT. Here's how the contest works: David invents 24 Regex problems he calls puzzles and shows you how to tackle each one. When he's done he has Copilot and ChatGPT work the same puzzles. What they produce intrigues him. Which side is likelier to get it right? Which will write simple and elegant code? Which one makes the smartest use of lesser-known Regex library features? Read the book to find out. David also offers AI best practices, showing how smart prompts return better results. By the end, you'll be a master at solving your own Regex puzzles, whether you use AI or not. About the technology Ground-breaking large language model research from OpenAI, Google, Amazon, and others, have transformed expectations of machine-generated software. But how do these AI assistants, like ChatGPT and GitHub Copilot, measure up against regular expressions—a workhorse technology for developers used to describe, find, and manipulate patterns in the text? Regular expressions are compact, complex, and subtle. Will AI assistants handle the challenge?

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