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The Python Workshop Second Edition

The Python Workshop Second Edition - Second Edition

By : Wade, Mario Corchero Jiménez , Bird, Dr. Lau Cher Han, Graham Lee
4.6 (19)
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The Python Workshop Second Edition

The Python Workshop Second Edition

4.6 (19)
By: Wade, Mario Corchero Jiménez , Bird, Dr. Lau Cher Han, Graham Lee

Overview of this book

Python is among the most popular programming languages in the world. It’s ideal for beginners because it’s easy to read and write, and for developers, because it’s widely available with a strong support community, extensive documentation, and phenomenal libraries – both built-in and user-contributed. This project-based course has been designed by a team of expert authors to get you up and running with Python. You’ll work though engaging projects that’ll enable you to leverage your newfound Python skills efficiently in technical jobs, personal projects, and job interviews. The book will help you gain an edge in data science, web development, and software development, preparing you to tackle real-world challenges in Python and pursue advanced topics on your own. Throughout the chapters, each component has been explicitly designed to engage and stimulate different parts of the brain so that you can retain and apply what you learn in the practical context with maximum impact. By completing the course from start to finish, you’ll walk away feeling capable of tackling any real-world Python development problem.
Table of Contents (16 chapters)
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13
Chapter 13: The Evolution of Python – Discovering New Python Features

Profiling code

Having exhausted the minimum-effort options for improving your code’s performance, it’s time to actually put some work in if you need to go faster. There’s no recipe to follow to write fast code: if there were, we could have taught you that in the previous chapter and there wouldn’t need to be a section on performance now. Of course, speed also isn’t the only performance goal – you might want to reduce memory use or increase the number of simultaneous operations that can be in flight – but programmers often use “performance” as a synonym for “reducing time to completion,” and that’s what you’ll investigate here.

Improving performance is a scientific process: you observe how your code behaves, hypothesize about a potential improvement, make the change, and then observe it again and check that you really did improve things. Good tool support exists for the observation steps in...

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The Python Workshop Second Edition
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