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Learning Advanced Python by Studying Open Source Projects

Rongpeng Li

$357

Hardback

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English
Chapman & Hall/CRC
10 November 2023
This book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and, most importantly, passion.

Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python.

Throughout this book, readers will learn how to write Python code that is efficient, readable and maintainable, covering key topics such as data structures, algorithms, object-oriented programming and more. The author’s passion for Python shines through in this book, making it an enjoyable and inspiring read for both beginners and experienced programmers.

By:  
Imprint:   Chapman & Hall/CRC
Country of Publication:   United Kingdom
Dimensions:   Height: 254mm,  Width: 178mm, 
Weight:   412g
ISBN:   9781032328188
ISBN 10:   1032328185
Series:   Chapman & Hall/CRC The Python Series
Pages:   126
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active
Introduction Chapter 1 ◾ The Data Model of Python Chapter 2 ◾ Selected Topics of Python Classes Chapter 3 ◾ Concurrency in Python Chapter 4 ◾ Asynchronous Programming in Python Chapter 5 ◾ Power Up Your Python Functions Chapter 6 ◾ Selected OOP Design Best Practices Chapter 7 ◾ Testing in a Pistachio Shell

Rongpeng Li (Ron) is a YouTube educator and animator. He has a consistent passion for education. He has published two books on statistics and scientific simulation.

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