![]() I like that the book addresses how to think like a programmer - how to use debugging techniques to make your program execute, how to understand the ‘flow of execution’ and create 'stack diagrams', how to interpret error messages, how to keep cool and persevere! In general it covers the programmer mindset and how to develop it, in addition to just teaching the language. The examples and text are specific to data science which does not lend itself much to variety. The text is easy to navigate and I saw no significant issues in navigation. The text is well organized and presents a clear picture of the topic it covers. If some topics need to be handled differently, the book organization makes it easy to move them around. There are subjects referenced in different modules as per their complexity. I found the book is written in a modular fashion and easy to digest as I read. I found the book consistent in its approach to the subject and the way the chapters are structured. The glossary has more accurate definitions than the ones used in text. The author at times uses a technical terminology in flow and later explains it. The language is simple, easy to read and understand. ![]() The book flows well and is a good introductory text for Programming in general, using Python as an example of a programming language. Further version updates will be easy to incorporate as well. ![]() The book is accurate and the author has made updates and acknowledged suggestions/edits by reviewers, and made relevant updates.Ĭontent is up-to-date as the book has been updated and uses Python 3, pointing out where relevant, differences from Python 2. ![]() Case studies are presented after each set of congruent concepts, and there are three in all in the text book. The text covers all subject areas well with a comprehensive index, debugging tips at end of each chapter, with glossary and exercises, together forming a good scaffolding structure. Reviewed by Rekha Rao, Adjunct Instructor, Portland Community College on 7/1/22 The book’s strengths lie in its clear exposition, structured approach, and comprehensive coverage of essential topics. Think Python book is a commendable resource for those looking to begin their journey with Python programming. However, it's written in a neutral tone and is designed to be accessible to a broad audience. It's well laid out with clear headings, diagrams, and code snippets.ĭowney's book is primarily focused on technical content and doesn't delve deep into cultural aspects. This structured approach aids in understanding and retention. The content flows logically from basic to more complex topics. However, I recommend covering Data Types such as List, Set, and Dictionary in the early phases. The examples and exercises are pertinent to real-world programming scenarios.ĭowney writes in a simple and understandable manner, making complex topics accessible to beginners.Įach chapter builds upon the last, making the learning process seamless. The author presents information in a way that aligns with industry standards and Python conventions. It covers fundamental programming concepts, Python-specific syntax, and also introduces more advanced topics. Reviewed by Eljilani Hmouda, Assistant Professor of Computer Science, Lander University on 10/19/23
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