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Think Python: How to Think Like a Computer Scientist 2nd Edition
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If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3.
Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser.
- Start with the basics, including language syntax and semantics
- Get a clear definition of each programming concept
- Learn about values, variables, statements, functions, and data structures in a logical progression
- Discover how to work with files and databases
- Understand objects, methods, and object-oriented programming
- Use debugging techniques to fix syntax, runtime, and semantic errors
- Explore interface design, data structures, and GUI-based programs through case studies
About the Author
Allen Downey is a Professor of Computer Science at Olin College of Engineering. He has taught at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT.
- ISBN-101491939362
- ISBN-13978-1491939369
- Edition2nd
- PublisherO'Reilly Media
- Publication dateJanuary 26, 2016
- LanguageEnglish
- Dimensions7 x 0.7 x 9.1 inches
- Print length289 pages
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Product details
- Publisher : O'Reilly Media; 2nd edition (January 26, 2016)
- Language : English
- Paperback : 289 pages
- ISBN-10 : 1491939362
- ISBN-13 : 978-1491939369
- Item Weight : 2.31 pounds
- Dimensions : 7 x 0.7 x 9.1 inches
- Best Sellers Rank: #61,366 in Books (See Top 100 in Books)
- #25 in Object-Oriented Design
- #65 in Software Development (Books)
- #66 in Python Programming
- Customer Reviews:
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About the author

Allen Downey is a Professor of Computer Science at Olin College and author of books related to programming and data science, including Think Python, Think Stats, Think Bayes, Think Complexity, and several others. The idea behind these books is that if you know how to program, you can use that skill to learn other things.
Allen has a Ph.D. from U.C. Berkeley and M.S. and B.S. degrees from MIT. He has taught at Colby College and Wellesley College.
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If you are looking to learn Python in-depth, this is not the book for you. However, if you want a survey of Python - what it can do, how it works (generally) - this is a good book.
I like the easy-to-understand language used in this book. The author does not make any assumptions about prior programming knowledge.
The book just scratches the surface of Python. It runs though a large number of topics, touching each with just enough to give the reader an understanding of the bigger picture. However, it doesn't do a deep dive on any topic in particular.
Overall, as a primer it's a great book. But be prepared to go deeper with other resources if you want to become even a good novice Python programmer.
This sounds like a sadly limited description of the capabilities of such a flexible and powerful language. Or does Python really live in its own little world?
I'm an old geezer in a hurry, looking for a computer language that will read existing binary files whose unicode names are provided from the Windows command line. It doesn't sound like much to ask, but every computer language I know has one or another problem doing it. Dare I hope that Python can be cajoled into meeting these simple requirements, and I can learn how by buying another book, or should I look for another language?
The only caveat I would give is that this may not be the best choice for the math-averse, as many of the exercises involve dealing with math problems. I would not consider myself particularly mathematically inclined and can still get through them with some effort, and enjoy the challenge of learning something new and putting some long-unused brain cells to work, but it may be frustrating if you really hate math. There is always the option to skip exercises you don't like, of course.
I definitely recommend this book to anyone interested in programming, or wanting to learn Python, beginners included. I had a little programming experience coming in, and breezed through the first few chapters, but the exercises quickly build in difficulty so even after a few chapters, I think all but quite experienced programmers will find some that are challenging and help you build proficiency in the language.
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Though I had been working with Python for a while now, I wanted a book that explained what works and why, when it comes to Python;
When following any online tutorial or solutions online , most times I noticed that - essentially although their way of working the syntax worked but none seemed to know or explain why. So, to that end - this book does the job really well.












