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Think Python 1st Edition

4 out of 5 stars 54 customer reviews
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ISBN-13: 860-1234620983
ISBN-10: 144933072X
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Editorial Reviews

Book Description

How to Think Like a Computer Scientist

About the Author

Allen Downey is an Associate Professor of Computer Science at the Olin College of Engineering. He has taught computer science 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.

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Product Details

  • Paperback: 300 pages
  • Publisher: O'Reilly Media; 1 edition (August 20, 2012)
  • Language: English
  • ISBN-10: 144933072X
  • ISBN-13: 978-1449330729
  • Product Dimensions: 7 x 0.9 x 9.2 inches
  • Shipping Weight: 1.1 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (54 customer reviews)
  • Amazon Best Sellers Rank: #202,922 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By MedIT VINE VOICE on March 19, 2011
Format: Paperback Verified Purchase
This book should be retitled ThinkPython: An Introduction to Scripting.

I would whole heartedly recommend this book to readers looking for a quick 0-60 self study in (Python) scripting. It's a great place to start for someone with really zero or next to zero experience who is looking to get up and running as quickly as possible. This book does not spend much/any time on computer science. It spends very little time on software design over and above splitting scripts into modules and basic OOP.

When my 13 year old cousin expressed some interest in programming I gave him this book without a second thought. For a high school class / intro college course for non(-committed) CS majors looking to cover the same ground in more detail I'd recommend Python Programming: An Introduction to Computer Science by Zelle. (These recommendations assume you are committed to Python if not look at How to Design Programs by F, F, F, & K)

Bottom Line: If you are looking to cultivate an interest before crushing it with big O notation or have zero interest in CS but want to automate something using Python this is a good starting place.

N.B. This book is freely available online.
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Format: Paperback
I really wanted to be able to write a perfect review for Think Python but I'm afraid I just can't bring myself to do it. Have no doubts about it this is a great little book (little in this case is a relative term - it's 300 pages which isn't generally a lightweight but it's relatively small in the computer language learning arena) which is extremely well written and very easy to get on with. However, for me it's not quite perfect. My issue is as much to do with my programming background as with the book itself. I cut my programming teeth on C - not C++ but proper, old fashioned procedural C - before moving on to PERL and PHP with a brief flirtation with Lisp. For me object oriented languages are relatively new beasts. I've been playing with Python a little bit recently, mainly to use the NLTK package, and I'm aware that I'm just programming by analogy to the languages I already know so I've been writing a sort of procedural Python. I'm sure if I understood the language and object oriented programming better I could get more out of NLTK, hence getting Think Python. However I found the structure of the book was a little bit backwards for my needs in that classes, objects and their related structures weren't formally introduced till chapter 15 and when they were introduced their coverage was a little bit sketchy. I can't help thinking that an earlier and more complete introduction to the object model of programming would be of huge benefit both to those coming to Python from a procedural background and for entirely new programmers who don't have an understanding of the paradigm.

Even with this proviso, Think Python is an excellent book for anyone interesting in learning a new language.
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Format: Paperback
This relatively compact volume (277 pages including appendices and index) offers an excellent approach to learning Python and also could serve well as a foundation course for the Computer Science curriculum in high school or university. There are several distinguishing features of Professor Downey's excellent approach; he has a Ph.D.. in Computer Science from U.C. Berkeley and Bachelors and Masters degrees from MIT. What most distinguishes this superior text from other language primers (in my opinion) are the short, 1-2 page conceptual subsections in each chapter that build up a topic-based introduction to Computer Science. Other prominent features include
the availability (by permission) of a full PDF download of the books text (ideal for following along online), and two graphical packages "swampy" and "lumpy" prepared by the author to enable simple "turtle graphics" and visualization of Data Structures given in advanced programs. This is not only an efficient book for properly learning the Python language; it also gives an orderly introduction to concepts beginning with variables and data types, leading to control structures and functions, and fully including advanced concepts such as object-oriented programming, searching and sorting, algorithms and data structures and well as more complete coverage of debugging than I have found in other texts.

I highly recommend this text for a first course in Computer Science at both secondary and university levels. It is as its title suggests an introduction to Python for Thinkers.

--Ira Laefsky MSE Computer Engineering, MBA IT Consultant & HCI Researcher
formerly on the Senior Consulting Staff of Arthur D. Little, Inc. and Digital Equipment Corporation
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Format: Paperback
"Think Python" is available online ([...]) which means you can decide if you like it first. Personally, I wanted to write in my copy making the paper copy a great thing. Inexpensive too for a computer book. It's one of those great books I know I'll refer to again. Can't imagine why you'd buy the Kindle version though.

The book is targetted at those learning Python. It's appropriate whether you are new to programming or coming from another language. And most importantly, it is NOT a "Learn Python in X days" type book. Those have their place, but this book targets those who actually are/want to be developers. Hence the subtitle "How to Think Like a Computer Scientist."

Each chapter ends with debugging tips, a glossary of terms and numerous exercises for practice. Common idioms are covered in addition to syntax, techniques and algorithms. Recursion is presented in a not scary, approachable way.

The author uses the term "state diagram" to refer to the state of variables in an object. I've never seen this usage before (being more used to the UML state diagram) and look forward to asking the author about it in his coderanch.com book promotion next month.

I think this makes for a great first Python book. To be followed by one that teaches the Python libraries. It teaches you how to think in Python. And how to be a developer; not just a coder.

Disclosure: I received a copy of this book from the publisher in exchange for writing this review.
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