Data Structure and Algorithmic Thinking with Pytho

I've covered the first two chapters so far, so remember this while reading my review. The book seems to go through all the basic topics in the field of algorithms and data structures, so the content should get you through anything you may want to do after. Pros: - LOTS of problems with proofs, this is by far the most important aspect of this book - uses Python, so it's simple to implement and understand - clear layout and organization Cons: - printed in an ENORMOUS format, a tiny bit shorter than A4 , but wider. It's a real burden to hold while reading, or just carry around. - some annoying use of English, for example the author sometimes ignores the use of articles altogether - sometimes the explanations are far too long, and not very clear. You lose the point of the whole thing while reading it. - some typos and errors in formulas (for example pag 31, solution to problem 22, the note should say = 2**n - 1 not 2**n . Overall I would recommend the book to anyone interested in the field.

This is rough translation of the author's Java book. He did not bother to investigate what is the notion arrays in Python and similar minor concepts where Python and other languages differ. A careful reader finds this thing really bizarre and irritating as the author does not have basic understanding of Python and he is writing book on its data structures. I had read some sample chapters of his Java algorithms book and so I had high hopes but I am really disappointed. Don't know how editors get it pass for published? An average university's above average CS student can do more justice to the subject. The author has simply used his earlier name and fame to grab more cash.

A clear style and a thorough treatment that helps to think about the algorithms and data structures. Two other texts that I have been studying from failed to get me thinking about the material. The Python angle made this indispensable for me.

Helped me achieve a good grade

I used this book to prepare for summer internships. I rate this book slightly above average because as claimed by the book, it is just what I needed to prepare for my interviews - the book is more of a series of lecture notes from a class on Data Structures and Algorithms with a variety of problems. On the positive side, the book focuses on conveying the most essential aspects of each topic followed by problems of increasing difficulty. The solutions are often supported by full Python code. However, there are a number of grammatical errors, as well as a few bugs in the code. And, let me mention that I have not been very thorough during my preparation; so I bet one would spot even more errors. My suggestion to the authors would be to review and rectify the errors first, next improve on the exposition and only then publish the next version/reprint. As time permits, I would be happy to add to the book's errata to bring to your attention the aforementioned errors. Moreover, I felt the book is a little bulky to carry. It would be more convenient if it could be reduced to 3/4th its current size even if it calls for adding more pages; and I think the figures, codes and the surrounding space can be used more effectively for the contextual text to aid in reducing the overall book size.