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Data Structures and Algorithms in Python

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From the Back Cover

This all-new Data Structures and Algorithms in Python is designed to provide an introduction to data structures and algorithms, including their design, analysis, and implementation. The authors take advantage of the beauty and simplicity of Python to present executable source code that is clear and concise. Furthermore, a consistent object-oriented viewpoint is retained throughout the book, including the use of inheritance, both to maximize code reuse and to draw attention to the clear similarities and differences of various abstract data types and algorithmic approaches. This is a “sister” book to Goodrich & Tamassia’s Data Structures and Algorithms in Java and Goodrich, Tamassia and Mount’s Data Structures and Algorithms in C++. This Python version retains much of the same pedagogical approach and general structure as the Java and C++ versions, so that curriculums that teach data structures in Python, Java, and C++ can share the same core syllabus. Key Features of this Book A primer that reviews the basics of programming in Python (Chapter 1), followed by a separate introduction to object-oriented programming in Python (Chapter 2). Extensive coverage of recursion (Chapter 4). A chapter describing the array-based underpinnings of Python’s standard list, string, and tuple classes (Chapter 5), including both theoretical and empirical analyses of their efficiencies. Source code with complete implementations of the majority of data structures and algorithms described in the book; the code follows modern standards for Python 3, and makes use of the standard collections module. 500 illustrations that present data structures and algorithms in a clear, visual manner. More than 750 exercises, divided into categories of reinforcement, creativity, and projects. About the cover: The cover art is based on an indigenous Australian painting style portraying what is known as Dreamtime. This style is traditionally iconic and representative of connections between points of interest or concepts; hence, it is a fitting way to capture at a high level the connections and points of interest used to visualize data structures and algorithms.

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About the Author

Michael Goodrich, PhD in Computer Science from Purdue University, 1987; Chancellor's Professor of Computer Science at University of California, Irvine; co-author (with Tamassia) of three other Wiley textbooks and a new computer security text, Addison Wesley, 2011. Roberto Tamassia, PhD in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign, 1988; Plastech Professor of Computer Science and Chair of the CS Dept at Brown University; co-author with Goodrich, see texts above. Michael Goldwasser, PhD in Computer Science from Stanford University, 1997; Associate Professor and Director of CS at St. Louis University; author of Object-Oriented Programming in Python, Pearson, 2008.

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Product details

Hardcover: 768 pages

Publisher: Wiley; 1 edition (March 18, 2013)

Language: English

ISBN-10: 1118290275

ISBN-13: 978-1118290279

Product Dimensions:

7.8 x 1.3 x 9.4 inches

Shipping Weight: 2.8 pounds (View shipping rates and policies)

Average Customer Review:

3.4 out of 5 stars

26 customer reviews

Amazon Best Sellers Rank:

#397,427 in Books (See Top 100 in Books)

I am the 13th reviewer (out of 20) to give 5-stars to ‘Data Structures & Algorithms in Python’. The book deserves it. All code is, as it should be, in the current Python 3.Some background, last year I taught myself John Zelle’s excellent ‘Python Programming: An Introduction to Computer Science’ and continued with Head First Python. These books are excellent if you are new to programming or new to Python. I had two programming classes as an undergraduate in college but that was 20 years ago. In the last 6 months, I’ve read Dasgupta’s excellent ‘Algorithms’, the UC Berkeley and UC San Diego Algorithms textbook, which demands considerable Math.This ‘Data Structures & Algorithms in Python’ textbook includes everything in Sedgewich’s excellent ‘Algorithms’ (Java-oriented) textbook (Object-Oriented Programming, Algorithm Analysis and Design, Arrays, Stacks, Queues, Trees, Sorting, Searching, Graphs, Strings, Pattern Matching, etc.). Best of all this textbook is dedicated to Python. As a Data Scientist, I want to become an expert at Python before moving on to Java or C++. This book is enabling me to become that Python expert.Thank you for writing it, Drs. Goodrich, Tamassia & Goldwasser. I hope you’re busy writing the next excellent book on Python that I’ll want to read.Best,Shawn BerryCEO, AppliedMathematicianCEO, PerfectGMATGraduate student in Georgia Tech’s MS Analytics

I like the content of the book, but the quality of the print is so bad. Pages in Chapter 9 are printed inside Chapter 3, and the pages that were supposed in Chapter 3 are gone. Many pages were printed one on top of another, like the picture shown. How am I supposed to read a book like this? Very disappointed.

This is the second copy of this book I have purchased - and from a different seller. BOTH of these have been the Indian printing that is illegal to be exported out of India and sold elsewhere - like in the US.

This book is really good. I got the international edition, but the contents covered is very beneficial. Looking forward to completing this book over next 3 months

I find that the first two chapters are great for learning python. Very concise and easy to understand. The rest is wordy and uses a lot of mathematics to explain, which a lot of it is just unnecessary and makes things more confusing. They are all PhD's so I guess they have a disability of thinking in plain English.

If you want to go deeper into data structures and algorithms whilst at the same time using python as your programming language, than this book is all you need.There are many examples that follow the explanations to each of the most important (as well of the minor ones) data structures or algorithms. This makes it easy to understand the concepts and to apply them.The authors often offer alternatives to the algorithms such as a in-place alternative to a algorithm that uses a help array. They also show the content in such a way that, whenever possible and appropriate, they build on top of previously presented topics, also making it easy to augment the knowledge you previously acquired.Recommend for students or for someone preparing to a programming interview.

The book covers all the basic data structures and algorithms covered in a second year course in my country (Norway), the code examples are also good. What is not good is the price. The material in this book is not worth over 175 USD. For less than 30 dollars you can buy Lambert's "Fundamentals of Python: Data Structures" which covers the same material and also has full code implementations. For 60 USD you can buy Sedgewick's "Algorithms" which is one of the best books on algorithms and data structures, and which has full code implementations and visuals to trace the code. It's also far more in depth than this book.This book is nothing special and I just don't understand how publishers have the heart to set these disgusting prices ripping off poor students. I am giving this book a 3-star rating not only because of the content but also because of the price. Some people say this is not right, that only the content should be reviewed. I disagree. When you pay prices that are morbidly inflated, then you should get something more than your average data structures and algorithms book written in black and white. I'm not gonna give a Toyota Prius a 5-star rating if it cost me as much as a Ferrari even though it's a decent car. Stay away from this book. Teach the publishers a lesson. There's just as good and better books for much much less.

The book itself is excellent but the quality of print is poor. The pages are see-through and thin. Some pages are also printed on wrong side (as shown in picture) and have hair-like marking.

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