Data Structures and Algorithms in Python Hardcover – 5 Jul 2013
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From the Back Cover
This all-new Data Structures and Algorithms in Python isdesigned to provide an introduction to data structures andalgorithms, including their design, analysis, and implementation.The authors take advantage of the beauty and simplicity of Pythonto present executable source code that is clear and concise.Furthermore, a consistent object-oriented viewpoint is retainedthroughout the book, including the use of inheritance, both tomaximize code reuse and to draw attention to the clear similaritiesand differences of various abstract data types and algorithmicapproaches.
This is a "sister" book to Goodrich &Tamassia's Data Structures and Algorithms in Java andGoodrich, Tamassia and Mount's Data Structures andAlgorithms in C++. This Python version retains much of the samepedagogical 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 toobject-oriented programming in Python (Chapter 2).
- Extensive coverage of recursion (Chapter 4).
- A chapter describing the array-based underpinnings ofPython's standard list, string, and tuple classes (Chapter5), including both theoretical and empirical analyses of theirefficiencies.
- Source code with complete implementations of the majority ofdata structures and algorithms described in the book; the codefollows modern standards for Python 3, and makes use of thestandard collections module.
- 500 illustrations that present data structures and algorithmsin a clear, visual manner.
- More than 750 exercises, divided into categories ofreinforcement, creativity, and projects.
About the cover:
The cover art is based on an indigenous Australian paintingstyle portraying what is known as Dreamtime. This style istraditionally iconic and representative of connections betweenpoints of interest or concepts; hence, it is a fitting way tocapture at a high level the connections and points of interest usedto visualize data structures and algorithms.
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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For example in the chapter on Trees the theoretical content is great but the examples are badly presented. Implementations are not complete and data types are not explicitly presented via an example of their use. Which is a shame as in many way the best way to learn is by seeing a complete working implementation first.
So whilst I get the whole learn by working it out philosophy, this is better done with access to somebody who can answer your questions rather than a book.
Most helpful customer reviews on Amazon.com
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.
Graduate student in Georgia Tech’s MS Analytics
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.