The Practice of Computing Using Python

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Addison-Wesley, 2011 - Computers - 670 pages
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A problem-solving approach to programming with Python.The Practice of Computing using Python, first editionis intended to teach problem solving within the context of CS1 to both majors and non-majors using Python as a vehicle. As such the authors cover general concepts like hardware, complexity, and software engineering as well as general concepts of programming using the Python language. In the end, if a student takes no other programming course than one such as this, they can be productive programmers who understand general principles of computation and can produce useful, meaningful results in their respective fields of study. The Study of Computer Science; Starting to Program–Beginnings, Control, Algorithms and Program Development; Organizing: Data Structures and Functions–Working with Strings, Functions–QuickStart, Lists and Tuples, Dictionaries and Sets, Files; Classes: Making Your Own Data Structures & Algorithms–Program Development with Classes; Becoming a Better Programmer–Exceptions and Exception Handling, Testing, Recursion-another control mechanism, Getting and Using Python, Simple Drawing with Turtle Graphics, Plotting and Numeric Tools, Python 3.0. Anyone interested in learning Python or computer programming skills in general.

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Without doubt, the worst textbook I have ever had to use. It has made my first course in computer science frustrating, and I am convinced I will not be ready for the next course. Any instructor who uses this book is ripping-off their students. Here's just one example: Files. The author has the reader/student doing this with files and that with files and on and on. That's in the first seven chapters. Where does he even DEFINE what a file is??? Chapter 9. Using this textbook has made this semester of computer science a complete waste of time AND money. Fortunately, for those students who have yet to take this course, the instructor is dumping this text. As for me, I have always excelled academically. However, I do not believe it is possible or realistic for me to build any sort of usable knowledge base on what I have learned using this text. I will definitely be changing my major. Thanks Punch and Enbody. In fairness, though, I have read ONE glowing review concerning this textbook. It was written by someone who is an instructor working at the same school as the author.  

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About the author (2011)

Richard Enbody is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University. Since joining the faculty in 1987, he has served as Acting Chair of the Department, Associate Chair, and as Director of the Computer Engineering Undergraduate Program.

Enbody received his B.A. in Mathematics from Carleton College in 1976, and spent six years teaching high school mathematics in Vermont and New Hampshire. He earned his Ph.D. in Computer Science from the University of Minnesota.

Richard's research interests are in computer security, computer architecture, web-based distance education and parallel processing, especially the application of parallel processing to computational science problems. He has two patents pending on hardware buffer-overflow protection which will prevent most computer worms and viruses.

In 1998 Richard pioneered a CS1 course (first course in Computer Science) over the World Wide Web using RealVideo synchronized with PowerPoint. Students from as far away as Russia and Korea enrolled in the course.

When not teaching, Richard plays hockey, squash, canoes, backpacks, as well as a host of family activities.

Bill Punch is an Associate Professor in the Department of Computer Science at Michigan State University as well as the director of Michigan State's High Performance Computing Center.

Punch is co-director of the Genetic Algorithms Research and Applications Group or GARAGe. His main interests are genetic algorithms and genetic programming, including theoretical issues (parallel GA/GP) and application issues (design, layout, scheduling, etc.). He also has conducted active research in data mining, focusing on the use of ontologies such as WordNet and Wikipedia for text search.

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