Softcover

ISBN 10: 0136150314 ISBN 13: 9780136150312

Publisher: Prentice Hall, 2007

This book presents a balanced and flexible approach to the incorporation of object-oriented principles in introductory courses using Python. Familiarizes readers with the terminology of object-oriented programming, the concept of an object's underlying state information, and its menu of available behaviors. Includes an exclusive, easy-to-use custom graphics library that helps readers grasp both basic and more advanced concepts. Lays the groundwork for transition to other languages such as Java and C++. For those interested in learning more about object-oriented programming using Python. 

From the Back Cover:

Object-Oriented Programming in PYTHON

Goldwasser

Letscher

 

Python's simple syntax, consistent semantics, and wide popularity make it an exceptionally attractive instructional language for new programmers. This text embraces Python's object-oriented nature, presenting a balanced and flexible approach to mastering object-oriented principles, and building a solid framework for advanced programming in Python and other languages.

 

Drawing on their highly successful CS1 course at Saint Louis University, the authors begin with core concepts every programmer must master, including data types, objects, control structures, I/O, user-defined classes, inheritance, and good software development practices. Next, students gain far deeper mastery, learning crucial techniques ranging from recursion to data structures. The authors conclude by introducing event-driven and network programming - two "advanced" topics that become surprisingly approachable with Python.

• Strong fundamentals coverage: Helps readers achieve immediate success, while building a strong foundation for further study
• Flexible organization: Enables instructors to reorder, emphasize, or deemphasize topics as needed
• Provides early "object awareness" and helps students master key object-oriented principles naturally and gradually
• Presents real-world case studies from domains such as animation, biology, physics, and the Internet
• Includes an exclusive, simple graphics library that helps students grasp basic concepts and explore more advanced topics such as transformations and layers
• Contains a convenient guide for transitioning from Python to Java™ or C++

About the Authors

 

Dr. Michael H. Goldwasser is Associate Professor and Dr. David Letscher is Assistant Professor at Saint Louis University. Dr. Goldwasser was previously on the Faculty at Loyola University Chicago where he was Undergraduate Program Director for Computer Science. He has also taught courses at Colorado College, Princeton University, and Stanford University. He holds a Ph.D. in Computer Science from Stanford University. Dr. Letscher served as Assistant Professor at Oklahoma State University, Visting Researcher at American Institute of Mathematics, Assistant Professor at University of California, San Diego, and Visiting Research Fellow at the University of Melbourne. He holds a Ph.D. in Mathematics from the University of Michigan.

About the Author:

Drs. Goldwasser and Letscher are on the Faculty in the Department of Mathematics and Computer Science at Saint Louis University.  Both are active in teaching the introductory computer science course for which this book was designed.  They have described the development of this material at the premier national and international conferences on Computer Science education. Dr. Goldwasser received his Ph.D. in Computer Science at Stanford University in 1997, and has taught courses at Stanford University, Princeton University, Loyola University of Chicago, and Colorado College before joining Saint Louis University. His research interests center around the design and analysis of algorithms. Dr. Letscher received his Ph.D. in Mathematics from the University of Michigan in 1997, and has taught courses in mathematics and computer science at the University of California San Diego, Oklahoma State University, and the American Institute of Mathematics before joining Saint Louis University. His primary research interests center around computational topology.