Object-Oriented Programming in Python

About

Features

• Strong fundamentals – Teaches readers how to program in a style that leads them to immediate success, while also gaining a deeper understanding that serves as the foundation for further study.

• Progressive lesson plans – Build upon one another with consistency. EX. A television analogy is introduced as pure design in Ch. 1, then revisited as a tangible class implementation (Ch. 6) and as a base for inheritance (Ch. 9).

• Flexible organization – Allows instructors to reorder or emphasize and deemphasize topics as needed.

• Natural development of object-oriented principles – Familiarizes students with the terminology of object-oriented programming, the concept of an object's underlying state information, and its menu of available behaviors.

• Cases studies with concrete applications – Draw on a wide variety of domains such as animation, puzzles, biology, and math to showcase new techniques and demonstrate the use of computer science in the real world.

• Support for graphics – Includes an exclusive, easy-to-use custom graphics library that helps students grasp basic concepts, while also supporting more advanced explorations into themes such as transformations, double buffering, and event-driven programming.

• Transition to Java or C++ – Lays the groundwork for students’ transition to other languages later in the curriculum, most prominently Java and C++.

• Advanced course material – Provides coverage of more complex topics, including recursion, data structures and algorithms, event-driven programming, and network programming.

• Supportive pedagogy – Displays all source code prominently within boxes, and includes "Word of Warning" features to highlight issues that commonly trip up beginning programmers. "For the Guru" boxes present deeper understanding in context for advanced students.

• Extensive end matter in each chapter – Includes a list of key points from the chapter, glossary of newly introduced terms, clearly marked Practice Problems with solutions, and extensive Exercises and Projects.

Description

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.

Sample Content

Table of Contents

Updates

Submit Errata