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Data Structures and Algorithms with Python

Author(s):
Publisher:

Springer

Pages: 363
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Paperback - 9783319130712

22 January 2015

$59.99

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Ebook - 9783319130729

12 January 2015

$44.99

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This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms...

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This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language background.

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Includes broad coverage of both introductory and advanced data structures topics, supported by examples

Guides the reader through the concepts of computational complexity, from the basics to amortized complexity

Makes learning fun, using the development of graphical user interface programs to illustrate concepts

1: Python Programming 101
2: Computational Complexity
3: Recursion
Sequences
4: Sets and Maps
5: Trees
6: Graphs
7: Membership Structures
8: Heaps
9: Balanced Binary Search Trees
10: B-Trees
11: Heuristic Search
Appendix A: Integer Operators
Appendix B: Float Operators
Appendix C: String Operators and Methods
Appendix D: List Operators and Methods
Appendix E: Dictionary Operators and Methods
Appendix F: Turtle Methods
Appendix G: TurtleScreen Methods
Appendix H: Complete Programs.

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Dr. Kent D. Lee is Professor of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer textbook Python Programming Fundamentals and the forthcoming Foundations of Programming Languages.

Dr. Steve Hubbard is Professor of Mathematics and Computer Science at Luther College.

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Dr. Kent D. Lee is Professor of Computer Science at Luther College, Decorah, Iowa, USA. He is the author of the successful Springer textbook Python Programming Fundamentals and the forthcoming Foundations of Programming Languages.

Dr. Steve Hubbard is Professor of Mathematics and Computer Science at Luther College.

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