AUTHORS

Dr. John Canning is an engineer, computer scientist, and researcher. He earned an S.B. degree in electrical engineering from the Massachusetts Institute of Technology and a Ph.D. in Computer Science from the University of Maryland at College Park. His varied professions include being a professor of computer science, a researcher and software engineer in industry, and a company vice president. He now is president of Shakumant Software.

Alan Broder is clinical professor and chair of the Department of Computer Science at Stern College for Women of Yeshiva University in New York City. He teaches introductory and advanced courses in Python programming, data structures, and data science. Before joining Stern College, he was a software engineer, designing and building large-scale data analysis systems. He founded and led White Oak Technologies, Inc. as its CEO, and later served as the chairman and fellow of its successor company, Novetta, in Fairfax, Virginia.

Robert Lafore has degrees in Electrical Engineering and Mathematics, has worked as a systems analyst for the Lawrence Berkeley Laboratory, founded his own software company, and is a best-selling writer in the field of computer programming. Some of his titles are Object-Oriented Programming in C++ and Data Structures and Algorithms in Java.

SUMMARY

This practical introduction to data structures and algorithms can help every programmer who wants to write more efficient software. Building on Robert Lafore's legendary Java-based guide, this book helps students understand exactly how data structures and algorithms operate. You'll learn how to efficiently apply them with the enormously popular Python language and scale your code to handle today's big data challenges.

Throughout, the authors focus on real-world examples, communicate key ideas with intuitive, interactive visualizations, and limit complexity and math to what you need to improve performance. Step-by-step, they introduce arrays, sorting, stacks, queues, linked lists, recursion, binary trees, 2-3-4 trees, hash tables, spatial data structures, graphs, and more. Their code examples and illustrations are so clear, you can understand them even if you're a near-beginner, or your experience is with other procedural or object-oriented languages.

Build core computer science skills that take you beyond merely “writing code”
Learn how data structures make programs (and programmers) more efficient
See how data organization and algorithms affect how much you can do with today's, and tomorrow's, computing resources
Develop data structure implementation skills you can use in any language
Choose the best data structure(s) and algorithms for each programming problem—and recognize which ones to avoid

Data Structures & Algorithms in Python is packed with examples, review questions, individual and team exercises, thought experiments, and longer programming projects. It's ideal for both self-study and classroom settings, and either as a primary text or as a complement to a more formal presentation.

Instructor Resources: Lecture slides and project solutions for the first few chapters are available on Pearson's Instructor Resource Center. For questions and additional ancillaries, such as complete lecture slides and programming project solutions, please contact the authors at their website, https://datastructures.live.

Two earlier editions of this book were published in 1998 and 2002 for the Java programming language. John Canning and Alan Broder developed this version using Python due to its popularity in education, commercial, and non-commercial software development. Canning and Broder expanded its coverage of data structures and updated many of its examples.