Data structures and algorithms with Python [electronic resource] / Kent D. Lee, Steve Hubbard.
2015
QA76.9.D35 L44 2015eb
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Online Access
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Unlimited
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Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Details
Title
Data structures and algorithms with Python [electronic resource] / Kent D. Lee, Steve Hubbard.
ISBN
9783319130729 electronic book
3319130722 electronic book
9783319130712
3319130722 electronic book
9783319130712
Published
Cham : Springer, 2015.
Language
English
Description
1 online resource (xv, 363 pages) : illustrations (some color).
Item Number
10.1007/978-3-319-13072-9 doi
Call Number
QA76.9.D35 L44 2015eb
Dewey Decimal Classification
005.7/3
Summary
This clearly structured and easy to read 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 motivating 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. The text assumes some basic experience in computer programming and familiarity in an object-oriented language, but not necessarily with Python. Topics and 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 coming from a different language background Reviews the use of hashing in sets and maps, along with an examination of binary search trees and tree traversals, and material on depth first search of graphs Discusses topics suitable for an advanced course, such as membership structures, heaps, balanced binary search trees, B-trees and heuristic search Students of computer science will find this clear and concise textbook to be invaluable for undergraduate courses on data structures and algorithms, at both introductory and advanced levels. The book is also suitable as a refresher guide for computer programmers starting new jobs working with Python.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed February 2, 2015).
Added Author
Hubbard, Steve, author.
Series
Undergraduate topics in computer science.
Available in Other Form
Print version: 9783319130712
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Online Access
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Table of Contents
Python Programming 101
Computational Complexity
Recursion
Sequences
Sets and Maps
Trees
Graphs
Membership Structures
Heaps
Balanced Binary Search Trees
B-Trees
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.
Computational Complexity
Recursion
Sequences
Sets and Maps
Trees
Graphs
Membership Structures
Heaps
Balanced Binary Search Trees
B-Trees
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.