Data Structures and Algorithms Using Python
- 9h 52m
- Rance D. Necaise
- John Wiley & Sons (US)
- 2011
And now for something completely different…
This book is designed for a data structures and algorithms course that uses Python. A key objective is to provide a "back to basics" approach to learning data structures and algorithms without overwhelming the reader with all of the object-oriented programming terminology and concepts. To provide flexibility in topic coverage for a wide variety of courses, the author focuses on data structures and algorithms, while designing the examples to allow the introduction of object-oriented programming if so desired. The book also introduces the concept of algorithm analysis and explores the efficiency of algorithms and data structures throughout the text.
Hallmark Features
- Provides complete coverage of abstraction and the basic data structures and algorithms using a "back to basics" approach.
- Python (version 3) used to design and implement classes for abstract data types and programs and algorithms.
- Flexible organziation allows coverage of class inheritance as needed or desired.
- Introduces students to the basic array structure and the fundamentals of implementing and using multi-dimensional arrays.
- The underlying mechanism of many of Python's built-in data structures and constructs are explored in order to expose the "magic" and to evaluate their efficiency.
- Sample applications of various chapter topics are presented throughout the text to help engage students.
- A number of ADTs and applications are presented as threads throughout the text (i.e. the Set, Bag, Matrix, Sparse Matrix, and Map ADTs.) This allows for multiple implementations as new data structures are introduced, which provides the opportunity to reinforce the abstraction concept and for studying algorithm efficiency.
In this Book
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Abstract Data Types
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Arrays
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Sets and Maps
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Algorithm Analysis
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Searching and Sorting
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Linked Structures
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Stacks
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Queues
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Advanced Linked Lists
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Recursion
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Hash Tables
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Advanced Sorting
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Binary Trees
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Search Trees
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Bibliography
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