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Python Data Structures and Algorithms

You're reading from  Python Data Structures and Algorithms

Product type Book
Published in May 2017
Publisher Packt
ISBN-13 9781786467355
Pages 310 pages
Edition 1st Edition
Languages
Author (1):
Benjamin Baka Benjamin Baka
Profile icon Benjamin Baka
Toc

Table of Contents (20) Chapters close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Python Objects, Types, and Expressions 2. Python Data Types and Structures 3. Principles of Algorithm Design 4. Lists and Pointer Structures 5. Stacks and Queues 6. Trees 7. Hashing and Symbol Tables 8. Graphs and Other Algorithms 9. Searching 10. Sorting 11. Selection Algorithms 12. Design Techniques and Strategies 13. Implementations, Applications, and Tools

Algorithm design paradigms


In general, we can discern three broad approaches to algorithm design. They are:

  • Divide and conquer
  • Greedy algorithms
  • Dynamic programming

As the name suggests, the divide and conquer paradigm involves breaking a problem into smaller sub problems, and then in some way combining the results to obtain a global solution. This is a very common and natural problem solving technique, and is, arguably, the most commonly used approach to algorithm design.

Greedy algorithms often involve optimization and combinatorial problems; the classic example is applying it to the traveling salesperson problem, where a greedy approach always chooses the closest destination first. This shortest path strategy involves finding the best solution to a local problem in the hope that this will lead to a global solution.

The dynamic programming approach is useful when our sub problems overlap. This is different from divide and conquer. Rather than break our problem into independent sub problems,...

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