Python Algorithms: Mastering Basic Algorithms in the Python Language / Edition 2

Python Algorithms: Mastering Basic Algorithms in the Python Language / Edition 2

by Magnus Lie Hetland
ISBN-10:
148420056X
ISBN-13:
9781484200568
Pub. Date:
09/04/2014
Publisher:
Apress
ISBN-10:
148420056X
ISBN-13:
9781484200568
Pub. Date:
09/04/2014
Publisher:
Apress
Python Algorithms: Mastering Basic Algorithms in the Python Language / Edition 2

Python Algorithms: Mastering Basic Algorithms in the Python Language / Edition 2

by Magnus Lie Hetland
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Overview

Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.

The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others.


Product Details

ISBN-13: 9781484200568
Publisher: Apress
Publication date: 09/04/2014
Edition description: 2nd ed.
Pages: 320
Product dimensions: 7.01(w) x 10.00(h) x 0.03(d)

About the Author

Magnus Lie Hetland is an experienced Python programmer, having used the language since the late 1990s. He is also an associate professor of algorithms at the Norwegian University of Science and Technology, having taught algorithms for the better part of a decade. Hetland is the author of Practical Python and Beginning Python, first and second editions, as well as several scientific papers.

Table of Contents

1. Introduction

2. The Basics

3. Counting 101

4. Induction and Recursion … and Reduction

5. Traversal: The Skeleton Key of Algorithmics

6. Divide, Combine, and Conquer

7. Greed Is Good? Prove It!

8. Tangled Dependencies and Memoization

9. From A to B with Edsger and Friends

10. Matchings, Cuts, and Flows

11. Hard Problems and (Limited) Sloppiness

12. Pedal to the Metal: Accelerating Python

13. List of Problems and Algorithms

14. Graph Terminology!

15. Hints for Exercises

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