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Mastering Object-oriented Python

You're reading from   Mastering Object-oriented Python If you want to master object-oriented Python programming this book is a must-have. With 750 code samples and a relaxed tutorial, it's a seamless route to programming Python.

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Product type Paperback
Published in Apr 2014
Publisher Packt
ISBN-13 9781783280971
Length 634 pages
Edition Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (26) Chapters Close

Mastering Object-oriented Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Some Preliminaries
1. The __init__() Method FREE CHAPTER 2. Integrating Seamlessly with Python Basic Special Methods 3. Attribute Access, Properties, and Descriptors 4. The ABCs of Consistent Design 5. Using Callables and Contexts 6. Creating Containers and Collections 7. Creating Numbers 8. Decorators and Mixins – Cross-cutting Aspects 9. Serializing and Saving – JSON, YAML, Pickle, CSV, and XML 10. Storing and Retrieving Objects via Shelve 11. Storing and Retrieving Objects via SQLite 12. Transmitting and Sharing Objects 13. Configuration Files and Persistence 14. The Logging and Warning Modules 15. Designing for Testability 16. Coping With the Command Line 17. The Module and Package Design 18. Quality and Documentation Index

Improving performance


We'll look at two performance tweaks for the Power3 class.

First, a better algorithm. Then, a better algorithm combined with memoization, which involves a cache; therefore, the function becomes stateful. This is where callable objects shine.

The first modification is to use a Divide and Conquer design strategy. The previous version chopped into n steps; the loop carried out n individual multiplication operations. If we can find a way to split the problem into two equal portions, the problem decomposes into steps. Given pow1(2,1024), the Power1 callable performs the calculation 1024 multiplications by 2. We can optimize this down to 10 multiplications, a significant speedup.

Rather than simply multiplying by a fixed value, we'll use the "fast exponentiation" algorithm. It uses three essential rules for computing , as follows:

  • If :, the result is simply 1.
  • If n is odd and , the result is . This involves a recursive computation of . This still does a multiplication but...
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