Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Python Design Patterns

You're reading from   Mastering Python Design Patterns Craft essential Python patterns by following core design principles

Arrow left icon
Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781837639618
Length 296 pages
Edition 3rd Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Kamon Ayeva Kamon Ayeva
Author Profile Icon Kamon Ayeva
Kamon Ayeva
Sakis Kasampalis Sakis Kasampalis
Author Profile Icon Sakis Kasampalis
Sakis Kasampalis
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Start with Principles FREE CHAPTER
2. Chapter 1: Foundational Design Principles 3. Chapter 2: SOLID Principles 4. Part 2: From the Gang of Four
5. Chapter 3: Creational Design Patterns 6. Chapter 4: Structural Design Patterns 7. Chapter 5: Behavioral Design Patterns 8. Part 3: Beyond the Gang of Four
9. Chapter 6: Architectural Design Patterns 10. Chapter 7: Concurrency and Asynchronous Patterns 11. Chapter 8: Performance Patterns 12. Chapter 9: Distributed Systems Patterns 13. Chapter 10: Patterns for Testing 14. Chapter 11: Python Anti-Patterns 15. Index 16. Other Books You May Enjoy

The Strategy pattern

Several solutions often exist for the same problem. Consider the task of sorting, which involves arranging the elements of a list in a particular sequence. For example, a variety of sorting algorithms are available for the task of sorting. Generally, no single algorithm outperforms all others in every situation.

Selecting a sorting algorithm depends on various factors, tailored to the specifics of each case. Some key considerations include the following:

  • The number of elements to be sorted, known as the input size: While most sorting algorithms perform adequately with a small input size, only a select few maintain efficiency with larger datasets.
  • The best/average/worst time complexity of the algorithm: Time complexity is (roughly) the amount of time the algorithm takes to complete, excluding coefficients and lower-order terms. This is often the most usual criterion to pick an algorithm, although it is not always sufficient.
  • The space complexity...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime