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Mastering Python Design Patterns

You're reading from   Mastering Python Design Patterns Start learning Python programming to a better standard by mastering the art of Python design patterns

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783989324
Length 212 pages
Edition 1st Edition
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Author (1):
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Sakis Kasampalis Sakis Kasampalis
Author Profile Icon Sakis Kasampalis
Sakis Kasampalis
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Table of Contents (18) Chapters Close

Preface 1. The Factory Pattern 2. The Builder Pattern FREE CHAPTER 3. The Prototype Pattern 4. The Adapter Pattern 5. The Decorator Pattern 6. The Facade Pattern 7. The Flyweight Pattern 8. The Model-View-Controller Pattern 9. The Proxy Pattern 10. The Chain of Responsibility Pattern 11. The Command Pattern 12. The Interpreter Pattern 13. The Observer Pattern 14. The State Pattern 15. The Strategy Pattern 16. The Template Pattern Index

Use cases

Strategy is a very generic design pattern with many use cases. In general, whenever we want to be able to apply different algorithms dynamically and transparently, Strategy is the way to go. By different algorithms, I mean different implementations of the same algorithm. This means that the result should be exactly the same, but each implementation has a different performance and code complexity (as an example, think of sequential search versus binary search).

We have already seen how Python and Java use the Strategy pattern to support different sorting algorithms. However, Strategy is not limited to sorting. It can also be used to create all kinds of different resource filters (authentication, logging, data compression, encryption, and so forth) [j.mp/javaxfilter].

Another usage of the Strategy pattern is to create different formatting representations, either to achieve portability (for example, line-breaking differences between platforms) or dynamically change the representation...

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