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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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Toc

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

A software example

Python's sorted() and list.sort() functions are examples of the Strategy pattern. Both functions accept a named parameter key, which is basically the name of the function that implements a sorting Strategy [Eckel08, page 202].

The following example (the code is in the langs.py file) shows how two different strategies can be used to sort programming languages in the following ways:

  • Alphabetically
  • Based on their popularity (using the TIOBE index [j.mp/tiobe14])

A namedtuple programming language [j.mp/namedtuple] is used to keep the statistics of the programming languages. A named tuple is an easy-to-create, lightweight, immutable object type. It is compatible with a normal tuple but it can also be treated as an object (can be called by name, using the usual class notation). A named tuple can be used [j.mp/sonamed]:

  • Instead of a class when we want to focus on immutability
  • Instead of a tuple, when it makes sense to use the object notation to create more readable code

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