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Mastering Object-Oriented Python

You're reading from   Mastering Object-Oriented Python Build powerful applications with reusable code using OOP design patterns and Python 3.7

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Product type Paperback
Published in Jun 2019
Publisher Packt
ISBN-13 9781789531367
Length 770 pages
Edition 2nd Edition
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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 (25) Chapters Close

Preface 1. Section 1: Tighter Integration Via Special Methods FREE CHAPTER
2. Preliminaries, Tools, and Techniques 3. The __init__() Method 4. Integrating Seamlessly - Basic Special Methods 5. Attribute Access, Properties, and Descriptors 6. The ABCs of Consistent Design 7. Using Callables and Contexts 8. Creating Containers and Collections 9. Creating Numbers 10. Decorators and Mixins - Cross-Cutting Aspects 11. Section 2: Object Serialization and Persistence
12. Serializing and Saving - JSON, YAML, Pickle, CSV, and XML 13. Storing and Retrieving Objects via Shelve 14. Storing and Retrieving Objects via SQLite 15. Transmitting and Sharing Objects 16. Configuration Files and Persistence 17. Section 3: Object-Oriented Testing and Debugging
18. Design Principles and Patterns 19. The Logging and Warning Modules 20. Designing for Testability 21. Coping with the Command Line 22. Module and Package Design 23. Quality and Documentation 24. Other Books You May Enjoy

Designing callables

There are two easy and commonly-used ways to create callable objects in Python, which are as follows:

  • By using the def statement to create a function.
  • By creating an instance of a class that implements the _call()_ method. This can be done by using collections.abc.Callable as its base class.

Beyond these two, we can also assign a lambda form to a variable. A lambda is a small, anonymous function that consists of exactly one expression. We'd rather not emphasize saving lambdas in a variable, as this leads to the confusing situation where we have a function-like callable that's not defined with a def statement.

The following is a simple callable object, pow1, created from a class:

from typing import Callable
IntExp = Callable[[int, int], int]
class Power1:
def __call__(self, x: int, n: int) -> int:
p = 1
for i in range(n):
...
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