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Mastering Python 2E

You're reading from   Mastering Python 2E Write powerful and efficient code using the full range of Python's capabilities

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Product type Paperback
Published in May 2022
Last Updated in May 2022
Publisher Packt
ISBN-13 9781800207721
Length 710 pages
Edition 2nd Edition
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Author (1):
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Rick Hattem Rick Hattem
Author Profile Icon Rick Hattem
Rick Hattem
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Table of Contents (21) Chapters Close

Preface 1. Getting Started – One Environment per Project FREE CHAPTER 2. Interactive Python Interpreters 3. Pythonic Syntax and Common Pitfalls 4. Pythonic Design Patterns 5. Functional Programming – Readability Versus Brevity 6. Decorators – Enabling Code Reuse by Decorating 7. Generators and Coroutines – Infinity, One Step at a Time 8. Metaclasses – Making Classes (Not Instances) Smarter 9. Documentation – How to Use Sphinx and reStructuredText 10. Testing and Logging – Preparing for Bugs 11. Debugging – Solving the Bugs 12. Performance – Tracking and Reducing Your Memory and CPU Usage 13. asyncio – Multithreading without Threads 14. Multiprocessing – When a Single CPU Core Is Not Enough 15. Scientific Python and Plotting 16. Artificial Intelligence 17. Extensions in C/C++, System Calls, and C/C++ Libraries 18. Packaging – Creating Your Own Libraries or Applications 19. Other Books You May Enjoy
20. Index

Dynamically creating classes

Metaclasses are the factories that create new classes in Python. In fact, even though you may not be aware of it, Python will always execute the type metaclass whenever you create a class.

A few common examples where metaclasses are used internally are abc (abstract base classes), dataclasses, and the Django framework, which heavily relies on metaclasses for the Model class.

When creating classes in a procedural way, the type metaclass is used as a function that takes three arguments: name, bases, and dict.name will become the __name__ attribute, bases is the list of inherited base classes and will be stored in __bases__, and dict is the namespace dictionary that contains all variables and will be stored in __dict__.

It should be noted that the type() function has another use as well. Given the arguments documented above, it will create a class with those specifications. Given a single argument with the instance of a class (for example, type...

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