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Mastering Python

Mastering Python

By : Rick Hattem
4 (11)
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Mastering Python

Mastering Python

4 (11)
By: Rick Hattem

Overview of this book

Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward. This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.
Table of Contents (17 chapters)
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6
6. Generators and Coroutines – Infinity, One Step at a Time
16
Index

Order of operations when instantiating classes


The order of operations during class instantiation is very important to keep in mind when debugging issues with dynamically created and/or modified classes. The instantiation of a class happens in the following order.

Finding the metaclass

The metaclass comes from either the explicitly given metaclass on the class or bases, or by using the default type metaclass.

For every class, the class itself and the bases, the first matching of the following will be used:

  • Explicitly given metaclass

  • Explicit metaclass from bases

  • type()

    Note

    Note that if no metaclass is found that is a subtype of all the candidate metaclasses, a TypeError will be raised. This scenario is not that likely to occur but certainly a possibility when using multiple inheritance/mixins with metaclasses.

Preparing the namespace

The class namespace is prepared through the metaclass selected previously. If the metaclass has a __prepare__ method, it will be called namespace = metaclass.__prepare__...

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Mastering Python
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