


Calling Parent Class init with Multiple Inheritance: The Right Approach
Multiple inheritance can be a useful technique in Python, but it can also introduce complexities when calling parent class constructors. This article investigates the correct method to invoke both parent class constructors in a child class, addressing potential issues and the need to consider the design of the inherited classes.
The Importance of Understanding Base Class Design
The primary factor to consider when calling parent class constructors is whether the base classes are designed for multiple inheritance. Three possible scenarios exist:
1. Unrelated Parent Classes:
If the base classes are standalone and not intended for multiple inheritance, they may not call super().__init__(). In this case, the child class must explicitly call each parent constructor manually, either directly or using super.
2. Mixin Class:
A mixin is designed to be used with multiple inheritance and automatically calls the subsequent parent constructor. Calling super().__init__() in the child class is sufficient to invoke all parent constructors.
3. Cooperative Parent Classes:
Cooperative classes also accept unused arguments and forward them to the next base class. Like mixins, they allow the child class to call super().__init__() and invoke all parent constructors.
Choosing the Right Approach
The appropriate method for calling parent class constructors depends on the design of the base classes:
- For unrelated parents, explicitly call each constructor.
- For mixins, call super().__init__() with all arguments.
- For cooperative parents, call super().__init__() with keyword arguments.
Conclusion
Understanding the design of inherited classes is crucial when accessing parent class constructors in multiple inheritance scenarios. By considering the specific class structure and following the appropriate approach, developers can ensure proper initialization and avoid potential issues.
The above is the detailed content of How Should I Call Parent Class `__init__` Methods with Multiple Inheritance in Python?. For more information, please follow other related articles on the PHP Chinese website!

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

DVWA
Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

SublimeText3 Linux new version
SublimeText3 Linux latest version
