Home Backend Development Python Tutorial How to implement multiple inheritance in python

How to implement multiple inheritance in python

Dec 11, 2023 pm 02:04 PM
python multiple inheritance

In Python, multiple inheritance can be achieved by defining a class by using multiple parent classes separated by commas. Detailed introduction: When a class inherits multiple parent classes, it will inherit the properties and methods of all parent classes. This means that subclasses can access and use properties and methods defined in the parent class.

How to implement multiple inheritance in python

The operating system for this tutorial: Windows 10 system, Python version 3.11.4, DELL G3 computer.

Multiple inheritance is a mechanism for implementing relationships between classes in Python, allowing a class to inherit properties and methods from multiple parent classes. In Python, multiple inheritance can be implemented by defining a class with multiple parent classes separated by commas. Multiple inheritance can improve code reusability and flexibility to a certain extent, but you also need to pay attention to some potential problems, such as method resolution order and diamond inheritance issues.

The basic syntax for implementing multiple inheritance in Python is as follows:

class Child(Parent1, Parent2, ...):
# 子类的定义
Copy after login

In the above code, Child is the name of the subclass, Parent1, Parent2, etc. are the names of the parent class, separated by commas Separate multiple parent classes.

Next, I will introduce several aspects of multiple inheritance in detail:

1. Inherit the properties and methods of multiple parent classes

When When a class inherits from multiple parent classes, it will inherit the properties and methods of all parent classes. This means that subclasses can access and use properties and methods defined in the parent class.

For example, suppose we have two parent classes, Parent1 and Parent2, which define some properties and methods respectively. We can create a subclass Child, inherits the properties and methods of these two parent classes, as shown below:

class Parent1:
def method1(self):
print("Parent1 method1")
class Parent2:
def method2(self):
print("Parent2 method2")
class Child(Parent1, Parent2):
pass
Copy after login

In the above code, the `Child` class inherits the two parent classes `Parent1` and `Parent2`. Therefore, the `Child` class can call `Parent1`'s `method1()` method and `Parent2`’s `method2()` method.

child = Child()
child.method1() # 输出: Parent1 method1
child.method2() # 输出: Parent2 method2
通过创建 `Child` 类的实例 `child`,我们可以调用继承的方法。
Copy after login

2. Method resolution order (MRO)

In multiple inheritance, if there are attributes or methods with the same name in multiple parent classes, Python will follow a specific Definition of the sequential search method. This order is called method resolution order (Method Resolution Order (MRO).

MRO determines the search order for methods in multiple inheritance classes. In the Python 2.x version, the order of MRO is calculated through depth-first search (DFS) and left-first approach. And in Python In version 3.x, the C3 linearization algorithm is used by default to calculate MRO.

You can view the method resolution order by calling the mro() method of the class. In method resolution order, each class's parent class is listed before it, maintaining the original order.

For example, consider the following example:

class Parent1:
def method(self):
print("Parent1 method")
class Parent2:
def method(self):
print("Parent2 method")
class Child(Parent1, Parent2):
pass
print(Child.mro()) # 输出: [, , , ]
Copy after login

In the above example, the `Child` class inherits the `method` methods of the two parent classes `Parent1` and `Parent2`. Since `Parent1` is in `Parent2` in front, so when calling `child.method()`, the method in the `Parent1` class is actually called.

Note that in multiple inheritance, the calculation of MRO is based on the inheritance order of classes. If you change the order of the parent class, the priority when calling properties or methods with the same name will also change.

3. Diamond Inheritance Problem

Multiple inheritance may cause a problem, namely Diamond Inheritance Problem Problem). The diamond inheritance problem occurs when a subclass inherits from two parent classes, and the two parent classes inherit from the same parent class.

Consider the following example:

class Grandparent:
def method(self):
print("Grandparent method")
class Parent1(Grandparent):
def method(self):
print("Parent1 method")
class Parent2(Grandparent):
def method(self):
print("Parent2 method")
class Child(Parent1, Parent2):
pass
child = Child()
child.method() # 输出: Parent1 method
Copy after login

In the above example, `Grandparent` is the top-level parent class, and `Parent1` and `Parent2` both inherit `Grandparent`. Then, the `Child` class inherits `Parent1` and `Parent2`, and both parent classes have a method named `method` Methods.

When calling `child.method()`, what is actually called is the `method` in the `Parent1` class method. This is because in multiple inheritance, Python searches for methods in the order of the parent class, and `Parent1` comes before `Parent2`.

If you wish to avoid or resolve conflicts in diamond inheritance, you can use the `super()` function to call methods of a specific parent class, or override methods to provide a custom implementation.

The above is some basic information and precautions about multiple inheritance. Multiple inheritance is a powerful feature, but it needs to be used with caution to avoid potential problems.

The above is the detailed content of How to implement multiple inheritance in python. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
Will R.E.P.O. Have Crossplay?
1 months ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

PHP and Python: Code Examples and Comparison PHP and Python: Code Examples and Comparison Apr 15, 2025 am 12:07 AM

PHP and Python have their own advantages and disadvantages, and the choice depends on project needs and personal preferences. 1.PHP is suitable for rapid development and maintenance of large-scale web applications. 2. Python dominates the field of data science and machine learning.

Python vs. JavaScript: Community, Libraries, and Resources Python vs. JavaScript: Community, Libraries, and Resources Apr 15, 2025 am 12:16 AM

Python and JavaScript have their own advantages and disadvantages in terms of community, libraries and resources. 1) The Python community is friendly and suitable for beginners, but the front-end development resources are not as rich as JavaScript. 2) Python is powerful in data science and machine learning libraries, while JavaScript is better in front-end development libraries and frameworks. 3) Both have rich learning resources, but Python is suitable for starting with official documents, while JavaScript is better with MDNWebDocs. The choice should be based on project needs and personal interests.

How is the GPU support for PyTorch on CentOS How is the GPU support for PyTorch on CentOS Apr 14, 2025 pm 06:48 PM

Enable PyTorch GPU acceleration on CentOS system requires the installation of CUDA, cuDNN and GPU versions of PyTorch. The following steps will guide you through the process: CUDA and cuDNN installation determine CUDA version compatibility: Use the nvidia-smi command to view the CUDA version supported by your NVIDIA graphics card. For example, your MX450 graphics card may support CUDA11.1 or higher. Download and install CUDAToolkit: Visit the official website of NVIDIACUDAToolkit and download and install the corresponding version according to the highest CUDA version supported by your graphics card. Install cuDNN library:

Detailed explanation of docker principle Detailed explanation of docker principle Apr 14, 2025 pm 11:57 PM

Docker uses Linux kernel features to provide an efficient and isolated application running environment. Its working principle is as follows: 1. The mirror is used as a read-only template, which contains everything you need to run the application; 2. The Union File System (UnionFS) stacks multiple file systems, only storing the differences, saving space and speeding up; 3. The daemon manages the mirrors and containers, and the client uses them for interaction; 4. Namespaces and cgroups implement container isolation and resource limitations; 5. Multiple network modes support container interconnection. Only by understanding these core concepts can you better utilize Docker.

MiniOpen Centos compatibility MiniOpen Centos compatibility Apr 14, 2025 pm 05:45 PM

MinIO Object Storage: High-performance deployment under CentOS system MinIO is a high-performance, distributed object storage system developed based on the Go language, compatible with AmazonS3. It supports a variety of client languages, including Java, Python, JavaScript, and Go. This article will briefly introduce the installation and compatibility of MinIO on CentOS systems. CentOS version compatibility MinIO has been verified on multiple CentOS versions, including but not limited to: CentOS7.9: Provides a complete installation guide covering cluster configuration, environment preparation, configuration file settings, disk partitioning, and MinI

How to operate distributed training of PyTorch on CentOS How to operate distributed training of PyTorch on CentOS Apr 14, 2025 pm 06:36 PM

PyTorch distributed training on CentOS system requires the following steps: PyTorch installation: The premise is that Python and pip are installed in CentOS system. Depending on your CUDA version, get the appropriate installation command from the PyTorch official website. For CPU-only training, you can use the following command: pipinstalltorchtorchvisiontorchaudio If you need GPU support, make sure that the corresponding version of CUDA and cuDNN are installed and use the corresponding PyTorch version for installation. Distributed environment configuration: Distributed training usually requires multiple machines or single-machine multiple GPUs. Place

How to choose the PyTorch version on CentOS How to choose the PyTorch version on CentOS Apr 14, 2025 pm 06:51 PM

When installing PyTorch on CentOS system, you need to carefully select the appropriate version and consider the following key factors: 1. System environment compatibility: Operating system: It is recommended to use CentOS7 or higher. CUDA and cuDNN:PyTorch version and CUDA version are closely related. For example, PyTorch1.9.0 requires CUDA11.1, while PyTorch2.0.1 requires CUDA11.3. The cuDNN version must also match the CUDA version. Before selecting the PyTorch version, be sure to confirm that compatible CUDA and cuDNN versions have been installed. Python version: PyTorch official branch

How to update PyTorch to the latest version on CentOS How to update PyTorch to the latest version on CentOS Apr 14, 2025 pm 06:15 PM

Updating PyTorch to the latest version on CentOS can follow the following steps: Method 1: Updating pip with pip: First make sure your pip is the latest version, because older versions of pip may not be able to properly install the latest version of PyTorch. pipinstall--upgradepip uninstalls old version of PyTorch (if installed): pipuninstalltorchtorchvisiontorchaudio installation latest

See all articles