search
HomeBackend DevelopmentPython TutorialThe whole process of creating a virtual independent Python environment under Ubuntu

Preface

Virtual environment is an independent execution environment when the program is executed. Different virtual environments can be created on the same server for use by different systems. The running environments between projects remain independent and mutually exclusive. Affected. For example, project B can run in a Python2.7-based environment, while project B can run in a Python3.x-based environment. Manage virtual environments in Python through the virtualenv tool.

In addition, it is highly recommended to install a virtual environment to manage your Python environment on win or mac. The virtual environment can bring you many benefits. For example, on Mac, the built-in Python environment is 2.7. The most suitable version for our Django development is 3.4+. In this case, you have to go to Google to uninstall or switch to the Python3.4 environment, which is still troublesome. Once we have a virtual environment, we can install different versions of the modules or packages we need in an independent environment, which will bring great convenience.

Install

Execute the following command to install in the Linux system:

$ sudo pip install virtualenv

Execute the following command to install in Ubuntu and its derivative systems:

$ sudo apt-get install python-virtualenv

Create

After successful installation, execute the following command to create a virtual environment named myvenv:

$ virtualenv myvenv

The prompts are as follows :

allen@ubuntu:~$ virtualenv myvenv
Running virtualenv with interpreter /usr/bin/python2
New python executable in myvenv/bin/python2
Also creating executable in myvenv/bin/python
Installing setuptools, pip...done.

Activate

source kvenv/bin/activate

The specific process is as follows. You can see that we are viewing the Python version in the current environment, and it is displayed in the virtual environment. Under myvenv:

allen@ubuntu:~$ source myvenv/bin/activate
(myvenv)allen@ubuntu:~$ which python
/home/allen/myvenv/bin/python

Of course, you can exit the current virtual environment with the following command:

deactivate

Pip

After activation After the virtual environment, you can use any Pip in this environment:

pip install Pillow

Virtualenvwrapper

It is a virtual environment expansion package, used to manage virtual environments, as shown in the list All virtual environments, deleted, etc.

1. Installation:

#安装virtualenv
(sudo) pip install virtualenv
 
#安装virtualenvwrapper
(sudo) pip install virtualenvwrapper

2. Configuration:

Modify ~/.bash_profile or other environment variable related files (such as .bashrc (I This is the one under Ubuntu15.10) or use .zshrc after ZSH), add the following statement:

export WORKON_HOME=$HOME/.virtualenvs
export PROJECT_HOME=$HOME/workspace
source /usr/local/bin/virtualenvwrapper.sh

Then run:

source ~/.bash_profile

3. Usage:

mkvirtualenv zqxt: Create a running environment zqxt

workon zqxt: Work in the zqxt environment or switch to the zqxt environment from other environments

deactivate: Exit the terminal environment

Others:

rmvirtualenv ENV: Delete the running environment ENV

mkproject mic: Create the mic project and running environment mic

mktmpenv: Create a temporary running environment

lsvirtualenv: List available running environments

lssitepackages: List packages installed in the current environment

The environments created are independent, do not interfere with each other, and do not require sudo permissions You can use pip to manage packages.

Summary

The above is the entire content of this article. I hope the content of this article can bring some help to everyone's study or work. If you have any questions, you can leave a message to communicate.

For more articles related to the entire process of creating a virtual independent Python environment under Ubuntu, please pay attention to the PHP Chinese website!

Statement
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
How to Use Python to Find the Zipf Distribution of a Text FileHow to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

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

How to Download Files in PythonHow to Download Files in PythonMar 01, 2025 am 10:03 AM

Python provides a variety of ways to download files from the Internet, which can be downloaded over HTTP using the urllib package or the requests library. This tutorial will explain how to use these libraries to download files from URLs from Python. requests library requests is one of the most popular libraries in Python. It allows sending HTTP/1.1 requests without manually adding query strings to URLs or form encoding of POST data. The requests library can perform many functions, including: Add form data Add multi-part file Access Python response data Make a request head

Image Filtering in PythonImage Filtering in PythonMar 03, 2025 am 09:44 AM

Dealing with noisy images is a common problem, especially with mobile phone or low-resolution camera photos. This tutorial explores image filtering techniques in Python using OpenCV to tackle this issue. Image Filtering: A Powerful Tool Image filter

How Do I Use Beautiful Soup to Parse HTML?How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

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

How to Work With PDF Documents Using PythonHow to Work With PDF Documents Using PythonMar 02, 2025 am 09:54 AM

PDF files are popular for their cross-platform compatibility, with content and layout consistent across operating systems, reading devices and software. However, unlike Python processing plain text files, PDF files are binary files with more complex structures and contain elements such as fonts, colors, and images. Fortunately, it is not difficult to process PDF files with Python's external modules. This article will use the PyPDF2 module to demonstrate how to open a PDF file, print a page, and extract text. For the creation and editing of PDF files, please refer to another tutorial from me. Preparation The core lies in using external module PyPDF2. First, install it using pip: pip is P

How to Cache Using Redis in Django ApplicationsHow to Cache Using Redis in Django ApplicationsMar 02, 2025 am 10:10 AM

This tutorial demonstrates how to leverage Redis caching to boost the performance of Python applications, specifically within a Django framework. We'll cover Redis installation, Django configuration, and performance comparisons to highlight the bene

Introducing the Natural Language Toolkit (NLTK)Introducing the Natural Language Toolkit (NLTK)Mar 01, 2025 am 10:05 AM

Natural language processing (NLP) is the automatic or semi-automatic processing of human language. NLP is closely related to linguistics and has links to research in cognitive science, psychology, physiology, and mathematics. In the computer science

How to Perform Deep Learning with TensorFlow or PyTorch?How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

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

See all articles

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)
2 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
Repo: How To Revive Teammates
4 weeks agoBy尊渡假赌尊渡假赌尊渡假赌
Hello Kitty Island Adventure: How To Get Giant Seeds
3 weeks agoBy尊渡假赌尊渡假赌尊渡假赌

Hot Tools

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools