How to connect create a Python Virtual Environment
It is often useful to have one or more Python environments where you can experiment with different combinations of packages without affecting your main installation. Python supports this through virtual environments. The virtual environment is a copy of an existing version of Python with the option to inherit existing packages. A virtual environment is also useful when you need to work on a shared system and do not have permission to install packages as you will be able to install them in the virtual environment.
Outline
- Open a terminal
- Setup the pip package manager
- Install the virtualenv package
- Create the virtual environment
- Activate the virtual environment
- Deactivate the virtual environment
- Optional: Make the virtual environment your default Python
- More: Python virtualenv documentation
Requirements
- An installation of Python
Jargon
Link to Jargon page with terms: terminal
Open a terminal
The method you use to open a terminal depends on your operating system.
Open the Windows Command Prompt (show path via Start menu and keyboard shortcuts)
Open the Terminal program. This is usually found under Utilities or Accessories.
Setup the pip package manager
Check to see if your Python installation has pip. Enter the following in your terminal:
If you see the help text for pip then you have pip installed, otherwise download and install pip
Install the virtualenv package
The virtualenv package is required to create virtual environments. You can install it with pip:
Create the virtual environment
To create a virtual environment, you must specify a path. For example to create one in the local directory called ‘mypython’, type the following:
Activate the virtual environment
You can activate the python environment by running the following command:
source mypython/bin/activate
You should see the name of your virtual environment in brackets on your terminal line e.g. (mypython).
Any python commands you use will now work with your virtual environment
Deactivate the virtual environment
To decativate the virtual environment and use your original Python environment, simply type ‘deactivate’.
Optional: Make the virtual environment your default Python
More: Python virtualenv documentation
For more detailed information, see the offical virtualenv documentation
FAQs
In a nutshell, Python virtual environments help decouple and isolate Python installs and associated pip packages. This allows end-users to install and manage their own set of packages that are independent of those provided by the system or used by other projects.
Which virtual environment is best for Python? ›
TLDR: There are three main options for creating and managing virtual environments in Python: pipenv , conda and venv . pipenv is superior to venv and conda . Learn to use pipenv first and you will not have to waste time learning the other two.
Should you use a virtual environment for Python? ›
If you're a developer working on multiple Python projects in parallel, you should use distinct virtual environments for each project. This practice makes working on multiple projects more organized and also reduces the risks of code execution errors.
Should I use Conda or venv? ›
Choosing the right environment management tool depends on your needs. If you need a simple, easy-to-use tool, venv might be the best choice. If you're dealing with complex dependencies, Conda env is the way to go. If you need to switch between different Python versions, consider pyenv or virtualenv.
What is an example of a virtual environment? ›
Email, chat, and web-based document sharing applications are all examples of virtual environments. Simply put, it is a networked common operating space.
How do I see all Python virtual environments? ›
To see a list of the Python virtual environments that you have created, you can use the 'conda env list' command. This command will give you the names as well as the filesystem paths for the location of your virtual environments.
What is the most common Python virtual environment? ›
Python venv is the most popular virtual environment tool out there. It comes with the Python3 installation. So, if you are using Python3, you do not need to install anything. Venv helps create lightweight virtual environments.
Is virtualenv deprecated? ›
Multiple Python projects, each with their own dependencies can be effectively managed using separate virtual environments. Pipenv, Venv, and Pyenv are popular dependency management tools. The ActiveState Platform is a modern solution to dependency management. Virtualenv has been deprecated in Python 3.8.
Why create a Python virtual environment? ›
A virtual environment is a tool that helps to keep dependencies required by different projects separate by creating isolated Python virtual environments for them. This is one of the most important tools that most Python developers use.
What is the best way to create a virtual environment in Python? ›
Getting Started
- Create a virtual environment in your current directory for a project with the command: virtualenv my_project. "my_project" is whatever name you would like to give this environment.
- To create a virtual environment with a specific version of python use the command: virtualenv -p /usr/bin/python2.7 my_project.
There are several conventions as to where to place environments, but one common approach is to put it alongside the source folder for a program. For example, a project might be checkout out to ~/myproject/project-src. If following the convention, the environment would be placed at ~/myproject/env.
Why use Anaconda over venv? ›
The choice between venv and Anaconda depends on your needs: For minimal environments: If you prefer lightweight, minimal environments, venv is the better choice. For data science projects: If you're working on data science projects and need a wide range of pre-installed packages, Anaconda is more suitable.
Should I install Conda or Python first? ›
Anaconda is built after Python, and thus it is imperative to have Python installed on the computer to use Anaconda. However, you do not need to install Python separately when using Anaconda, as Anaconda comes with its own version of Python.
Do I need Conda if I have Anaconda? ›
Both pip and conda are included in Anaconda and Miniconda, so you do not need to install them separately.
What is a virtual environment in code? ›
A virtual environment is a built-in way to create an environment. A virtual environment creates a folder that contains a copy (or symlink) to a specific interpreter. When you install packages into a virtual environment it will end up in this new folder, and thus isolated from other packages used by other workspaces.
What are virtual functions in Python? ›
A virtual function is a member function defined in the base class, re-defined by a derived class. It is declared using the virtual keyword. It tells the compiler to perform late binding or dynamic linkage on function.
What is the difference between venv and Virtualenv? ›
venv is a built-in module in Python 3.3 and later versions that allows you to create isolated Python environments. It is similar to virtualenv , but it is installed by default with Python. pyvenv is a script that comes with Python 3.3 and later versions that allows you to create virtual environments.
What is a coding virtual environment? ›
A virtual environment is itself a directory structure. Use venv to create and manage Python virtual environments. Use pip to install and manage Python external (third-party) libraries. pip allows you to declare all dependencies for a project in a separate file (by convention called requirements.
