Python Virtual Environment | Introduction
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 of the Python developers use.
Why do we need a virtual environment?
Imagine a scenario where you are working on two web based python projects and one of them uses a Django 1.9 and the other uses Django 1.10 and so on. In such situations virtual environment can be really useful to maintain dependencies of both the projects.
When and where to use a virtual environment?
By default, every project on your system will use these same directories to store and retrieve site packages (third party libraries). How does this matter? Now, in the above example of two projects, you have two versions of Django. This is a real problem for Python since it can’t differentiate between versions in the “site-packages” directory. So both v1.9 and v1.10 would reside in the same directory with the same name. This is where virtual environments come into play. To solve this problem, we just need to create two separate virtual environments for both the projects.The great thing about this is that there are no limits to the number of environments you can have since they’re just directories containing a few scripts.
Virtual Environment should be used whenever you work on any Python based project. It is generally good to have one new virtual environment for every Python based project you work on. So the dependencies of every project are isolated from the system and each other.
How does a virtual environment work?
We use a module named virtualenv which is a tool to create isolated Python environments. virtualenv creates a folder which contains all the necessary executables to use the packages that a Python project would need.
$ pip install virtualenv
Test your installation:
$ virtualenv --version
You can create a virtualenv using the following command:
$ virtualenv my_name
After running this command, a directory named my_name will be created. This is the directory which contains all the necessary executables to use the packages that a Python project would need. This is where Python packages will be installed.
If you want to specify Python interpreter of your choice, for example Python 3, it can be done using the following command:
$ virtualenv -p /usr/bin/python3 virtualenv_name
To create a Python 2.7 virtual environment, use the following command:
$ virtualenv -p /usr/bin/python2.7 virtualenv_name
Now after creating virtual environment, you need to activate it. Remember to activate the relevant virtual environment every time you work on the project. This can be done using the following command:
$ source virtualenv_name/bin/activate
Once the virtual environment is activated, the name of your virtual environment will appear on left side of terminal. This will let you know that the virtual environment is currently active. In the image below, venv named virtual environment is active.
Now you can install dependencies related to the project in this virtual environment. For example if you are using Django 1.9 for a project, you can install it like you install other packages.
(virtualenv_name)$ pip install Django==1.9
The Django 1.9 package will be placed in virtualenv_name folder and will be isolated from the complete system.
Once you are done with the work, you can deactivate the virtual environment by the following command:
Now you will be back to system’s default Python installation.
This article is contributed by Mayank Agrawal. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to email@example.com. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.