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Virtual Environment in Python

Authored on October 22, 2022 by Aaron Christopher.

4 min read
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Working with virtual environment in Python is tedious for some sussy bakas. In this article we will use venv. It is a module that should be included when you install Python.

Venv official definition

The venv module supports creating lightweight “virtual environments”, each with their own independent set of Python packages installed in their site directories. A virtual environment is created on top of an existing Python installation, known as the virtual environment's “base” Python, and may optionally be isolated from the packages in the base environment, so only those explicitly installed in the virtual environment are available.

You can read the documentation if you want to...

Definition simplified

I know the explanation above is too technical for some sussy bakas, but here is my attempt to explain it.

You install Python on your machine. This includes some standard packages. For a lot of projects though, you'll have to install additional packages (using PIP for example). As you build more, and more complex projects, it becomes hard to track which projects use which packages. Also: different projects may use different versions of the same package.

To make this more structured, you should create a virtual environment for each project. This basically contains a copy of your original Python installation, and you can add all your project-specific packages here. Other projects won't be affected. Take it a step further, and you arrive at Docker containers. These create isolated environments, containers, not only for your Python installations, but for all project dependencies. This makes it very easy to transfer your project to another machine as well. You just have to clone the Docker container.

Enough talking, let's see how to do it.

Create a virtual environment

python -m venv .venv

The command will create a folder called .venv. Inside the folder, there is some subfolders and files that you should not be worried about.

But the important file is inside the bin folder, called activate. This is an executable, which will activate the virtual environment.

Note: I'm assuming you are working on UNIX machine (Linux or Mac), if you're on windows, consider this

Activate the virtual environment

source .venv/bin/activate

The command will activate the virtual environment, so now if you have installed Numpy for example, you will lose it in the current env, because it creates a clean state of Python.

Installing packages in the virtual environment

Now I'm going to install numpy on my new venv, let's do it.

pip install numpy

Now you can use numpy, but what if you want to tell people and your future self that this project uses numpy? The answer is by creating requirements.txt file.

pip freeze > requirements.txt

Now you should have a new file called requirements.txt that lists all your installed Python packages. If you want to install the packages listed in the requirements.txt, you can use the command below

pip install -r requirements.txt

Of course, we can use other tools like Poetry to manage packages easily, but I tends to stick with the requirements.txt file whenever possible.

You can add some more packages as you need, and the steps above are also doable, unless there is a dependency errors. Maybe I will explain this in another blog.

Deactivate the virtual environment

To deactivate the virtual environment means you are going back to the main Python environment. You can achieve this by entering this command



So now you have learned how to use the virtual environment in Python! I suggest you to try experimenting with it, because experience is the best teacher, ah me so wise ._.