Virtual environments also allows the end-user to install and manage their own set of dependencies not provided on their system. Then you would create a virtual environments. For example, let’s say you had Python 3.11 on your machine, and you wanted to run another program from a GitHub repo that was developed in Python 2, and you didn’t want to to install Python 2 on your local machine.

Using virtual environment isolates Python installs and associated pip packages.

I suppose my primary concern is that if I can only use the latest versions of a package in a virtual environment, that would limit my capability to perform tasks … Why use a virtual environment at all if it just matches my global environment? Why use Virtual Environments Let me know if this helps or if you need further assistance! If the instructions tell you to install a specific older version of numpy that is causing an error then I would go with that latest version. This will spawn a new shell subprocess, which can be deactivated by using exit. Step 4: Activate Virtual Environment pipenv shell Step 1: Make project folder mkdir my_project Follow these steps in creating a new virtual environment using pipenv. I use pipenv daily, I might be able to assist you with this. According to the pipenv doc, the command to install pipenv is: pip install -user pipenv Yes, you are correct, CodeAcademy instruction video is a bit old however, using - has not depreciated. using -three to create a virtual environment is deprecated, so perhaps there is new information in the setup I’m missing? I’ve noticed the CodeAcademy instruction video is a bit old, i.e.

Numpy latest version