It's unlikely that the OS's version of Python, and the Python packages available through the OS, are going to be the ones you'd install of your own volition. And on your workstation, it's likely you'll have multiple projects with different requirements.
You almost always want to develop in a virtualenv so you can install the exact versions of things you need without conflicting with the ones the OS itself requires. If you're abstracting out the site-packages directory anyway, why not take one more step and abstract out Python, too? Things like pyenv and uv make that trivially easy.
For instance, this creates a new project using Python 3.13.
I did not have Python 3.13 installed before I ran those commands. Now I do. It's so trivially easy to have per-project versions that this is my default way of using Python.
You can get 95% of the same functionality by installing pyenv and using it to install the various versions you might want. It's also an excellent tool. Python's own built-in venv module (https://docs.python.org/3/library/venv.html) makes it easy to create virtualenvs anytime you want to use them. I like using uv to combine that and more into one single tool, but that's just my preference. There are many tools that support this workflow and I highly recommend you find one you like and use it. (But not pipenv. Don't pick that one.)
This is the conventional wisdom these days, and a real thing, but unless you are admin challenged, running your local scripts with the system Python is fine. Been doing it two decades plus now.
You almost always want to develop in a virtualenv so you can install the exact versions of things you need without conflicting with the ones the OS itself requires. If you're abstracting out the site-packages directory anyway, why not take one more step and abstract out Python, too? Things like pyenv and uv make that trivially easy.
For instance, this creates a new project using Python 3.13.
I did not have Python 3.13 installed before I ran those commands. Now I do. It's so trivially easy to have per-project versions that this is my default way of using Python.You can get 95% of the same functionality by installing pyenv and using it to install the various versions you might want. It's also an excellent tool. Python's own built-in venv module (https://docs.python.org/3/library/venv.html) makes it easy to create virtualenvs anytime you want to use them. I like using uv to combine that and more into one single tool, but that's just my preference. There are many tools that support this workflow and I highly recommend you find one you like and use it. (But not pipenv. Don't pick that one.)