Python: Uninstalling

Python seems to install a bit like a virus and traces can get everywhere.

At times, removing an old version of Python can be challenging.

Cleaning up unneeded Python installations can help avoid conflicts between different Python versions and packages.

Using package managers and virtual environments can help.

Uninstalling

Installations can leave traces on your system that may no longer be needed. Here are some recommendations for cleaning up old Python installations:

  1. Uninstall Python from the Control Panel: If you have installed Python using the official installer on a Windows machine, you can uninstall it from the Control Panel. Simply search for “Add or Remove Programs” in the Start menu, then find the Python installation you want to remove and click “Uninstall”.

  2. Delete Python folders: Python installations typically create folders on your system that can be deleted to remove the installation. The main folders are typically located in C:\Python or C:\Users\{user}\AppData\Local\Programs\Python. Be careful when deleting folders to ensure you are only deleting the correct installation.

  3. Clean up environment variables: Python installations can add environment variables to your system that may no longer be needed. You can clean these up by going to the System Properties window, selecting “Advanced System Settings”, then clicking the “Environment Variables” button. Here you can remove any Python-related environment variables that are no longer needed.

Management Tools

Managing Python well can help avoid issues. The following recommendations can help.

  1. Use a package manager: Using a package manager like conda or pipenv can help keep track of Python installations and dependencies. These package managers allow you to create isolated environments for specific projects, so you can avoid installing unnecessary packages and versions of Python.

  2. Use virtual environments: Another way to manage multiple Python installations is to use virtual environments. Virtual environments allow you to create isolated environments for specific projects, so you can avoid conflicts between different Python versions and packages. You can create virtual environments using the venv module or third-party tools like virtualenv or conda.