Python Virtual Environments

Maintaining different versions of Python can be a chore. Thankfully, there are many tools for managing Python environments; here are a few recommendations:

• PyCharm IDE – great for developing code in Python, and can automatically create virtual environments for a codebase by detecting versions and dependencies from the setup.py or setup.cfg.

• Conda package manager – a Python package manager focused on scientific computing that can also manage virtual environments.

• pyenv CLI – a shell based tool for installing and switching between different versions of Python and dependencies. I will give a brief tutorial of using pyenv below, but recognize that the instructions may change over time so the pyenv documentation is the best place to look.

To create a Python 3.9 virtual environment, try the following steps:

• Install pyenv:

  • if on Mac, use brew: brew install pyenv

  • if on a linux system, try pyenv-installer

  • if on Windows, try pyenv-win

• Install Python 3.9:

  • in a shell, run pyenv install 3.9.1

• Activate Python 3.9 in the current shell

  • in the shell, run pyenv shell 3.9.1

• Proceed with the install of mosartwmpy:

  • in the same shell, run pip install mosartwmpy

• Now you can interact with mosartwmpy in this current shell session

  • if you start a new shell session you will need to run pyenv shell 3.9.1 again before proceeding

  • this new shell session should maintain all previously pip installed modules for Python 3.9.1