Python Virtual Environments

Environments are collections of software that tailor an otherwise “basic” computing ecosystem into one that supports your particular computing needs for a particular type of task. You may need different environments for your different tasks. There is a series of videos here on

1. motivation,

2. how to use modules,

3. how to structure directories to house your virtual environments,

4. how to construct and use virtual environments (VEs) for

   • command-line execution of code and

   • use with applications like Jupyter notebooks.

• Motivation: why we need environments.

  • Motivation for environments

• Modules–a backbone of customizing your environments.

  • How to use modules

• Ways to think about structuring the locations of virtual environments to organize the (cluster, compute node type) for which they are used.

  • Organizing your virtual environments

• How to create and use Conda virtual environments on Owl (and other) clusters.

  • Create a Conda VE on Owl for Python

  • Run a python code using a Conda VE on Owl

• How to create and use a Python pip-venv virtual environment (VE) on Owl (and other clusters).

  • Create a Pip-Venv VE on Owl for Python

  • Run a python code using a Pip-Venv VE on Owl

• How to create and use Python Conda virtual environments with Jupyter notebooks (through OOD [Open OnDemand]).

  • Create a Conda VE on Owl for Jupyter notebooks and Python

  • Run a Jupyter notebook with a Conda VE on Owl

• How to create a Conda virtual environment (VE) on Falcon. (The process of creating a VE for Jupyter notebooks on Falcon and of using the VE for both sbatch slurm jobs and Jupyter notebooks are the same as those in previous videos in this section.)

  • Create a Conda VE on Falcon for Python