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Introduction: This workshop will discuss how the various Python related tools work together on the cluster and introduce a series of best practices for managing these environments.

Course Goals:

  • Understand where pip installs packages within a user’s home folder with respect to different versions of Python.

  • Understand how to use pip to install a package within a conda environment.

  • Demonstrate how to create a conda environment, with pip installs, that can be shared across a project.

  • Demonstrate creating a module file to load a conda/python environment.

  • Suggested Best Practices.

Notes:

  • The focus of this workshop is on how to use Python, Pip and Conda explicitly on the ARCC clusters (not on desktops).

  • This is NOT an introduction to Python programming. Users should be familiar with python, using pip, and creating conda environments.

  • If you have existing conda environments, or have installed your own version of Anaconda, then the examples within this workshop might provide different results.


Sections

  1. Python Pip Installs on the Cluster:

  2. Pip Install within a Conda Environment:

  3. Create a Shared TensorFlow Conda Environment:

  4. Create a Module File to Load Your Conda Environment:

  5. Python, Conda and Pip: Suggested Best Practices:


 

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