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  • 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.

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Note

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.

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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:

Existing Conda Environments?

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Python Pip Installs on the Cluster

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