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Software Package/Environment Management Workshop

Package and computing environment management systems for R, Python, and Anaconda make it easy to install the software you need for your research projects. They also make it easy to accidentally use up all of the space in your home directory or end up with frustrating software conflicts!

In this workshop presented by the SCINet Office, we will cover best practices for managing software packages and computing environments on SCINet’s supercomputers. This will be a hands-on workshop that will provide you with the practical knowledge and skills you need to spend less time worrying about package management and more time focusing on your research!

At least some experience with the command line will be helpful for working through the exercises.

To register, please fill out this form

Remote


Tutorial instructions

Steps to prepare for the tutorial sessions:

  1. Login to Ceres Open OnDemand at https://ceres-ondemand.scinet.usda.gov/. For more information on login procedures for web-based SCINet access, see the SCINet access user guide.

  2. Open a command-line session by clicking on “Clusters” -> “Ceres Shell Access” on the top menu. This will open a new tab with a command-line session on Ceres’ login node.

  3. Request resources on a computer node by running the following command. 
     salloc --reservation=scinet_workshop1 -A scinet_workshop1 -t 05:00:00 -n 1 --mem 8G
  4. Create a workshop working directory by running the following commands. Note: you do not have to edit the commands with your username as it will be determined by the $USER variable. 
     mkdir /project/scinet_workshop1/$USER/
 cd /project/scinet_workshop1/$USER/


Recording

A recording of this workshop is available here.

  • Software Package/Environment Management Workshop: Python and conda

    We will begin by focusing on package and environment management with the standard Python toolset: the venv and pip modules that are usually included with Python. Later, we will learn package and environment management with conda.

    • Friday, July 19, 2024

  • Software Package/Environment Management Workshop: R

    In this session, we will begin by using R from the command line. Later, we will cover similar steps using RStudio Server available on Open OnDemand. We will primarily focus on using the renv package for package management, but we will also note alternatives at the end.

    • Friday, July 19, 2024