updating conda env on tallgrass #349
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A follow-up note on that "extra" environment, To get that environment as an option in your jupyter server, you need to add it as a kernel specification. There are a few ways to do that. The least hacky is to do this:
Tweak that last command to reflect the name and display name you like. This will install a After you do this, the next time you run OOD, you should have access to this additional environment. This mechanism will let you create a 'beta' or 'pre-release' HyTEST environment (substitute 'hytest-beta' for 'gdp' in all of the above). So doing will let you test-drive updated environment to satisfy yourself that it doesn't break anything. Then you can update the 'production' hytest environment. |
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Hello,
The Open On Demand (OOD) service lets us spin up a jupyter server on a tallgrass node. It's an easy way to get hub-like interface and HPC computational power without any user training or configuration. There are some details to be aware of on this system. I offer them here to be sure that they are captured somewhere before I migrate off this project:
module avail
to see all the modules you have access tohytest
should be one of the optionsmodule load hytest
should configure your shell to use the right conda environment./caldera/projects/usgs/water/impd/hytest/modules/hytest
hytest
module is built on a conda installation in/caldera/projects/usgs/water/impd/hytest/
export PATH=/caldera/projects/usgs/water/impd/hytest/conda/bin:$PATH
source /caldera/projects/usgs/water/impd/hytest/conda/etc/profile.d/conda.sh
conda activate hytest
conda env list
conda update --dry-run --update-all
--dry-run
switch causes conda to just report what it would do.conda update --update-all
conda update packagename
if you only want to update a specific package.gdp
environment is installed there as well. Once you've got this conda active, you can create and modify these environments per normal conda usage.Note that you'll be modifying the common environment and its packages. This will affect all users of this environment. Also, updating a conda environment while processes are actively using it can yield odd results. Recommend that you make such upgrades at periods of low usage (evenings, early-mornings, weekends).
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