While the python installation and management through
reticulate
is per default managed via Miniconda, high
performance computing facilities (such as Compute Canada cluster
‘cedar’) ask users not to install Miniconda, but use pip
and standard virtual python environments instead. In this case, users
need to manually create a virtual environment that satisfies the python
dependencies of this R package (i.e., listed in the DESCRIPTION
file).
A suitable environment py-snowpack
can be created on
cedar as follows:
module load python/3.7
module load scipy-stack/2021a # contains numpy, pandas, etc
virtualenv --no-download py-snowpack # creates the virtual environment 'py-snowpack' in $HOME directory
source py-snowpack/bin/activate # activates environment
pip install --no-index --upgrade pip
pip install joblib --no-index
pip install scikit-learn==0.22.1 --no-index # specific version!
deactivate
To use this specific virtual environment in your R session and by this R package, the requirements to activating the environment need to be called in a job (bash) script,
module load python/3.7
module load scipy-stack/2021a
and the following line should be included in your R script to direct
reticulate
to your environment
library(sarp.snowprofile.pyface)
reticulate::use_virtualenv("~/py-snowpack") # use the path to the virtual environment installed above