September 10, 2024
Many applications require specific versions of R and Python or a combination of additional modules. As there might be conflicts between those modules, we recommend to use virtual environments to manage and use those packages.
Individual steps
Log in to Scientific Computing (SciC) Linux Clusters
ssh eristwo.partners.org
then load conda in your environment with the miniforge3 module:
module load miniforge3
then you can create the conda environment:
conda create --name env_name
you can already add requirements here like:
conda create --name env_name python=3.7 R=3.6
execution will take a while. Note that you do not need to specify a version. Do not specify it when you do not use R or Python.
Activate the environment with:
conda activate env_name
In this virtual environment, you can then install packages with conda install package_name (e.g.) :
(env_name) conda install package_name
Note that you need to add:
module load miniforge3
and
conda activate env_name
to your job submission scripts.
Links
Please read more about conda environments :
https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
http://know.continuum.io/rs/387-XNW-688/images/conda-cheatsheet.pdf