For researchers who have Python or R package requirements beyond the common packages (e.g. Numby, Scipy, Pandas, BioConda, R) we recommend using Anaconda. Using Anaconda’s package manager allows the creation and management of packages and environments. Using conda you can switch between versions of Python libraries and applications for different projects.
For your convenience, we provide several versions of Miniconda (which is a minimal set of Anaconda libraries) as a module on koko and koko 2.0.
koko 3.0 (koko-login.hpc.fau.edu)
# koko 3.0 miniconda 3
module load miniconda3-4.6.14-gcc-8.3.0-eenl5dj
# koko 3.0 minicona 2
module load miniconda2-4.6.14-gcc-8.3.0-ccf3jpq
koko 2.0 (koko-login.fau.edu)
# koko 2.0 anaconda 3
module load anaconda3/5.0.1
or
module load miniconda3-4.6.14-gcc-7.3.0-nfdnfv4
# koko 2.0 anaconda
module load anaconda2/5.0.1
Once you load the anaconda or miniconda modules you can create virtual environments with your need components.
Example:
# R
conda create -n r_env r-essentials r-base
# OpenBlas
conda create -n legacy_application python=2.7 openblas
# Your own personal jupyter notebook server
conda create -n py37_dev python=3.7 numpy scipy pandas matplotlib ipython jupyter
Using your environment:
To use the applications in your environment, load the miniconda module and execute the following
source activate env_name