Environments
Currently there are two pre-built environments available for general usage. These include the default which should cover many general use cases, and the remote desktop which has everything the default environment includes, and adds a remote desktop feature in the browser. The remote desktop feature allows for running graphical applications in the cluster environment that would not have been previously possible.
Default
Python Data Science packages installed:
numpy
matplotlib
pandas
pytorch
torchvision
torchaudio
pytorch-cuda
tensorflow-gpu
opencv
scipy
scikit-learn
scrapy
beautifulsoup4
keras
R Packages (from r-essentials):
r-base
r-recommended
r-ggplot2
r-plyr
r-reshape2
r-dplyr
r-tidyr
r-caret
r-randomforest
r-data.table
r-quantmod
r-shiny
r-rmarkdown
r-glmnet
r-jsonlite
r-zoo
r-rbokeh
r-formatr
r-tidyverse
r-dbi
r-broom
r-forcats
r-haven
r-hms
r-httr
r-lubridate
r-magrittr
r-modelr
r-purrr
r-readr
r-readxl
r-rvest
r-stringr
r-tibble
r-xml2
All installed Conda Packages (Python, R, etc.):
In addition to what is installed from Conda, the environment has many of the familiar packages found on Linux systems:
tar
xz
gzip
bzip2
git
zip
unzip
wget
which
find-utils
bash-completion
less
htop
man-db
man-pages
tmux
pandoc (for exporting the Jupyter notebooks)
Jupyter extensions / features:
jupyter-resource-usage
nbgitpuller
ipywidgets
Various LSPs (for making editing easier):
python-lsp-server
r-languageserver
bash-language-server
Remote Desktop
Extends the Default environment, by adding:
XFCE Desktop
Firefox
Emacs
Neovim
VSCode