User Environments

Resources¶

These are available to each user:

• RAM: 2 GB

• CPU: 1

• Storage Limits: 10G per user (configurable for special purposes)

Kernels¶

The base image includes both Python and R kernels.

Development Environments¶

• JupyterLab

• Jupyter Notebook

• VS Code

• RStudio

• Shiny

Default Packages Installed For Users¶

Below is the list of base packages that are installed on the user images. If you would like additional packages installed, it is strongly recommended that you open an issue in the image repository and request we install it there.

When a user installs a package in to their home directory, it can take up significant amounts of space and push you close to your 10G storage limit.

Python Packages¶

The following Python packages are pre-installed. The full list and available versions are found in the base user image repository:

• datascience

• jupyter-shiny-proxy

• jupysql

• geopandas

• geopy

• openpyxl

• matplotlib

• numpy

• openpyxl

• otter-grader

• pandas

• plotly

• pytorch

• scikit-learn

• scipy

• seaborn

• statsmodels

• sympy

R Packages¶

The following R packages are pre-installed. Versions are available in the repository:

• car

• colorspace

• devtools

• esquisse

• extrafont

• flexdashboard

• forcats

• forecast

• gdalcubes

• ggThemeAssist

• ggalluvial

• ggbeeswarm

• ggcorrplot

• GGally

• ggdist

• ggformula

• gghighlight

• ggmosaic

• ggpubr

• ggrepel

• ggridges

• ggtext

• ggthemes

• gridExtra

• gtsummary

• IRkernel

• janitor

• knitr

• leaflet

• Lock5Data

• lubridate

• magick

• mapgl

• mapproj

• maps

• minioclient

• mosaic

• naniar

• nycflights13

• openintro

• palmerpenguins

• plotly

• pwr

• quarto

• RColorBrewer

• remotes

• renv

• rmarkdown

• rstac

• scales

• see

• sf

• sjPlot

• socviz

• stars

• sweep

• terra

• tidymodels

• tidyquant

• tidyr

• tidyverse

• timetk

• viridis