This repo contains information to setup a docker image with R, Rstudio, Shiny, Radiant, Python, Postgres, JupyterLab, and Spark

To use the docker images you first need to install Docker

• For Mac (M1): https://desktop.docker.com/mac/stable/arm64/Docker.dmg
• For Mac (Intel): https://desktop.docker.com/mac/stable/amd64/Docker.dmg
• For Windows: https://desktop.docker.com/win/main/amd64/Docker%20Desktop%20Installer.exe

After installing Docker, check that it is running by typing docker --version in a terminal. This should return something like the below:

docker --version
Docker version 20.10.13, build a224086

• For detailed install instructions on Windows see install/rsm-msba-windows.md
• For detailed install instructions on macOS (M1) see install/rsm-msba-macos-m1.md
• For detailed install instructions on macOS (Intel) see install/rsm-msba-macos.md
• For detailed install instructions on Linux see install/rsm-msba-linux.md
• For detailed install instructions on ChromeOS see install/rsm-msba-chromeos.md

rsm-msba-arm is built for M1, ARM based macOS computers. rsm-msba-intel is built for AMD based computers and includes Rstudio Server. To build a new image based on rsm-jupter-rs add the following at the top of your Dockerfile

FROM vnijs/rsm-msba-intel:latest

This image builds on rsm-msba-intel and is set up to be accessible from a server running jupyter hub.

To stop (all) running containers use:

docker kill $(docker ps -q)

If the build fails for some reason you can access the container through the bash shell using to investigate what went wrong:

docker run -t -i $USER/rsm-upyter-rs /bin/bash

To remove an existing image use:

docker rmi --force $USER/rsm-msba-spark

To remove stop all running containers, remove unused images, and errand docker processes use the dclean.sh script

./scripts/dclean.sh

Check the disk space used by docker images

docker ps -s

docker system df

To see the documentation and configuration files for versions prior to 2.0 see docker1.0

Shiny is registered trademarks of RStudio, Inc. The use of the trademarked terms Shiny through the images hosted on hub.docker.com has been granted by explicit permission of RStudio. Please review RStudio's trademark use policy and address inquiries about further distribution or other questions to permissions@rstudio.com.

Jupyter is distributed under the BSD 3-Clause license (Copyright (c) 2017, Project Jupyter Contributors)

Thanks to Ajar Vashisth for helping me get started with Docker and Docker Compose. Thanks also to Raghav Prasad for setting up the > 2.0.0 versions of the docker images to start from Jupyter docker images.