vladdsm/docker-demo

Demo about using Docker Containers for Reproducible Resarch

docker-demo

Purpose

Illustrate few use cases about using Docker Containers for Data Science and Reproducible Research

Advantages:

• Portability
• Reproducibility
• Automated builds

Disadvantages:

• Persistent Data Storage
• GUI

Examples of Dockerfiles

• set up custom R-Studio IDE in a container. Added custom packages and h2o open-source platform: https://github.com/vladdsm/docker-r-studio
• set up base R template. Added custom packages and h2o open-source platform: https://github.com/vladdsm/docker-r-h2o
• example of adding R markdown: https://github.com/vladdsm/docker-r-r
• example of running R script: https://github.com/vladdsm/docker-r-s
• example of R plumber API: https://github.com/vladdsm/docker-r-plumber
• example of R ShinyApp: https://github.com/vladdsm/docker-r-shiny
• example of R ShinyApp developed in a Docker Container with {golem} framework: https://github.com/vladdsm/trackpack
• PLANNED example of multi container application with docker-compose (ShinyApp + database):

Docker compose

Service to run multi container applications:

Useful commands on Docker compose

• Check version: docker-compose version
• Start service: docker-compose up - must be in the same folder as docker-compose.yml file
• Stop service: docker-compose down
• Command to run docker compose file: docker-compose up -d
• Command to check all processes: docker ps
• ... scale a service: docker-compose up -d --scale

Useful resources

Use r with docker general info ⇒ this is just amazing tutorial!!! https://ropenscilabs.github.io/r-docker-tutorial/

Run R script in the docker container: https://www.r-bloggers.com/running-your-r-script-in-docker/