Skip to content
Information for the Docker for Data Science Tutorial at useR!2019
Branch: master
Clone or download
Latest commit e9cda9b Jul 9, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
kubernetes-cronjobs-example extra examples Jul 9, 2019
kubernetes-plumber-example extra examples Jul 9, 2019
shinyproxy-docker-compose extra examples Jul 9, 2019
.gitignore ignore .project Jul 2, 2019
README.md hint on allowing tcp connections Jul 9, 2019
docker-for-data-science.html slides Jul 9, 2019

README.md

useR!2019 tutorial on Docker for Data Science

Contents

See abstract on the useR!2019 website

Preparation for the tutorial

It is absolutely mandatory to install the required software prior to the tutorial.

Software to install

By all means:

Optionally:

Note: The Docker daemon needs to be configured to accept connections over TCP, see https://www.shinyproxy.io/getting-started/#docker-startup-options This will be explained in the tutorial, but it does not harm to already configure it.

Docker images to pull

docker pull hello-world
docker pull openanalytics/r-base
docker pull openanalytics/shinyproxy
docker pull openanalytics/shinyproxy-snapshot
docker pull openanalytics/shinyproxy-demo
docker pull openanalytics/shinyproxy-dash-demo
docker pull openanalytics/shinyproxy-rstudio-ide-demo
docker pull openanalytics/scheduled-reporting-demo
docker pull openanalytics/scheduled-reporting-demo-report
docker pull openanalytics/rdepot-repo
docker pull openanalytics/rdepot-app
docker pull openanalytics/rtq-client
docker pull redis
docker pull apache/zeppelin:0.8.1

Git repositories to clone

See you in Toulouse!

You can’t perform that action at this time.