I am decidedly a novice when it comes to any and all things Docker (which, incidentally, is why I’ve been reading these posts). But, since it’s helpful for me to have all of these resources together in one place, I thought I’d share the love around.1
R Docker turorial for reproducible research. via rOpenSci Labs
This is actually a series of 6 lessons put together at the rOpenSci unconf in 2016.
Docker for the UseR by Noam Ross
Enough Docker to be Dangerous by Sean Kross
liftr 📦 by Nan Xiao
liftr aims to solve the problem of persistent reproducible reporting. To achieve this goal, it extends the R Markdown metadata format, and uses Docker to containerize and render R Markdown documents.
You can also learn more about liftr from the slides from Nan Xiao’s talk from JSM 2018! 👇
Docker for R Package Development by Jim Hester
An R-docker hello world example via symbolix
How to get started with data science in containers by Jamie Hall
This post isn’t R-specific, but that doesn’t mean it’s not useful!
Dockerized Shiny App development by Tamas Szilagyi
stevedore: A docker client for R by Rich FitzJohn
Dockerise and deploy your own R Archive Repo by Colin Fay
Shipping Data Science Products with R and Docker by Steph Locke
Additions? Questions? Comments? Snide remarks? Feel free to tweet me @dataandme 🐦, and/or comment below!