Running an R Script on a Schedule: Gh-Actions (2024)

In this tutorial I have an R script that runs every day on github actions. It creates a curve in ggplot2 and posts that picture to twitter.

The use case is this: You have a script and it needs to run on a schedule (for instance every day).

Other ways to schedule a script

I will create a new post for many of the other ways on which you can run an R script on schedule. But in this case I will run the script on github actions. Github actions is completely scriptable and works quite well. I found it quite difficult to make it work in one go. Find all posts about scheduling an R script here

Github actions details

Github actions is a new product from github, you get 2000 minutes per account/month.You create github actions by writing down the steps in a yaml file in a specificplace in your repo: .github/workflows/*. Yaml files are sensitive to indentationso try a yaml validator before you push the data to github.

So what are we going to do?

Example of a script

I have an R script that:

creates a u-shape curve dataset
adds random names to the x and y axes
creates ggplot2 image
posts the tweet as a twitter account

With this as result:

Of course you could create something that is actually useful, like downloading data, cleaning it and pushing it into a database. But this example is relatively small and you can actually see the results online.

Small diversion: credentials/ secrets

For many applications you need credentials and you don’t want to put thecredentials in the script, if you share the script with someone, they also have the credentials. If you put it on github, the world has your secrets (I just did this).

So how can you do it? R can read environmental variablesand in github you can input the environmental variables that willbe passed to the runner when it runs (there are better, more professional tools to do the same thing but this is good enough for me). So you create an environmental variable called apikey with a value like aVerY5eCretKEy. In your script you use Sys.getenv("apikey") and the script will retrieve the apikey: aVerY5eCretKEy and use that.

How do you add them to your local environment?

Create a .Renviron file in your local project
add a new line to your .gitignore file: .Renviron
Now this file with secrets will be ignored by git and youcan never accidentely add it to a repo.
the .Renviron file is a simple text file where you can add ‘secrets’ like: apikey="aVerY5eCretKEy" on a new line.

How do you add them to github?

go to settings/secret in your repo and add them

they will be retrieved from the stores with something like ${{ secrets.APIKEY}}

So what do you need to make this work?

Steps in order

Check if your script runs on your computerSet up renv and snapshot(optional) try a cache of your renv libraries for faster install the correct packages on the runnerexecute the script

Steps with explanation

run your R script locally to make sure it works source("script.R")
check if you have set up renv for this project. renv::status(). When you are satisfied with the script, use renv::snapshot() to fix the versions of your required packages. This creates an ‘renv.lock’ file that contains the package versions you used.
copy and modify the actions from r-lib
(optional) use a cache step from the renv vignette about CI

env: RENV_PATHS_ROOT: ~/.local/share/renvsteps:- name: Cache packages uses: actions/cache@v1 with: path: ${{ env.RENV_PATHS_ROOT }} key: ${{ runner.os }}-renv-${{ hashFiles('**/renv.lock') }} restore-keys: | ${{ runner.os }}-renv-- name: Restore packages shell: Rscript {0} run: | if (!requireNamespace("renv", quietly = TRUE)) install.packages("renv") renv::restore()

use renv::restore() to install the correct packages based on the renv.lock file

- run: R -e 'renv::restore()'

run the script

- run: Rscript run_job.R

So to run a thing on github actions we have to give instructions to theinfrastructure, we tell it what docker container to use, what things to installand what commands to run, until, finally, we can run our script.And now it runs every day.

References

Find more tutorials by me in this tutorial overview page
Find all posts about scheduling an R script here
the github workflow file
examples of R-specific github actions can be found here
there is a book of github actions for R online.

Reproducibility

At the moment of creation (when I knitted this document ) this was the state of my machine: **click here to expand**

sessioninfo::session_info()

─ Session info ─────────────────────────────────────────────────────────────── setting value version R version 4.0.2 (2020-06-22) os macOS Catalina 10.15.6 system x86_64, darwin17.0 ui X11 language (EN) collate en_US.UTF-8 ctype en_US.UTF-8 tz Europe/Amsterdam date 2020-09-24 ─ Packages ─────────────────────────────────────────────────────────────────── package * version date lib source assertthat 0.2.1 2019-03-21 [1] CRAN (R 4.0.0) cli 2.0.2 2020-02-28 [1] CRAN (R 4.0.0) crayon 1.3.4 2017-09-16 [1] CRAN (R 4.0.0) digest 0.6.25 2020-02-23 [1] CRAN (R 4.0.0) evaluate 0.14 2019-05-28 [1] CRAN (R 4.0.0) fansi 0.4.1 2020-01-08 [1] CRAN (R 4.0.0) glue 1.4.1 2020-05-13 [1] CRAN (R 4.0.1) htmltools 0.5.0 2020-06-16 [1] CRAN (R 4.0.1) knitr 1.29 2020-06-23 [1] CRAN (R 4.0.1) magrittr 1.5 2014-11-22 [1] CRAN (R 4.0.0) rlang 0.4.7 2020-07-09 [1] CRAN (R 4.0.2) rmarkdown 2.3 2020-06-18 [1] CRAN (R 4.0.1) sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.1) stringi 1.4.6 2020-02-17 [1] CRAN (R 4.0.0) stringr 1.4.0 2019-02-10 [1] CRAN (R 4.0.0) withr 2.2.0 2020-04-20 [1] CRAN (R 4.0.2) xfun 0.15 2020-06-21 [1] CRAN (R 4.0.2) yaml 2.2.1 2020-02-01 [1] CRAN (R 4.0.0)[1] /Library/Frameworks/R.framework/Versions/4.0/Resources/library