This GitHub repository is sandbox of Github Actions to play with for the purposes of a workshop (or independent learning)
See the slides here to be guided through these activities.
This repository contains some mock scripts and files to mimic what a code analysis repository might look like so GitHub actions within this context can be demonstrated.
For the tutorial you will need two main folders:
activity-1-sample-github-actions- we walk through these first to get the idea of how GitHub actions are set up.activity-2-find-the-break- Intentionally broken GitHub actions that will give you good practice at troubleshooting GitHub actions
Additionally, the utils folder has files that are referenced by some of the GitHub Actions. The data folder has a dataset that is utilized by the mock analysis files that are used for this tutorial.
To re-run the entire "analysis", run sh run_analysis.sh in a Terminal or Command Prompt. You will need Python and R installed on whatever environment you choose to run it.
run_analysis.sh- this script represents a main script that can be called to re-run the entire analysis.01-python_test.py- this script represents a python script that is called byrun_analysis.sh. In order for it to be run by GitHub actions, the Docker image or other environment would need to have Python installed.02-r_test.R- this script represents an R script that is also called byrun_analysis.sh. In order for it to be run by GitHub actions, the Docker image or other environment would need to have R installed.03-make-a-plot.Rmd- This file is an R Markdown file, which is commonly used for data analysis notebook output (it creates the03-make-a-plot.htmlwhen run). In order for it to be run by GitHub actions, the Docker image or other environment would need to have R and RMarkdown and other packages used by the Rmd installed.
The data folder represents where data might be kept for an analysis. Often times files that are too big to be stored on GitHub might need to be stored elsewhere and downloaded by a data download script.