Docker Environment for Strong Replication

To ensure a fully reproducible environment, the replication package ships with a Docker workflow that bundles the full R stack, required packages, and JupyterLab.

Recommended: Use Docker whenever you need a clean-room replication or plan to run the notebook on a new machine.

Prebuilt Image

  • Registry: ztshi/plp
  • Ready for local machines or GitHub Codespaces (install the suggested Jupyter kernel extension when prompted).

Build Locally 

docker build -t plp .

Run the Container 

docker run --rm -it -p 8888:8888 \
  -e JUPYTER_TOKEN=panel-lp \
  -v ${PWD}:/home/jovyan/work \
  plp
  1. Wait for the console to print the JupyterLab URL (token or panel-lp).
  2. Open the URL in a browser.
  3. Launch applications/replication.ipynb.

All required R libraries (ggplot2, reshape2, ggpubr, etc.) are baked into the image, so the notebook runs without additional setup.

Troubleshooting

  • Port already in use: change -p 8888:8888 to another host port (e.g., -p 8787:8888).
  • Permission issues on Windows: ensure Docker Desktop has file-sharing enabled for the repository directory.
  • Need persistent tokens: adjust JUPYTER_TOKEN or omit the flag to have Jupyter generate a random token each run.

Licensed under MIT.