Streamlit app for comparing q10(LRV) evaluation methods on the same editable integer input table:
- Empirical bootstrap
- Bayesian approximation
- Bayesian (PyMC)
conda activate validreusepip install -r requirements.txtRecommended:
- Use Python 3.13 for the full app, including PyMC.
- The older
validreuse/Python 3.14 environment is still present, but PyMC is not reliable there.
streamlit run app.pyBuild the image:
docker build -t validreuse-app .Run it locally:
docker run --rm -p 8501:8501 validreuse-appThen open http://localhost:8501.
- Copy the project to the server.
- Install Docker.
- Build the image:
docker build -t validreuse-app .- Run the container in the background:
docker run -d --name validreuse -p 8501:8501 --restart unless-stopped validreuse-app- Put Nginx or Caddy in front of port
8501if you want HTTPS and a public domain.
This app can also be deployed from a GitHub repo on Streamlit Community Cloud with app.py as the entrypoint.
Note:
- PyMC makes deployment heavier than a simple Streamlit app.
- If you want the lightest deployment, we can make the PyMC method optional or disable it in cloud builds.