A cookiecutter template to bootstrap machine learning prediction experiments, and integrate the predictions generated by this experiment to a Translator Reasoner API.
- Install
cookiecutter
with:
pip install cookiecutter
- Run
cookiecutter
with:
cookiecutter https://github.com/MaastrichtU-IDS/cookiecutter-trapi-predict-kit
-
Enter the requested information, then win! Remember, package names should only have letters, numbers, and underscores.
-
If you're working under version control, copy the repository into your folder tracked under git, commit the files, and push to your remote.
Your new python package will have the following:
- Standard
src/
layout - Declarative setup with
pyproject.toml
- Reproducible tests with
pytest
- Data management with
dvc
- Automated running of tests on each push with GitHub Actions
One liner to quickly reset a create default repo and run training:
cd .. && rm -rf my-model && cookiecutter https://github.com/MaastrichtU-IDS/cookiecutter-trapi-predict-kit && cd my-model && hatch run train && hatch run predict && hatch run test