Internal tools for the ML backend. Includes preproccesing of URLs. Versions model-training and model-service.
If you wish to test the package, you can install it locally through $ pip install remlapreprocesspy. You can also install it by running poetry install from within the lib-ml folder.
# python
import remlapreprocesspy
print(preprocess(["test.org","www.test.com"]))
To release an updated version, set the version variable within the pyproject.toml and push a tag with the same version number. For example, to release VX.X.X, set version = X.X.X in pyproject.toml. Then add the new tag through git tag VX.X.X and push the tag using git push origin tag VX.X.X. The new version will be automatically published to PyPI by the github workflow.