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.