Addresses #559 by deprecating PatsyTransformer and introducing a FormulaicTransformer.
In writing of FormulaicTranformer I followed what is described in the formulaic documentation for integrating with sklearn. The main (tiny) differences with such implementation can be summarized as:
keeping the return_type parameter available (similar to what PatsyTransformer does)
avoiding parsing of parameters in __init__ method
how fit check is performed in .transform()
Additionally the PR makes both dependencies optional.
Type of change
[ ] Bug fix (non-breaking change which fixes an issue)
[X] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
Checklist:
[X] My code follows the style guidelines (flake8)
[X] I have commented my code, particularly in hard-to-understand areas
[ ] I have made corresponding changes to the documentation (also to the readme.md)
[X] I have added tests that prove my fix is effective or that my feature works
[X] I have added tests to check whether the new feature adheres to the sklearn convention
[X] New and existing unit tests pass locally with my changes
Description
Addresses #559 by deprecating
PatsyTransformerand introducing aFormulaicTransformer.In writing of
FormulaicTranformerI followed what is described in the formulaic documentation for integrating with sklearn. The main (tiny) differences with such implementation can be summarized as:return_typeparameter available (similar to whatPatsyTransformerdoes)__init__method.transform()Additionally the PR makes both dependencies optional.
Type of change
Checklist: