Wrote a convenience function for getting variable names from formula

I am using patsy as a key dependency in a stats project, and I found myself needing to identify which variables are categorical after constructing a dataframe using patsy formulas.

After an attempt using regexps ("...now you have two problems..."), I read Model specification for experts and computers a few times, and spent a lot of time poking around in X.design_info (where y, X=dmatrices(formula, data, return_type='dataframe')). Thankfully I ended up with something much shorter and more robust than my regexps attempt.

I have two questions:

1. I'm still not sure if I've used the interiors details of X.design_info correctly -- it does what I want but there are places where multiple things provide the same info. I'd love to have someone "in the know" look at the function and tell me if I should make a different choice. Is there a way to do this? (Counting comments the function is ~60 lines; not counting comments it is about 30 lines).

2. Is there any interest in having something like this contributed back to the project? I've commented and unit tested the function already, and happy to make sure final comments/tests conform to your norms & standards. I skimmed the issues before posting, and for example it appears this issue #155: patsy equivalent of R's all.vars might benefit from my function (not exactly the same but perhaps close enough).

Start by reviewing the proposed convenience function and how it uses X.design_info after dmatrices(formula, data, return_type='dataframe'). Compare its intended variable-name behavior with issue #155 and the existing patsy model-specification guidance. Done requires agreement on whether the function belongs in patsy and which tests and documentation should define its behavior.