If the dependency is really a showstopper, bundling could be an option. The module is a single, pure python file so that shouldn't complicate things much.
@Joel, regarding «without ndarray/sparse matrix type support, we're not going to be able to annotate most of our code in sufficient detail» That shouldn't be a problem, we have already written some working support for numpy at https://github.com/machinalis/mypy-data, so it's possible no annotate ndarrays and matrix types (scipy.sparse is not covered yet, I could take a look into that). Best, D. On Tue, Aug 2, 2016 at 7:12 PM, Andreas Mueller <t3k...@gmail.com> wrote: > > > On 08/02/2016 01:48 PM, Gael Varoquaux wrote: > >> * One relevant consequence is that, to add annotations on the code, >>> scikit-learn should depend on the "typing"[1] module which contains some >>> of the >>> basic names imported and used in annotations. It's a stdlib module in >>> python >>> 3.5, but the PyPI package backports it to python 2.7 and newer (I'm not >>> sure >>> how it works with Python 2.6, which might be an issue) >>> >> I am afraid that this is going to be a problem: we have a no dependency >> policy (beyond numpy and scipy). >> > I still think this is a point we should discuss further ;) > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > -- Daniel F. Moisset - UK Country Manager www.machinalis.com Skype: @dmoisset
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