On Fri, Sep 30, 2016 at 9:13 AM, Stephan Hoyer <sho...@gmail.com> wrote:
> One way to do this is to move to vendorized dependencies into an submodule > of numpy itself (e.g., sklearn.externals.joblib, though maybe even a little > more indirection than that would be valuable to make it clear that it isn't > part of NumPy public API). This would avoid further enlarging the set of > namespaces we use. > > In any case, I'm perfectly OK with using something like npy_tempita > internally, too, as long as we can be sure that we're using NumPy's > vendorized version, not whatever version is installed locally. We're not > planning to actually install "npy_tempita" when installing numpy (even for > dev installs), right? > > > The only thing in the tools directory included in a source distribution is the swig directory. Tempita is only currently used by the cythonize script also in the tools directory. The search path for the cythonize script is 1) installed modules, 2) modules in same directory, which is why it might be good to rename the module npy_tempita` so that is always the one used. <snip> Chuck
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