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I am using Python in Windows. For performance reasons I need certain Python packages built against Intel MKL, most notably numpy. So far I have been installing all packages I use from precompiled installers from http://www.lfd.uci.edu/~gohlke/pythonlibs/. Obviously, manual package management is somewhat inefficient.

I know package managers and distributions exist (pip, Anaconda, Enthought). Is there a way to combine package management for most of the packages with manual install of specific package builds?

So far I have briefly tried pip. I see that after manually updating a package from an exe installer pip freeze still reports the previous version, while Python picks up the new version. So something seems to go at least a bit wrong.

Very related discussions are Anaconda vs. EPD Enthought vs. manual installation of Python and Python packages installation in Windows, but I did not find an answer to my particular question there.

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ilya
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Conda has the ability to convert Golhke installers into conda packages. You'll need to specify the dependencies manually, since the metadata isn't include in the installers. For example, to convert the cvxopt installer to a conda package use:

conda convert cvxopt-1.1.7.win-amd64-py2.7.exe -d 'numpy >=1.8'
asmeurer
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  • Thank you for the reply. In the meanwhile, Gholke changed the installers to whl format which needs pip ot be installed. – ilya Jan 27 '15 at 13:12