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I'll concede the point that pip can't handle non-python packages. But it can handle side by side versioning by way of virtualenv. But if I need a specific ver
by olympus 14y ago
I'll concede the point that pip can't handle non-python packages. But it can handle side by side versioning by way of virtualenv. But if I need a specific version for a project I just install that version into my virtualenv's /bin/ folder and that becomes the version used whenever I activate that virtualenv. It's super easy and doesn't add to the cluttered package manager ecosystem.
- jofer 14y agoYeah, I didn't mean to imply that pip didn't handle multiple versions (though my comment certainly reads that way). I intended that to be a comparison of "full-blown" package managers with conda. (As were the user-home-directory and cross-platform comments.) At any rate, pip is really fantastic, and I use it constantly. However, being able to handle non-python dependencies is huge in the scientific world, where lots of python packages have a _lot_ of non-python dependencies. Widely-used packages (e.g. numpy, matplotlib, scipy, etc) don't have very many, and are well supported, but a lot of the less widely-used packages can be a real pain to build. I'm excited about it because conda has the potential to replace a couple of virtual machines I currently keep around for this purpose. I'll certainly admit it's not a majority use-case, but if it works as advertised it will be very useful for me, at any rate.