On Jan 15, 2016 10:23 AM, "Chris Barker" <chris.bar...@noaa.gov> wrote: > [...] > So here is the problem I want to solve: > > > pip install numpy scipy matplotlib scikit-learn scikit-image pandas h5py > > last I checked, each of those is self-contained, except for python-level dependencies, most notably on numpy. So it doesn't' help me solve my problem. For instance, I have my own C/C++ code that I'm wrapping that requires netcdf (https://github.com/NOAA-ORR-ERD/PyGnome), and another that requires image libs like libpng, libjpeg, etc.( https://github.com/NOAA-ORR-ERD/py_gd) > > netcdf is not too ugly itself, but it depends on hdf5, libcurl, zlib (others?). So I have all these libs I need. As it happens, matplotlib probably has the image libs I need, and h5py has hdf5 (and libcurl? and zlib?). But even then, as far as I can tell, I need to build and provide these libs myself for my code. Which is a pain in the @%$ and then I'm shipping (and running) multiple copies of the same libs all over the place -- will there be compatibility issues? apparently not, but it's still wastes the advantage of shared libs, and makes things a pain for all of us. > > With conda, on the other hand, I get netcdf libs, hdf5 libs, libpng, libjpeg, ibtiff, and I can build my stuff against those and depend on them -- saves me a lot of pain, and my users get a better system.
Sure. Someone's already packaged those for conda, and no one has packaged them for pypi, so it makes sense that conda is more convenient for you. If someone does the work of packaging them for pypi, then that difference goes away. I'm not planning to do that work myself :-). My focus in these discussions around pip/pypi is selfishly focused on the needs of numpy. pip/pypi is clearly the weakest link in the space of packaging and distribution systems that our users care about, so improvements there raise the minimum baseline we can assume. But if/when we sort out the hard problems blocking numpy wheels (Linux issues, windows issues, etc.) then I suspect that we'll start seeing people packaging up those dependencies that you're worrying about and putting them on pypi, just because there won't be any big road blocks anymore to doing so. -n
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