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> Numpy and Scipy are so mature in this respect it is difficult to compete with them.

Tell me about it. What I'd give to have something equivalent for Objective-C (or certain other languages too, e.g. Julia). I'm looking at PyObjC as a stop-gap solution for now, but it sure adds complexity to a project.

Edit: Since SciPy is BSD-licensed and presumably mostly C behind-the-scenes, perhaps there's potential for a group to try and package it up for other languages? I have no idea how large an undertaking like that would be...



At least with Julia's PyCall, you don't need to sacrifice losing access to the Python stack. You can work with NumPy arrays without needing to copy data around.


Thanks! I didn't realise this. This looks really useful.


The author of numpy is making the next generation numpy, blaze (http://blaze.pydata.org/docs/index.html). There're also many python project, such like numexpr, blz, numpy aim to boost scientific computing in python. Having a strong community, I think python might dominate the data analysis in the nearly future.


iOS and OS X ship with Accelerate.framework, which include implementations of BLAS and LAPACK: https://developer.apple.com/library/mac/documentation/Accele...


Thanks – sadly, for myself, the algorithms I need aren't part of Accelerate (I've most recently been using SciPy for its spatial algorithms). The benefit of SciPy is that there's just so much breadth, along with an easy way of moving data between different parts of SciPy, and good documentation too. There's just nothing else like it that I know of.


GNU Scientific Library? I've not benchmarked it against Numpy/Scipy, but there is quite a bit of overlap in functionality.


It looks great. Sadly doesn't have the specific tools I need, and regardless the license is prohibitive if I ever wanted to publish something on the App Store (regardless of if I open sourced it myself), so it's not really an option. Not that that's GSL's fault of course.




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