Hacker Newsnew | past | comments | ask | show | jobs | submitlogin

OK, perhaps I should have qualified that. It's a good 90% solution for a lot of use cases, although obviously more useful for implementing algorithms in terms of numerical building blocks, than ultra-performance-critical code where you want to write a lot of your own tight inner loops. Is that what you meant?

The parallelisation story isn't great at the moment either, although seems like it has the potential to improve. Still 'sucks' is pretty harsh. For me, looking at how far it's come since I first played with it, I'm impressed. For machine learning, the majority of the building blocks one needs are there, and you get to sit back and put them together using a nice, clean, widely-adopted general purpose programming language. And unlike MATLAB still maintain a decent amount of control over things like memory usage and which BLAS routines it's calling.

Adding bindings for new libraries is more of a pain than it should be though on the occasions where you do really need some fortran or C++ library that doesn't have bindings yet. A language which bridges the gap between high and low levels (not C++!) and has great interop would be very interesting. I guess I'm just hopeful that this kind of thing can be achieved in a general-purpose language (new or existing) which like Python is adopted across the wider software engineering community. Perhaps that's my unreasonable demand to add to their list :)



Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: