3 ms·

Alternatives? I really have never heard of any serious alternatives if you actually need the speed and ubiquity of numpy. Maybe if you're willing to leave Pytho

Alternatives? I really have never heard of any serious alternatives if you actually need the speed and ubiquity of numpy. Maybe if you're willing to leave Python behind and go to C, but frankly within the Python ecosystem there just isn't a realistic alternative if you even remotely need efficient numerical processing.

dunefox 6y ago
Julia is the best 'alternative', imho it's much better. You don't need to use C to get performance.
- thorakites 6y ago
  Julia is definitely a fair counterpoint to my comment about C, but I don't think it really has comparable ubiquity to numpy + Python and C/C++ in the computational science/numerical computing communities. What is nice about ubiquity is that if I need to use a rather esoteric numerical technique for research, odds are there are at least prototypes for it already made in numpy + Python or C/C++, if not a fully-fledged, well tested package for it. Julia might be catching up there. I hope so, because I do think my area of computational science would benefit from not only relying on 1 or 2 programming language ecosystems for 99% of all work.
  - dunefox 6y ago
    > odds are there are at least prototypes for it already made in numpy + Python or C/C++, if not a fully-fledged, well tested package for it. Odds are that there is one in Julia as well - if not only in Julia. Also, with PyCall you can just seamlessly use any Python library. So, use Julia - the better language for scientific programming - and use Python libraries where needed. This is one of the reasons I'm investing time into Julia, especially for deep learning and natural language processing.
ulucs 6y ago
Speed is not really an argument against k though, there are cases where it's decidedly faster than C
- thorakites 6y ago
  Sure, I was speaking in terms of within the Python ecosystem. I just use C as an example because it's the main alternative for numerical computing in my field.

dunefox 6y ago

Julia is the best 'alternative', imho it's much better. You don't need to use C to get performance.

thorakites 6y ago
Julia is definitely a fair counterpoint to my comment about C, but I don't think it really has comparable ubiquity to numpy + Python and C/C++ in the computational science/numerical computing communities. What is nice about ubiquity is that if I need to use a rather esoteric numerical technique for research, odds are there are at least prototypes for it already made in numpy + Python or C/C++, if not a fully-fledged, well tested package for it. Julia might be catching up there. I hope so, because I do think my area of computational science would benefit from not only relying on 1 or 2 programming language ecosystems for 99% of all work.
- dunefox 6y ago
  > odds are there are at least prototypes for it already made in numpy + Python or C/C++, if not a fully-fledged, well tested package for it. Odds are that there is one in Julia as well - if not only in Julia. Also, with PyCall you can just seamlessly use any Python library. So, use Julia - the better language for scientific programming - and use Python libraries where needed. This is one of the reasons I'm investing time into Julia, especially for deep learning and natural language processing.

ulucs 6y ago

Speed is not really an argument against k though, there are cases where it's decidedly faster than C

thorakites 6y ago
Sure, I was speaking in terms of within the Python ecosystem. I just use C as an example because it's the main alternative for numerical computing in my field.