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I completely agree that there are many scientific libraries in python which scale up. I was addressing the article which showed a more advanced way to use pytho
by biridir 8y ago
I completely agree that there are many scientific libraries in python which scale up. I was addressing the article which showed a more advanced way to use python with the purpose of making it applicable to large datasets. If you were to implement a method from scratch or scale up to a larger dataset then you'll end up with using numba, numpy and dask. This is completely from a lower level programming perspective to implement and integrate methods rather than pipelining methods from higher level scientific libraries.
Just for some context:
https://www.scipy.org/about.html https://www.scipy.org/about.html
https://www.scipy.org/topical-software.html https://www.scipy.org/topical-software.html
- semi-extrinsic 8y agoI have yet to see a situation where Numba makes real sense, as compared to just dropping down into C(++) or Fortran when you need to do the heavy lifting. Can you give me a good example?