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My point was that even if you copy the numpy protocol, you still have huge projects that depend on c-extensions that you wouldn't want to port. Pandas is one,
by mangecoeur 11y ago
My point was that even if you copy the numpy protocol, you still have huge projects that depend on c-extensions that you wouldn't want to port.
Pandas is one, others include scikit-learn, scikit-image, Astropy, Bioinformatics libraries, stats libraries, etc... which all have heavy C/Cython use and depend to varying degrees on the Python C-api. Porting NumPy barely scratches the surface of scientific python.
- dalke 11y agoBiopython runs on pypy. It also runs under Jython. While it has C use, it is not "heavy" C use. Going on a tangent, and though I realize it's a lost battle, I wish people would stop saying that NumPy is the base of scientific programming in Python. As Biopython shows, it isn't required for at least some of bioinformatics. My own research[1] deals with chemical graphs, and NumPy/SciPy/etc. are nearly irrelevant to that research. [1] For example, given a set of 100 structures, what is the largest substructure (based on the number of bonds) which is in at least 90 of the structures?