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Between ccall, PyCall and RCall you can access a huge range of existing code from inside Julia. So the libraries issue is moot. Having used both, I much prefer
by conjectures 10y ago
Between ccall, PyCall and RCall you can access a huge range of existing code from inside Julia. So the libraries issue is moot.
Having used both, I much prefer Julia to python+cython. Three examples: multiprocessing is much less restrictive, there's no edit-compile loop so development is quicker, and no awkward pyx/pxd system. If you have to go deep with a cython project, you basically end up writing C, and that's slow - not cython's fault, it's a great tool, just a limitation of that platform.
- Derbasti 10y agoI don't like Cython very much. I much prefer CFFI or Numba, which have none of your stated problems.
- conjectures 10y agoA quick look at the numba docs suggests that it doesn't parallelise any better than regular python - so there's one of my problems. Numba also seems to be restricted in the functionality it offers, e.g. currently looks like no user defined types so good for hot loops but not your whole codebase. If you touch the python C API it suggests it can't do full JIT compilation, i.e. sounds like this would happen with any C-extension library code outside the range of supported numpy features. No strings?... I'd love to be shown wrong about this.