travisoliphant

10 ms·

1. 61.▲
   by travisoliphant 13y ago

   This is exactly what Numba is designed to help with. And it already works extremely well for such cases. Numba lets you have ease of use (un-typed containers) and speed (with typed-containers) in the same run-time and the same syntax. H
2. 62.▲
   by travisoliphant 14y ago

   I wish this were true, I really do, but it's just not true. Maybe for python-only packages. But, for the myriad of python extensions necessary for Scientific Computing with Python, pip and virtualenv are not enough. We think conda is a us
3. 63.▲
   by travisoliphant 14y ago

   Cython is helpful, but you have to spell out a lot of type-information that is not specifically necessary. You might also try Numba --- easiest way to get it is via Anaconda CE or Wakari. Both at http://continuum.io
4. 64.▲
   by travisoliphant 14y ago

   I think the article tagline would be better "Domain Specific Languages for data analysis". Fortunately, the article does mention Python which is critical because new people might not recognize just how prevalent Python is for solving dat
5. 65.▲
   by travisoliphant 14y ago

   Actually some NumPy calls can be made inside the numba-compiled function as there is nascent support for the NumPy C-API --- it translates the call to a C-call. In the future, we want to support all Python, but not necessarily optimized ---