Hacker News Reader

Python with Numpy/Scipy. The Python there is just calling high performance fortran libraries.

It's not quite that simple. The core packages wrap fortran or C code but then additional packages are built on that. Going by the github breakdowns Pandas, SymPy or Jupyter are pretty much pure Python, matplotlib is 90% Python 10% C++ (though the Python ratio is probably skewed up by the in-repo examples).

And that high-performance Fortran or C code is at the root of so much scientific computing is an issue in Go considering the overhead of cgo calls.

Jupyter and matplotlib aren't designed to actually do any calculation (they are just for communicating results) so it doesn't make sense for them to be written in C. Pandas has a ton of pure Python code, but if you dig through the layers of abstraction, all of the core algorithms are implemented in cython or make calls to numpy (which is calling C code).

Bottom line, when you're using an established Python scientific computing library to do numerical calculations, you're calling C (or maybe Fortran) routines.

Reply on news.ycombinator.com