(Replying to PARENT post)

I have personally gotten a lot of mileage from just writing the compute heavy parts of my code in C++ and exposing it to Python with a tool like PyBind11 [1] or NumpyEigen [2]. I find tools like numba and cython to be more trouble than they're worth.

[1] https://github.com/pybind/pybind11 [2] https://github.com/fwilliams/numpyeigen

👤fwilliams🕑3y🔼0🗨️0

(Replying to PARENT post)

I prototype in python or whatever, then, if the project survives into market and has legs I either buy more hardware or rewrite the expensive parts in C++.

Reduces calendar time, risk, cost. And I'm likely to make better decisions once the code and market is better understood after the prototype is tested under real world conditions and the requirements have changed (like they always seem to do).

👤netjiro🕑3y🔼0🗨️0

(Replying to PARENT post)

+1 for pybind11. I wrote python bindings using pybind11 for two C++ based simulators: MOOSE and Smoldyn. It was surprisingly easy to use given how badly Python C-API and c++ tooling suck. Though you have to create binary wheels for every version of python and platform separately.

👤dilawar🕑3y🔼0🗨️0