I've written a couple of C-extensions for a Python service that needed to run in real-time. We started out 100x slower than real-time and managed to make it slightly faster than real-time in a hectic couple of weeks.

The main bottleneck that C-extensions solved for us then was marshaling. Instead of doing something like Numpy --> custom algorithm --> Numpy --> custom algorithm in Python, we moved it all to C. This way, we decreased the number of times we had to marshal data & we reduced the amount of data that needed to be marshaled.

IIRC we gained 10-100x improved performance in all scenarios where we used C-extensions. Before doing so we tried to use Numba, as it seemed to offer a "free lunch", but we never got it to work.

The final cherry on top that let us surpass real-time speed was replacing a graph algorithm with another that had a better time complexity for larger graphs. Before doing that switch, we'd still be faster than real-time for _most_ inputs but would lag behind severely whenever we had a dense input graph come in.