[riri-au]

Agreed, shared programming is an immensely useful feature for numerical programming, including data science and machine learning. Lots of people will say that those should be written in C++, but I think the rise of machine learning & data science in high level languages argues against their point.

[bhntr3]

Yeah. Python is pretty standard now. To implement high throughput scoring on models written in python, I have to run multiple processes with one copy of the python model for each process. For large models like random forests, this can eat up a lot of memory.

Ideally, it would be a single model in memory with access from multiple threads. But that won't work right now cause GIL.