[waldrews]

For math/data-sci/ML, multiple (GIL-bound) interpreters per process, with (unsafely) shared data structures, would get us much of the way there - basically multiprocessing without the marshalling and process overhead, at the price of pinky-swearing we won't mutate the shared data. That would enable, for example, calling Python-world utilities in-process from a properly multi-threaded language, which can be used to bootstrap e.g. the Julia or Golang (or C#, or Rust...) ecosystems with all the math that's now locked into Python world. If we want NumPy/Scikit etc. to be accessible via thin wrappers, it's tolerable if the Python layer is slow, but importing the GIL into the host language is too high a price.