Why would you even want a no-GIL Python? Java and C showed how much more effort it takes to maintain slower thread safe code for no real benefit. Parallelize at the fork level or at the isolated numeric library level.
> Parallelize at the fork level IPC is a PITA, and orchestrating processes is even worse. > or at the isolated numeric library level Not everything I want to parallelise in python runs in numpy. Simple example: WebService Backends. I have a 64 core server running a Werkzeug/Gunicorn application. The Service is mostly doing CPU bound tasks (data aggregation and analysis), so asyncio is pointless. What happens is, it r…
I think, rightfully, the concern is people who will try to use this incorrectly causing major bloat to CPython.