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https://github.com/faster-cpython/ideas/wiki/Python-3.12-Goa... is interesting too.
> Python currently has a single global interpreter lock per process, which prevents multi-threaded parallelism. This work, described in PEP 684, is to make all global state thread safe and move to a global interpreter lock (GIL) per sub-interpreter. Additionally, PEP 554 will make it possible to create subinterpreters from Python (currently a C API-only feature), opening up true multi-threaded parallelism.
Very basic question: in a world where a Python program can spin up multiple subinterpreters, each of which can then execute on a separate CPU core (since they don't share a GIL), what will the best mechanisms be for passing data between those subinterpreters?
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Looks like it's still active to me:
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25% number is from pyperformance benchmark suite, which you can replicate. Whether pyperformance is representative benchmark suite is another question.
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Yes, it is released [1]. This allows you to access it from multiple thread in the same interpreter though, so I still don't understand robertlagrant's question.
[1]: https://github.com/python/cpython/blob/4b81139aac3fa11779f6e...
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