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by globular-toast 1866 days ago
You can easily do that by simply running N instances and distributing requests among them. No need for all the complication that would come with removing the GIL.
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klibertp 1866 days ago
And pay in memory for that luxury: when using lots of complex libraries (like in ML) the Python process can eat quite a lot of RAM.
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viraptor 1866 days ago
Since gc.freeze() got implemented (https://docs.python.org/3/library/gc.html#gc.freeze) having forked workers has much lower cost these days. As long as you can load your data pre-fork that is.
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klibertp 1866 days ago
Wow, I missed its introduction. Nice. On a cursory glance Celery doesn't make use of it yet, unfortunately.
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globular-toast 1866 days ago
Yes. Python is not without tradeoffs.
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