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You are playing with words here: of course you can run multiple python instances to scale your application on multiple-cores, that's a trivial statement. But I
by cdavid 15y ago
You are playing with words here: of course you can run multiple python instances to scale your application on multiple-cores, that's a trivial statement. But I was talking about python the interpreter (more exactly cpython). There are legitimate cases where multi-threading is the natural, elegant solution, and cpython, mostly because of reference counting, prevents that.
- kragen 15y agoCPython prevents you from using shared-state multithreading to scale your application on multiple cores, but it doesn't prevent you from scaling your application on multiple cores. That's not "playing with words". It is indeed unfortunate when the limitations of our platforms force us to contort our code to improve performance, but that is just as true of multithreading as of multi-process programming. The difference between the complexity of the two is small.