> `multiprocessing` works fine for serving HTTP requests
Not if you use Windows, then it's a mess. I have a suspicion that people who say that the multiprocessing works just fine never had to seriously use Python on Windows.
Probably a very small minority of Python codebases run on Windows, no? That's my impression. It would explain why so many people are unaware of multiprocessing issues on Windows. I've never ran any serious Python code on windows...
Adding on to the other comment, multiprocessing is also kinda broken on Linux/Mac.
1. Because global objects are refcounted, CoW effectively isn't a thing on Linux. They did add a way to avoid this [0], but you have to manually call it once your main imports are done.
2. On Mac, turns out a lot of the system libs aren't actually fork-safe [1]. Since these get imported inadvertently all the time, Python on Mac actually uses `spawn` [2] -- so it's roughly as slow as on Windows.
I haven't worked in Python in a couple years, but handling concurrency while supporting the major OSes was a goddamn mess and a half.
Re (1), are there publicly documented cases with numbers on observed slowdowns with it?
I see this mentioned from time to time, but intuitively you'd think this wouldn't pose a big slowdown since the system builtin objects would have been allocated at the same time (startup) and densely located on smaller nr of pages. I guess if you have a lot of global state in your app it could be more significant.
Would also be interesting to see a benchmark using hugepages, you'd think this could solve remaining perf problems if they were due to large number of independent CoW page faults.
* A lack of fork() makes starting new processes slow.
* All Python webservers that somewhat support multiprocessing on Windows disable the IOCP asyncio event loop when using more than one process (because it breaks in random ways), so you're left with the slower select() event loop which doesn't support more than 512 connections.
