In a forking model that shouldn’t be the case, I guess all the workers are loading and initializing things post-fork that likely could have been accomplished pre-fork?
That said, Python devs are some of the worst engineers I encounter, so it’s not surprising things are being implemented incorrectly.
Last I heard, forking wasn’t a very effective memory-sharing technique on CPython because of the way it does reference counting: if you load things in before you fork, when the children start doing work they update the refcounts on all those pre-loaded objects and scribble all over that memory, forcing most of the pages to be copied anyway.
That said, Python devs are some of the worst engineers I encounter, so it’s not surprising things are being implemented incorrectly.