And it's worse if your python libraries might be on network storage - like in a user's homedir in a shared compute environment.

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dekhn 4 days ago | parent [-]

Exactly this. The time to start python is roughly a function of timeof(stat) * numberof(stat calls) and on a network system that can often be magnitudes larger than a local filesystem.

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zahlman 4 days ago | parent [-]

I do wonder, on a local filesystem, how much of the time is statting paths vs. reading the file contents vs. unmarshaling code objects. (Top-level code also runs when a module is imported, but the cost of that is of course highly module-dependent.)

	▲	dekhn 4 days ago \| parent [-]
		Maybe you could take the stat timings, the read timings (both from strace) and somehow instrument Python to output timing for unmarshalling code (or just instrument everything in python). Either way, at least on my system with cached file attributes, python can startup in 10ms, so it's not clear whether you truly need to optimize much more than that (by identifying remaining bits to optimize), versus solving the problem another way (not statting 500 files, most of which don't exist, every time you start up).