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I'm getting seriously frustrated at how slow python startup is. Just importing more or less basic modules takes a second, since python runs down the sys.path looking for matching files (and generating 4 stat() calls - ["foo", "foo.py", "foo.pyc", "foo.so"] - for each check). For a complicated project environment, with tons of different directories, this can take around 5 seconds -- all to run a script that might fail instantly.
Do folks have suggestions for how to speed up this process? For instance, one hack I've seen is to set the LD_PRELOAD_32 environment variable to a library that caches the result of ENOENT calls (e.g. failed stat() calls) between runs. Of course, this has all sorts of problems (potentially confusing non-python programs, negative caching, etc.).
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Imports inside class definitions or inside functions/methods are not “top level” and are never lazy. Dynamic imports using __import__() or importlib. import_module() are also never lazy.
__loader__ is an attribute that is set on an imported module by its loader. Accessing it should return the loader object itself. In Python versions before 3.3, __loader__ was not set by the built-in import machinery. Instead, this attribute was only available on modules that were imported using a custom loader.
zipping up as many pyc files as feasible (with proper directory structure for packages), and putting that zipfile as the very first entry in sys.path (on the best available local disk, ideally) can speed up startup times a lot.
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