On 2/9/2012 7:19 PM, PJ Eby wrote:
Right. It was the part of the post that mentioned that all they sped up
was knowing which directory the files were in, not the actual loading of
bytecode. The thought then occurred to me that this could perhaps be
applied to normal importing, as a zipimport-style speedup. (The
zipimport module caches each zipfile directory it finds on sys.path, so
failed import lookups are extremely fast.)
It occurs to me, too, that applying the caching trick to *only* the
stdlib directories would still be a win as soon as you have between four
and eight site-packages (or user specific site-packages) imports in an
application, so it might be worth applying unconditionally to
system-defined stdlib (non-site) directories.
It might be worthwhile to store a single file in in the directory that
contains /Lib with the info inport needs to get files in /Lib and its
subdirs, and check that it is not outdated relative to /Lib. Since in
Python 3, .pyc files go in __pycache__, if /Lib included an empyty
__pycache__ on installation, /Lib would never be touched on most
installations. Ditto for the non-__pycache__ subdirs.
--
Terry Jan Reedy
_______________________________________________
Python-Dev mailing list
Python-Dev@python.org
http://mail.python.org/mailman/listinfo/python-dev
Unsubscribe:
http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
