On 2/9/2012 3:27 PM, Glenn Linderman wrote: > On 2/9/2012 11:53 AM, Mike Meyer wrote: >> On Thu, 9 Feb 2012 14:19:59 -0500 >> Brett Cannon<brett at python.org> wrote: >>> On Thu, Feb 9, 2012 at 13:43, PJ Eby<pje at telecommunity.com> wrote: >>>> Again, the goal is fast startup of command-line tools that only use a >>>> small subset of the overall framework; doing disk access for lazy imports >>>> goes against that goal. >>>> >>> Depends if you consider stat calls the overhead vs. the actual disk >>> read/write to load the data. Anyway, this is going to lead down to a >>> discussion/argument over design parameters which I'm not up to having since >>> I'm not actively working on a lazy loader for the stdlib right now. >> For those of you not watching -ideas, or ignoring the "Python TIOBE >> -3%" discussion, this would seem to be relevant to any discussion of >> reworking the import mechanism: >> >> http://mail.scipy.org/pipermail/numpy-discussion/2012-January/059801.html "For 32k processes on BlueGene/P, importing 100 trivial C-extension modules takes 5.5 hours, compared to 35 minutes for all other interpreter loading and initialization. We developed a simple pure-Python module (based on knee.py, a hierarchical import example) that cuts the import time from 5.5 hours to 6 minutes." > So what is the implication here? That building a cache of module > locations (cleared when a new module is installed) would be more > effective than optimizing the search for modules on every invocation of > Python? -- Terry Jan Reedy
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