<div dir="ltr"><br><div class="gmail_extra"><br><div class="gmail_quote">2017-07-20 19:23 GMT+02:00 Victor Stinner <span dir="ltr"><<a href="mailto:victor.stinner@gmail.com" target="_blank">victor.stinner@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><span class="">2017-07-20 19:09 GMT+02:00 Cesare Di Mauro <<a href="mailto:cesare.di.mauro@gmail.com">cesare.di.mauro@gmail.com</a>>:<br>
> I assume that Python loads compiled (.pyc and/or .pyo) from the stdlib. That's something that also influences the startup time (compiling source vs loading pre-compiled modules).<br>
<br>
</span>My benchmark was "python3 -m perf command -- python3 -c pass": I don't<br>
explicitly remove .pyc files, I expect that Python uses prebuilt .pyc<br>
files from __pycache__.<br>
<span class="HOEnZb"><font color="#888888"><br>
Victor<br>
</font></span></blockquote></div><br></div><div class="gmail_extra">OK, that should be the best case.</div><div class="gmail_extra"><br></div><div class="gmail_extra">An idea to improve the situation might be to find an alternative structure for .pyc/pyo files, which allows to (partially) "parallelize" their loading (not execution, of course), or at least speed-up the process. Maybe a GSoC project for some student, if no core dev has time to investigate it.</div><div class="gmail_extra"><br></div><div class="gmail_extra">Cesare</div></div><div id="DAB4FAD8-2DD7-40BB-A1B8-4E2AA1F9FDF2"><br> <table style="border-top:1px solid #d3d4de">
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