My guess is that this has to do with disk access? With venvs running on
a ramdisk I get almost identical times, particularly if I run it a
couple of times:
15:39$ time python -c "from matplotlib import pyplot; import matplotlib;
15:36$ time python -c "from matplotlib import pyplot; import matplotlib;
Both of those times fluctuate and despite what I pasted, 1.4.3 seems to
be faster more often than not (but by hundredths of seconds).
Running this command several times seems the later runs seem to be
faster than the first time.
Running multiple times one does see variations, but not large ones
compared to the factor of two I am getting between the versions. My
environment is a virtualenv in a VMWare linux VM on a Mac, with the disk
access via VMWare's hgfs. The Mac has SSD, so the physical disk access
is quick; and at least some things will be retrieved from cache on
multiple runs. The tests were made using the same VM and the same
virtualenv, so the only thing that changed was whether I had just build
mpl from 1.4.3 or from master.
Now I have tried the experiment on the OSX side, and I get very similar
results, except that all the times are a little bit longer than on the
(python3)efiring at manini2:~/work/programs/py/ladcp_netcdf$ time python -c
"from matplotlib import pyplot; import matplotlib;
(testmpl3)efiring at manini2:~/work/programs/py/mpl/matplotlib$ time python
-c "from matplotlib import pyplot; import matplotlib;
I guess the fact that the linux VM on OSX is faster than native OSX
points to disk access in some form--maybe there is more caching on the
linux side--but the puzzle remains: why the factor of two difference
between 1.4.3 and master in these two reasonably normal configurations?
On 2015/09/08 9:51 AM, Thomas Caswell wrote:
On Tue, Sep 8, 2015 at 3:30 PM Eric Firing <efiring at hawaii.edu > <mailto:efiring at hawaii.edu>> wrote:
time python -c "from matplotlib import pyplot"
On a linux VM with Py 3.4 the user time is around
0.25 s for 1.4.3
0.5 s for master
That's quite a difference. Can anyone else reproduce this? Any ideas
as to what is causing the slowdown?
In both tests the backend was tkagg, so the difference was not a matter
of importing different gui toolkits.
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