Hi Armin,
On 18-03-16 18:52, Armin Rigo wrote:
Hi Pim,
On 18 March 2016 at 15:08, Pim van der Eijk (Lists)
<li...@sonnenglanz.net> wrote:
- Memory use continues to grow up to over 80% at which time where my
laptop
starts swapping, whereas with CPython usage is never more than 4%.
This is more annoying. Can you give us a way to reproduce this?
It already happens with the script I attached to the original issue, which
you already have:
https://bitbucket.org/pypy/pypy/issues/2260/pypy-500-dumps-core-with-lxml-360
Ok, partially reproduced. With CPython it grows continously too, but
only up to 1.2GB and then it finishes. With PyPy it grows faster up
to 22GB. If I add some "gc.collect()" executed every few seconds,
then PyPy only grows up to 1.7GB.
I added "add_memory_pressure=True" to some chosen mallocs inside
cpyext, and it seems to be enough to fix the problem. Now PyPy grows
up to 1.7GB even without any gc.collect(). Yay! (changeset
9137853fd0ec, grafted to release-5.x too)
I retested and confirm that the library works and memory use is now like
CPython, which is great. It is still slower than CPython, for reasons
you explained before, but that is because my test script heavily uses
of lxml. In larger applications where lxml processing is a smaller part
of the overall functionality, the PyPy speed-up of regular Python code
could well compensate for this.
Many thanks,
Pim
A bientôt,
Armin.
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