Hi!
Currently, I try to fix several memory leaks, namely at trac ticket
#715, #11521, #12215 and #12313. The common idea is: Use weak
references for the caches (in particular for caching coercions and
actions), so that stuff can be collected once it is no more used.
But of course it would be easy to overdo it. For example, with the
current patch from #715, the following computation involves the
creation of 481 actions, while it only needs 320 actions without the
patch:
E = J0(46).endomorphism_ring()
g = E.gens()
So, in that example, actions seem to be garbage collected although
they will be used again. However, other examples involving elliptic
curves (e.g., EllipticCurve('960d1').prove_BSD()) are fine, the same
number of actions is created with or without the patch.
Now I wonder what you would recommend to do?
* Is there a Python package that provides "soft" references (that is
stronger than a weak reference)? That would be a good solution, but
google has not been able to find it.
* Should I try to trace down "E.gens()" and add a reference to some
parent in an appropriate location, so that the 160 actions in the
example above are prevented from being collected? That would solve the
particular problem, but there is no guarantee that it is the only
example of that type.
* Should I modify my weak version of
`sage.structure.coerce_dict.TripleDict` so that strong references are
used in the first place, but so that the oldest references are
"weakened" when the dictionary grows bigger than a certain threshold?
That is likely to fix the example above and other types of examples as
well, but may create an overhead.
* Should I consider it as the price to pay for fixing memory leaks?
Best regards,
Simon
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