GH-139951: Fix major GC performance regression #140262
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* Count number of actually tracked objects, instead of trackable objects. This ensures that untracking tuples has the desired effect of reducing GC overhead * Do not track most untrackable tuples during creation. This prevents large numbers of small tuples causing execessive GCs.
markshannon
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needs backport to 3.14
eendebakpt
reviewed
Oct 17, 2025
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I'm not sure I get what android (x86_64) fails.
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I'm not at all familiar with the garbage collector, but one of the ways that Android differs from the other platforms is that it runs all the test suite serially in a single process. |
sergey-miryanov
approved these changes
Oct 21, 2025
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Should we redo the benchmarks to see how the final version impacts performance? Maybe we can run it on https://github.com/faster-cpython/benchmarking-public (but I don't know how). |
efimov-mikhail
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Oct 21, 2025
Misc/NEWS.d/next/Core_and_Builtins/2025-10-17-18-03-12.gh-issue-139951.IdwM2O.rst
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Thanks @markshannon for the PR 🌮🎉.. I'm working now to backport this PR to: 3.14. |
miss-islington
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Oct 21, 2025
* Count number of actually tracked objects, instead of trackable objects. This ensures that untracking tuples has the desired effect of reducing GC overhead * Do not track most untrackable tuples during creation. This prevents large numbers of small tuples causing execessive GCs. (cherry picked from commit 0c01090ad957de4625f504ce4f29df0a05d09fba) Co-authored-by: Mark Shannon <[email protected]>
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GH-140423 is a backport of this pull request to the 3.14 branch. |
markshannon
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Oct 23, 2025
…-140262 (GH-140447) * Count number of actually tracked objects, instead of trackable objects. This ensures that untracking tuples has the desired effect of reducing GC overhead * Do not track most untrackable tuples during creation. This prevents large numbers of small tuples causing execessive GCs.
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This PR:
For the example in the original report this makes performance on main a bit better than 3.13.
Benchmarking results show this is about neutral on performance otherwise.