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Performance improvements to counter context.clone slowdown #1009
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e133c7c
Add limit to the total number of nodes inferred per context
nelfin 86b924c
Add global inference cache
nelfin 8efd924
Update changelog
nelfin 543d798
Update safe_infer to catch StopIteration
nelfin 11638f0
Merge branch 'master' into wip/performance
cdce8p 7e3fd68
Merge branch 'master' into wip/performance
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If i understand well, here we will store every inferred node in a global variable that will exists throughout the life of the program.
It will definitely allow cpu time sparing but what about memory consumption?
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Is the number of inferred node limit sufficient for the speed up ? There are really big code bases using pylint and having a cache can affects them to the point it's not possible to run pylint on them at all.
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Your understanding is correct. It could theoretically grow without bound, but I suppose many other parts of astroid (such as
astroid.MANAGER.astroid_cache) can as well. I regularly see pylint/astroid runs in the hundreds of MiB, but without a benchmark, I'm not sure there's a meaningful way to answer this question.I tried running pylint (commit 9361fa0630ce920081b57865be7882a39e9da1e3) on itself with and without these astroid changes.
With
wip/performance(0d7d798):Without (d3fea8f):
So memory usage (max RSS) went down from 235MB -> 231MB
They address different problems: the inferred node limit is to stop pathological cases, like really large files. The inferred node cache helps with re-use, like when scanning a package with a lot of files. The main problem I saw with the inference cache was that it was re-built from scratch for every node so the hit-rate was very low, and cloning it introduced a large number of small copies which was inefficient time-wise. In fact, it was so inefficient that just removing it altogether produces a small but noticeable (~2%) speed-up on astroid 2.5.6 (middle of 3 runs):
astroid-2.5.6 (36dda3f):
With no-cache.patch applied:
no-cache.patch: