perf: try to cache inner contexts of overloads#19408
perf: try to cache inner contexts of overloads#19408sterliakov wants to merge 10 commits intopython:masterfrom
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Now this is what I wanted to see: no behavior changes and This is not ready for code review, removing draft status to get some feedback on the idea itself. I do not particularly like using |
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JukkaL
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I think we need something along these lines, but it may be more complicated than this to maintain 100% compatibility with non-cached behavior. I suspect that we may need to consider the binder and possibly cache generated errors as well. There may be some other relevant state that is kind of implicit in the type checker. I can look into this in more detail and reason through all possible issues, but it will take some effort.
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That's why I only added caching to Binder is indeed an implicit dependency, but it's still OK within a parent overload: re-accepting an I'll add the changes mentioned above in a few hrs, but frankly my main "wtf" here is using IDs as cache keys. |
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According to mypy_primer, this change doesn't affect type check results on a corpus of open source code. ✅ |
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Still quite nice in a single sample: |
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FWIW I am trying a (much) higher-level caching, like caching |
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Superseded by #19505 which implements a superset of this functionality (but only for some expressions), further attempts should add other expressions there instead of rolling out another cache on top. |
Improves #14978 and marginally improves nested overloads checking in general. This is not ready for review, but I would appreciate any in-progress feedback on the idea itself.
If I understand correctly, this change should not change any behavior at all:
infer_arg_types_in_empty_contextis almost pure.This change halves
colourcheck time.Another very similar problem arises when checking overloaded binary operations (like in #14978), they do not translate directly into a series of overloads check but repeat the whole process for every node instead. Improving overload checking helps with that, but the result is still slow beyond reasonable. I'll try to push this further later in a separate PR.