Introduce Beartype Dependency for Type Checking - #35899
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Summary of Changes
Hello @jrmccluskey, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request integrates the beartype library into Apache Beam's Python SDK to enhance runtime type checking capabilities. The primary change involves migrating existing type consistency checks from issubclass() to beartype.door.is_subhint(), which is a foundational step towards more comprehensive type validation. The necessary beartype dependency has also been added to the project's setup configuration.
Highlights
- Dependency Management: The
beartypelibrary, specifically version0.21.0to0.22.0, has been added as a new dependency in thesetup.pyfile. - Type Checking Logic Update: The
is_consistent_withfunction insdks/python/apache_beam/typehints/typehints.pynow utilizesbeartype.door.is_subhint()instead of the built-inissubclass()for type consistency checks. - Error Handling Improvement: A
try-exceptblock has been introduced around theis_subhint()call to robustly handle any exceptions that might occur during the type consistency evaluation.
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Assigning reviewers: R: @claudevdm for label python. Note: If you would like to opt out of this review, comment Available commands:
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R: @damccorm since Claude is out |
| try: | ||
| return is_subhint(sub, base) | ||
| except (BeartypeDoorException): | ||
| return False |
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Should we gate this on a pipeline option so that users can disable this for now if they run into issues? Could be part of
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I was thinking we would do that eventually once we were getting to where we'd skip things like normalize() calls, but considering that we'd need to do the plumbing for that anyway I'm not opposed to it. Seeing exactly how best to plumb that through will take a bit, but the bottom level having a use_beartype boolean parameter is a good starting point. As written now it's just off with no way to actually enable it, I will look at the actual pipeline option next (can do that either in this PR or in a follow-up, it's going to be next week either way)
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Sounds good - I'll leave it up to you whether you'd like it in this PR or a future one. To be clear, once we have a flag with the ability to turn this off I have no problem with defaulting to it on (assuming it passes test suites)
damccorm
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Current state is good with me, or we can add a flag and flip the default to on
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Game plan around this for ease more than any thing else is to get this in as-is to keep the internal import as simple as possible. I don't anticipate the beartype route here breaking anything internally but if this way, if there is a problem, it can be handled after getting the new dependency set up correctly. Plumbing through an option and changing the default after that seems like a reasonable choice. |
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SGTM, thanks |
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Introduces Beartype into Beam Python for type checking as discussed in https://s.apache.org/beam-python-third-party-type-checking, uses the
is_subhint()method overis_subclass()as a first step towards migrating more checks to Beartype.Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:
addresses #123), if applicable. This will automatically add a link to the pull request in the issue. If you would like the issue to automatically close on merging the pull request, commentfixes #<ISSUE NUMBER>instead.CHANGES.mdwith noteworthy changes.See the Contributor Guide for more tips on how to make review process smoother.
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