Support infer types involving dataclass fields#38548
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Summary of ChangesHello, 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 enhances Apache Beam's type inference system to correctly handle fields within Python dataclasses, particularly when they are accessed within lambda functions. This addresses a limitation where dataclass type hints were not preserved during type inference, leading to fields being typed as Highlights
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Code Review
This pull request enhances the Apache Beam type inference system by adding support for Python dataclasses. The changes include updating the _getattr opcode handler to resolve field types from dataclass definitions and adding unit tests to verify type inference for dataclass fields and row mappings. A review comment identifies an improvement opportunity in opcodes.py to remove an unnecessarily restrictive class check, allowing the inference engine to correctly handle both dataclass classes and instances.
| return Const(BoundMethod(func, o)) | ||
| elif isinstance(o, row_type.RowTypeConstraint): | ||
| return o.get_type_for(name) | ||
| elif inspect.isclass(o) and dataclasses.is_dataclass(o): |
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The inspect.isclass(o) check is unnecessarily restrictive. dataclasses.is_dataclass(o) returns True for both dataclass classes and instances. Removing the class check allows the type inference engine to correctly resolve fields when it encounters a dataclass instance (for example, when an instance is wrapped in a Const object during the inference process).
| elif inspect.isclass(o) and dataclasses.is_dataclass(o): | |
| elif dataclasses.is_dataclass(o): |
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R: @jrmccluskey (Python typehinting) |
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After #22085, dataclass is a supported type for Beam Row. However the original stackoverflow example in #20738 still missing one part from working that is dataclass's typehints do not survive lambda. We get all fields as "any".
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