autophagy opened a new pull request, #29498:
URL: https://github.com/apache/flink/pull/29498
## What is the purpose of the change
This change extends the type inference for `TypedDict` to other composite
classes, specifically `dataclass`, `typing.NamedTuple` and fixed length
`tuple`, so that they are then mapped to a corresponding `ROW`.
For both `TypedDict` and `dataclass`, the column names are taken from the
fields. For `tuple`, it instead uses a positional naming of `_1`, `_2`, etc. In
the DataFrame API, an explicit UDTF `return_dtype=Tuple[...]` now produces the
same positional `f0`/`f1` fields as an annotated `Iterator[Tuple[...]]`.
This PR also has a behaviour change in that an empty `TypedDict` used to
infer to a `ROW<>`, and now it rejects these, matching the java behaviour when
trying to infer a structured type from a class with no fields.
## Brief change log
- Extended Python type inference for Dataframe API to support `dataclass`,
`NamedTuple` and `tuple` types.
- Changed behaviour when inferring from a `TypedDict` with no fields so that
they are rejected.
## Verifying this change
This change added tests and can be verified as follows:
- Added tests to cover the new behaviour in both the `test_typehints` tests
and across the dataframe api's udf/udtf etc tests.
## Does this pull request potentially affect one of the following parts:
- Dependencies (does it add or upgrade a dependency): (no)
- The public API, i.e., is any changed class annotated with
`@Public(Evolving)`: (no)
- The serializers: (no)
- The runtime per-record code paths (performance sensitive): (no)
- Anything that affects deployment or recovery: JobManager (and its
components), Checkpointing, Kubernetes/Yarn, ZooKeeper: (no)
- The S3 file system connector: (no)
## Documentation
- Does this pull request introduce a new feature? (yes)
- If yes, how is the feature documented? (not applicable)
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