auroflow opened a new pull request, #28974:
URL: https://github.com/apache/flink/pull/28974

   ## What is the purpose of the change
   
   This pull request implements the generic DataFrame connector I/O APIs 
proposed by [FLINK-40199](https://issues.apache.org/jira/browse/FLINK-40199). 
It allows PyFlink DataFrame users to read from and write to Table API 
connectors without requiring a connector-specific DataFrame method.
   
   
   ## Brief change log
   
     - Add the public evolving `pyflink.dataframe.read_generic` API with 
physical columns, computed columns, and watermark support.
     - Add the public evolving `DataFrame.write_generic` API, backed by eager 
`Table.execute_insert()` execution.
     - Share connector descriptor construction and validation between the read 
and write paths.
     - Add DataFrame I/O reference documentation and CSV filesystem examples.
     - Add compact unit coverage and one MiniCluster filesystem/CSV round-trip 
test.
   
   
   ## Verifying this change
   
   Please make sure both new and modified tests in this PR follow [the 
conventions for tests defined in our code quality 
guide](https://flink.apache.org/how-to-contribute/code-style-and-quality-common/#7-testing).
   
   This change added tests and can be verified as follows:
   
     - Ran `pyflink.dataframe.tests.test_io`, including descriptor/schema 
construction, shared argument validation, writer delegation and waiting 
behavior, and one filesystem/CSV MiniCluster round trip.
     - Ran the existing `pyflink.dataframe.tests.test_dataframe` suite.
     - Ran Flake8 and Mypy for the PyFlink changes.
     - Built the PyFlink Sphinx documentation.
   
   ## 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)`: yes
     - 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? docs and API docstrings
   
   ---
   
   ##### Was generative AI tooling used to co-author this PR?
   
   - [X] Yes (please specify the tool below)
   
   Generated-by: Codex (GPT-5)
   


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