HyukjinKwon opened a new pull request, #301:
URL: https://github.com/apache/spark-connect-rust/pull/301

   ### What changes were proposed in this pull request?
   
   [SPARK-61096](https://issues.apache.org/jira/browse/SPARK-61096): the repr 
of a `GroupedData` is now PySpark Connect's.
   
   As PySpark Connect's, it names the grouping expressions, the columns of the 
DataFrame with their types, and the type of the grouping (`GroupBy`, `RollUp`, 
`Cube`, `GroupingSets` or `Pivot`):
   
   ```
   GroupedData[grouping expressions: [+(k, 1), s], value: [k: int, s: string, 
v: double], type: GroupBy]
   ```
   
   The core's `GroupedData` gains `grouping_columns`, `group_type` and 
`dataframe`.
   
   ### Why are the changes needed?
   
   The client gave the default repr of an object: 
`<pyspark.sql.group.GroupedData object at 0x...>`.
   
   ### Does this PR introduce _any_ user-facing change?
   
   Yes. The repr of a `GroupedData` is that of PySpark 4.3.0.
   
   ### How was this patch tested?
   
   - A new live test checks the repr of a grouping by an expression and a 
column, of a rollup and of a pivot. It passes with official PySpark 4.3.0 and 
fails without this change.
   - A new offline test checks the repr of each type of grouping against a mock 
Connect server.
   - On a local server, the reprs of 8 groupings, by columns, expressions and 
aliases, of each type and of none, are the same as official PySpark 4.3.0's.
   - The lib tests of both crates (595 passed), the build of all tests, also 
with `wasm-udf`, the offline Python suites (2047 passed, 12 skipped), and the 
live drop-in and Arrow suites (151 passed) and live cases (10 passed) against a 
local Spark 4.3.0 server. Clippy reports no diagnostics in the changed lines.
   
   ### Was this patch authored or co-authored using generative AI tooling?
   
   Generated-by: Claude Opus 5.5
   
   This pull request and its description were written by Isaac.
   


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