Xiugapurin opened a new pull request, #59362: URL: https://github.com/apache/spark/pull/59362
### What changes were proposed in this pull request? Add unit tests to `python/pyspark/sql/tests/pandas/test_converter.py` for timestamps nested inside complex types, in both conversion directions: - `test_converter_from_pandas_nested_timestamp`: nested `TimestampType` and `TimestampLTZNanosType`, with timezone-aware and naive values, verifying that naive values are interpreted in the session timezone and that nanosecond precision is preserved. - `test_converter_to_pandas_nested_timestamp`: nested `TimestampType` (including `timestamp_utc_localized=False`), `TimestampLTZNanosType` and `TimestampNTZType`. ### Why are the changes needed? Top-level timestamp columns are converted with a vectorized path, but nested timestamps go through per-value converters in `pyspark/sql/pandas/types.py` that are not covered by existing tests. These tests improve coverage and guard the timezone handling and nanosecond precision of these paths. ### Does this PR introduce _any_ user-facing change? No, test-only. ### How was this patch tested? New unit tests. They do not require a JVM: ``` python/run-tests --testnames pyspark.sql.tests.pandas.test_converter ``` ### Was this patch authored or co-authored using generative AI tooling? Generated-by: Claude Code (Claude Opus 5.5) 🤖 Generated with [Claude Code](https://claude.com/claude-code) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
