Hi all, I'm a developer trying to make my first contribution to Apache Spark, and while exploring the codebase I came across something I was curious about.
In several places, such as this test case: https://github.com/apache/spark/pull/51225/files#diff-b494cf5a64997153f883507917a63dfb17a8c26624cfef72601e111c0800a9e8R295 I noticed the use of: super(ArrowPythonUDFLegacyTests, cls).setUpClass() instead of the more modern and concise: super().setUpClass() As far as I understand, the explicit form (`super(Class, cls)`) was commonly used to maintain Python 2 compatibility. Since Spark now requires Python 3, I was wondering whether it's okay to start updating these to use `super()`. >From what I know, if a test file has already been refactored to be Python 3-only, using `super()` should be fine. However, I’m not sure if the test environment or codebase still intentionally keeps the older style for consistency or other reasons. I tried looking for past discussions on this but couldn’t find any — maybe I missed something. Sorry if this is a naive question — I’m still learning and very excited to contribute! Best regards, Kyungjun Lee
