pan3793 commented on PR #52633: URL: https://github.com/apache/spark/pull/52633#issuecomment-3408999611
@zhengruifeng, I have a silly question about Python deps management - I see that many Python deps are declared without a version, or with a range version(half-bounded, e.g. `foo>=1.0` or `bar<2.0`). Silently upgrading 3rd libs may introduce breaking changes (especially for major version bumping)/bugs. This means that if we do not specify the dependency version, or only specify the lower bound of the dependency version, PySpark may not work once a new major version of the dependency is released. This becomes a problem if users want to use older Spark versions (in practice, EOLed versions of Spark are used widely and upgrading is not timely). I wonder if Spark can pin all Python deps in a fixed version(or at least a bounded range version, e.g. `foo>=1.0,<=2.3`), this clearly shows the versions of Spark that have been fully tested. -- 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]
