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Dependency Versioning Stategy

Open npatki opened this issue 3 years ago • 0 comments

Problem Description

Currently, all libraries in the SDV ecosystem have narrow and fixed dependency ranges (with a min and max).

Sometimes as external libraries change, users may have problems installing the SDV such as #1349, #1360, #1345.

Expected behavior

I'm filing this as a broad issue to think about the SDV dependency versioning strategy. In addition to supporting the latest version of pandas (#1366) and pytorch (#1365), we should also think about how to enable the broadest set of of acceptable versions.

npatki avatar Apr 10 '23 14:04 npatki