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This is a meta issue to prioritize our work for Pydata Seattle 2023.
High-level tasks for the presentation:
High-level tasks for new features/maintenance ahead of Pydata Seattle 2023. These are divided into "must", "should" and "nice-to-have":
Must:
-
sktimeandskbaseinitial integration is completed. Targeting mid-April release ofsktimev0.18.0 - Create "example" repository that includes a stylized package that uses
skbase(will also be useful for additional testing of our lookup, testing and validation functionality too) - Local (class) configuration interface
- [ENH] Refactor
skbase.base._metaand add unit tests #106
Should
- [ENH] Implements sklearn style pretty printing directly in
skbase#150 - Add persistance (re-work of
sktimepersistance approach to make sure it works more generally) - Upgrade documentation, with emphasis on landing page
- Redo governance section of documentation
- Create functionality roadmap (borrow from HackMD and design document and add other ideas)
- Improve documentation of the
skbase.testingmodule
Nice-to-have
- [ENH] Add global config interface #149
- Example showing how to use
skbaseto createscikit-learncompliant class (need to investigate if this is possible. If their checks are "duck-typed" then it should be)
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