You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
From this list of processors, the following processors wrap concepts which, under the hood, are implemented on the user_partitions framework:
ContentGatingOutlineProcessor
EnrollmentTrackPartitionGroupsOutlineProcessor
CohortPartitionGroupsOutlineProcessor
TeamPartitionGroupsOutlineProcessor (new as of this PR)
Theoretically, they could all be merged into a single UserPartitionOutlineProcessor, which would dedupe some business logic and ensure that any new user_partition schemes automatically work with learning_sequences.
Open questions:
is this as straightforward as I think it is, or are there leaky abstractions / edge cases we're going to hit?
performance regressions?
could the same refactoring be applied to block transformers?
From this list of processors, the following processors wrap concepts which, under the hood, are implemented on the user_partitions framework:
Theoretically, they could all be merged into a single
UserPartitionOutlineProcessor
, which would dedupe some business logic and ensure that any new user_partition schemes automatically work with learning_sequences.Open questions:
CC @ormsbee
The text was updated successfully, but these errors were encountered: