Right To Left (RTL) languages need to reverse the
direction of the icons in navigation.
This fix corrects the arrows in UnitNavigation.jsx,
which were missed in the previous checkin.
Fixes: AA-891
Co-authored-by: cdeery <cdeery@edx.edu>
These redirects are already in place for the courseware, and will
redirect to the outline page, or the dashboard, or wherever, based
on the type of access error (unenrolled, access expired, survey
needed, etc).
This commit stops the course home tabs from paying attention to the
401 error messages coming from the backend - course_access in the
metadata API handles that now.
This commit also changes our useModel hook to more gracefully handle
not being able to find the model - it is a valid case we want to
allow (still will cause problems if you actually try to use the data,
but will at least provide an object you can inspect).
For performance and long term simplification reasons, we want to take
the work currently done by the Course Blocks API and split it up between
the Learning Sequences API (course outline) and Sequence Metadata API
(details about the Units in a Sequence). This will also make it easier
to later support different kinds of Sequences, where we might not know
all the details about it at the time we load the course-wide outline
data.
This starts moving over the responsibility for the high level outline
and metadata to Learning Sequences. It requires that the waffle flag
"learning_sequences.use_for_outlines" be active in the LMS. If that flag
is not active, the Learning Sequences API call will return a 403 error,
and this code will fall back to the older behavior.
Some data could not be shifted over yet. Namely:
* Sequence legacy URL is not currently output by the Learning Sequences
API. This is simple to add, but I don't know if there's any point in
adding it now that the Courseware MFE is functional for timed exams.
* Unit metadata was not completely shifted over to the Sequence Metadata
API because doing so would cause blocking requests and would cause a
noticeable performance regression. This should not be moved over until
the Sequence Metadata API can be made more performant.
* Effort Estimation currently relies on content introspection of the
underlying content in a way that the Learning Sequences API does not
support.
This is the last of a handful of PRs in support of TNL-8330.
