* Use full LMS imports paths in LMS settings and urls modules
* Use full LMS import paths in Studio settings and urls modules
* Import from lms.djangoapps.badges instead of badges
* Import from lms.djangoapps.branding instead of branding
* Import from lms.djangoapps.bulk_email instead of bulk_email
* Import from lms.djangoapps.bulk_enroll instead of bulk_enroll
* Import from lms.djangoapps.ccx instead of ccx
* Import from lms.djangoapps.course_api instead of course_api
* Import from lms.djangoapps.course_blocks instead of course_blocks
* Import from lms.djangoapps.course_wiki instead of course_wiki
* Import from lms.djangoapps.courseware instead of courseware
* Import from lms.djangoapps.dashboard instead of dashboard
* Import from lms.djangoapps.discussion import discussion
* Import from lms.djangoapps.email_marketing instead of email_marketing
* Import from lms.djangoapps.experiments instead of experiments
* Import from lms.djangoapps.gating instead of gating
* Import from lms.djangoapps.grades instead of grades
* Import from lms.djangoapps.instructor_analytics instead of instructor_analytics
* Import form lms.djangoapps.lms_xblock instead of lms_xblock
* Import from lms.djangoapps.lti_provider instead of lti_provider
* Import from lms.djangoapps.mobile_api instead of mobile_api
* Import from lms.djangoapps.rss_proxy instead of rss_proxy
* Import from lms.djangoapps.static_template_view instead of static_template_view
* Import from lms.djangoapps.survey instead of survey
* Import from lms.djangoapps.verify_student instead of verify_student
* Stop suppressing EdxPlatformDeprecatedImportWarnings
When an InstructorTask is stuck in QUEUING (say if there was a
problem with celery), the support team needs to manually intervene
and mark the task as "FAILED" so that new tasks of that type can
be created for that course. This is usually done one at a time,
but sometimes a bug or outage might cause many tasks to fail at
once, making recovery extremely cumbersome. This commit adds the
ability to do this process in batches.
* Import instructor tasks explicitly on workers.
Importing them via app config leads to an dependency chain nightmare as lots of other apps get pulled into the startup
and are not configured in situations like testing the common and lib unit tests. This should register tasks to the celery
workers without messing with the startup dependency chains of the LMS, CMS and test setup.
This fixes an issue where instructor_task Celery tasks were not being
auto-discovered, thus leaving them unregistered and unable to be
completed by our Celery workers.
TNL-7652
Removed most of the deprecated shoppingcart app, leaving just enough to allow us to cleanly remove the related database tables later. Also removed the relevant Django settings that weren't in use elsewhere.
Instead of going up the stacktrace to find the module names of waffle
flags and switches, we manually pass the module __name__ whenever the
flag is created. This is similar to `logging.getLogger(__name__)`
standard behaviour.
As the waffle classes are used outside of edx-platform, we make the new
module_name argument an optional keyword argument. This will change once
we pull waffle_utils outside of edx-platform.
Note that the module name is normally only required to view the list of
existing waffle flags and switches. The module name should not be
necessary to verify if a flag is enabled. Thus, maybe it would make
sense to create a `add` class methor similar to:
class WaffleFlag:
@classmethod
def add(cls, namespace, flag, module):
instance = cls(namespace, flag)
cls._class_instances.add((instance, module))
This change adds support for specifying multiple root blocks while generating
problem response reports. It also allows specifying a block type filter so that
only blocks of the filtered types will be included in the report.
Finally, this change also consistenly uses absolute path for the location in the
report instead of relative paths.
Ratelimited `login_user` endpoint using `django-ratelimit`, also
decreased default value of logistration rate limit to 100 requests
per five minutes per IP.
PROD-1877
https://github.com/boto/boto/issues/2868
In python 3 contentfile can act like a file but return unicode strings.
Boto doesn't like that and it causes issues when encoding the bytes for
transfer to s3.
This is a follow up from MST-16, which was commited
in 3858036a4e.
Changes:
* Enrich course teams_configuration from a plain Dict
to a custom XBlock field that uses the new TeamsConfig
wrapper class.
* Remove teams_conf property from course, as the previous
change made it redundant.
* Update teams_enabled implementation.
* Remove teams_max_size field from course, which is
no longer semantically correct, as max team size
is now defined on a teamset level.
* Remove teams_topics in order to discourage use of raw
teams config dict.
* Add convenience properties teamsets and teamsets_by_id
to course.
* Allow periods and spaces in teamset IDs to avoid breaking
existing course teams.
Some parts of the code still use the old raw config data
(identifiable by searching "cleaned_data_old_format"),
which we expect to be slowly factored away as we build
new teams features. MST-40 has been created to remove any
remaining references if necessary.
MST-18
* fix: bokchoy test
* fix: remove pdb break
updated the csv reader to make the csv output compatible across both python versions
added the encoding argument to unicodecsv.DictReader method
updated the csv file read process to accomodate different input types
changes made to fix issues with UniversalNewLineIterator
changes made as suggested
changes made as suggested
changes made to fulfill quality check requirement to pass quality check
minor changes
