- added the abstract and concrete layers of enrollment report provider - created a celery task. -added the button in the e-commerce reports section added the enrollment data backend added the payment data and start writing the test cases. updated the code with the feedback suggestions and wrote some test cases. - all the downloadable reports are now visible in the ecommerce download section. Pending instructor tasks is also visible in the ecommerce section added the fields in the user profile information changed the report store configuration key added the new http endpoint for financial reports to add more permissions for finance_admin to access. fix quality issues added test cases to check csv content data rebased with master and resolved conflicts changed the log messages added the changes as per code clintonb suggestions during code review updated the test cases for the finance_admin decorator changes suggested by clinton. Created and moved Table level filters to the Custom Manager for the CourseEnrollment model. ecommerce.js file was loaded twice in the instructor_dashboard.js fixed the issues added the registration code column in the csv added the full gender in the csv file Update data sources and add display name translations for the report columns fix meta name Make sure the reports section does not appear on non whitelabel courses pylint fixes expand out enumerated values
210 lines
9.3 KiB
Python
210 lines
9.3 KiB
Python
"""
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This file contains tasks that are designed to perform background operations on the
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running state of a course.
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At present, these tasks all operate on StudentModule objects in one way or another,
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so they share a visitor architecture. Each task defines an "update function" that
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takes a module_descriptor, a particular StudentModule object, and xmodule_instance_args.
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A task may optionally specify a "filter function" that takes a query for StudentModule
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objects, and adds additional filter clauses.
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A task also passes through "xmodule_instance_args", that are used to provide
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information to our code that instantiates xmodule instances.
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The task definition then calls the traversal function, passing in the three arguments
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above, along with the id value for an InstructorTask object. The InstructorTask
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object contains a 'task_input' row which is a JSON-encoded dict containing
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a problem URL and optionally a student. These are used to set up the initial value
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of the query for traversing StudentModule objects.
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"""
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import logging
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from functools import partial
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from django.conf import settings
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from django.utils.translation import ugettext_noop
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from celery import task
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from bulk_email.tasks import perform_delegate_email_batches
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from instructor_task.tasks_helper import (
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run_main_task,
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BaseInstructorTask,
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perform_module_state_update,
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rescore_problem_module_state,
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reset_attempts_module_state,
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delete_problem_module_state,
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upload_grades_csv,
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upload_problem_grade_report,
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upload_students_csv,
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cohort_students_and_upload,
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upload_enrollment_report)
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TASK_LOG = logging.getLogger('edx.celery.task')
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@task(base=BaseInstructorTask) # pylint: disable=not-callable
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def rescore_problem(entry_id, xmodule_instance_args):
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"""Rescores a problem in a course, for all students or one specific student.
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`entry_id` is the id value of the InstructorTask entry that corresponds to this task.
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The entry contains the `course_id` that identifies the course, as well as the
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`task_input`, which contains task-specific input.
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The task_input should be a dict with the following entries:
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'problem_url': the full URL to the problem to be rescored. (required)
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'student': the identifier (username or email) of a particular user whose
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problem submission should be rescored. If not specified, all problem
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submissions for the problem will be rescored.
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`xmodule_instance_args` provides information needed by _get_module_instance_for_task()
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to instantiate an xmodule instance.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('rescored')
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update_fcn = partial(rescore_problem_module_state, xmodule_instance_args)
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def filter_fcn(modules_to_update):
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"""Filter that matches problems which are marked as being done"""
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return modules_to_update.filter(state__contains='"done": true')
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visit_fcn = partial(perform_module_state_update, update_fcn, filter_fcn)
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return run_main_task(entry_id, visit_fcn, action_name)
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@task(base=BaseInstructorTask) # pylint: disable=not-callable
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def reset_problem_attempts(entry_id, xmodule_instance_args):
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"""Resets problem attempts to zero for a particular problem for all students in a course.
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`entry_id` is the id value of the InstructorTask entry that corresponds to this task.
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The entry contains the `course_id` that identifies the course, as well as the
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`task_input`, which contains task-specific input.
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The task_input should be a dict with the following entries:
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'problem_url': the full URL to the problem to be rescored. (required)
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`xmodule_instance_args` provides information needed by _get_module_instance_for_task()
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to instantiate an xmodule instance.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('reset')
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update_fcn = partial(reset_attempts_module_state, xmodule_instance_args)
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visit_fcn = partial(perform_module_state_update, update_fcn, None)
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return run_main_task(entry_id, visit_fcn, action_name)
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@task(base=BaseInstructorTask) # pylint: disable=not-callable
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def delete_problem_state(entry_id, xmodule_instance_args):
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"""Deletes problem state entirely for all students on a particular problem in a course.
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`entry_id` is the id value of the InstructorTask entry that corresponds to this task.
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The entry contains the `course_id` that identifies the course, as well as the
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`task_input`, which contains task-specific input.
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The task_input should be a dict with the following entries:
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'problem_url': the full URL to the problem to be rescored. (required)
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`xmodule_instance_args` provides information needed by _get_module_instance_for_task()
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to instantiate an xmodule instance.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('deleted')
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update_fcn = partial(delete_problem_module_state, xmodule_instance_args)
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visit_fcn = partial(perform_module_state_update, update_fcn, None)
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return run_main_task(entry_id, visit_fcn, action_name)
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@task(base=BaseInstructorTask) # pylint: disable=not-callable
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def send_bulk_course_email(entry_id, _xmodule_instance_args):
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"""Sends emails to recipients enrolled in a course.
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`entry_id` is the id value of the InstructorTask entry that corresponds to this task.
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The entry contains the `course_id` that identifies the course, as well as the
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`task_input`, which contains task-specific input.
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The task_input should be a dict with the following entries:
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'email_id': the full URL to the problem to be rescored. (required)
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`_xmodule_instance_args` provides information needed by _get_module_instance_for_task()
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to instantiate an xmodule instance. This is unused here.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('emailed')
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visit_fcn = perform_delegate_email_batches
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return run_main_task(entry_id, visit_fcn, action_name)
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@task(base=BaseInstructorTask, routing_key=settings.GRADES_DOWNLOAD_ROUTING_KEY) # pylint: disable=not-callable
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def calculate_grades_csv(entry_id, xmodule_instance_args):
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"""
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Grade a course and push the results to an S3 bucket for download.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('graded')
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TASK_LOG.info(
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u"Task: %s, InstructorTask ID: %s, Task type: %s, Preparing for task execution",
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xmodule_instance_args.get('task_id'), entry_id, action_name
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)
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task_fn = partial(upload_grades_csv, xmodule_instance_args)
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return run_main_task(entry_id, task_fn, action_name)
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@task(base=BaseInstructorTask, routing_key=settings.GRADES_DOWNLOAD_ROUTING_KEY) # pylint: disable=not-callable
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def calculate_problem_grade_report(entry_id, xmodule_instance_args):
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"""
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Generate a CSV for a course containing all students' problem
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grades and push the results to an S3 bucket for download.
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"""
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# Translators: This is a past-tense phrase that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('problem distribution graded')
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TASK_LOG.info(
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u"Task: %s, InstructorTask ID: %s, Task type: %s, Preparing for task execution",
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xmodule_instance_args.get('task_id'), entry_id, action_name
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)
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task_fn = partial(upload_problem_grade_report, xmodule_instance_args)
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return run_main_task(entry_id, task_fn, action_name)
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@task(base=BaseInstructorTask, routing_key=settings.GRADES_DOWNLOAD_ROUTING_KEY) # pylint: disable=not-callable
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def calculate_students_features_csv(entry_id, xmodule_instance_args):
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"""
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Compute student profile information for a course and upload the
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CSV to an S3 bucket for download.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('generated')
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task_fn = partial(upload_students_csv, xmodule_instance_args)
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return run_main_task(entry_id, task_fn, action_name)
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@task(base=BaseInstructorTask, routing_key=settings.GRADES_DOWNLOAD_ROUTING_KEY) # pylint: disable=not-callable
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def enrollment_report_features_csv(entry_id, xmodule_instance_args):
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"""
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Compute student profile information for a course and upload the
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CSV to an S3 bucket for download.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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action_name = ugettext_noop('generating_enrollment_report')
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task_fn = partial(upload_enrollment_report, xmodule_instance_args)
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return run_main_task(entry_id, task_fn, action_name)
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@task(base=BaseInstructorTask) # pylint: disable=E1102
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def cohort_students(entry_id, xmodule_instance_args):
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"""
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Cohort students in bulk, and upload the results.
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"""
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# Translators: This is a past-tense verb that is inserted into task progress messages as {action}.
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# An example of such a message is: "Progress: {action} {succeeded} of {attempted} so far"
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action_name = ugettext_noop('cohorted')
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task_fn = partial(cohort_students_and_upload, xmodule_instance_args)
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return run_main_task(entry_id, task_fn, action_name)
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