that are not present in a given student's gradeset. General code cleanup and addition of comments. Instructor dashboard API unit tests. LMS-58
142 lines
6.3 KiB
Python
142 lines
6.3 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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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 functools import partial
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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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push_grades_to_s3,
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)
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from bulk_email.tasks import perform_delegate_email_batches
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@task(base=BaseInstructorTask) # pylint: disable=E1102
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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=E1102
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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=E1102
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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=E1102
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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=E1102
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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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action_name = ugettext_noop('graded')
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task_fn = partial(push_grades_to_s3, xmodule_instance_args)
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return run_main_task(entry_id, task_fn, action_name)
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