584 lines
24 KiB
Python
584 lines
24 KiB
Python
"""
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Functionality for generating grade reports.
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"""
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import logging
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import re
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from collections import OrderedDict
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from datetime import datetime
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from itertools import chain, izip, izip_longest
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from time import time
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from lazy import lazy
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from pytz import UTC
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from six import text_type
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from courseware.courses import get_course_by_id
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from instructor_analytics.basic import list_problem_responses
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from instructor_analytics.csvs import format_dictlist
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from lms.djangoapps.certificates.models import CertificateWhitelist, GeneratedCertificate, certificate_info_for_user
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from lms.djangoapps.grades.context import grading_context, grading_context_for_course
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from lms.djangoapps.grades.models import PersistentCourseGrade
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from lms.djangoapps.grades.course_grade_factory import CourseGradeFactory
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from lms.djangoapps.teams.models import CourseTeamMembership
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from lms.djangoapps.verify_student.services import IDVerificationService
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from openedx.core.djangoapps.content.block_structure.api import get_course_in_cache
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from openedx.core.djangoapps.course_groups.cohorts import bulk_cache_cohorts, get_cohort, is_course_cohorted
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from openedx.core.djangoapps.user_api.course_tag.api import BulkCourseTags
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from student.models import CourseEnrollment
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from student.roles import BulkRoleCache
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from xmodule.modulestore.django import modulestore
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from xmodule.partitions.partitions_service import PartitionService
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from xmodule.split_test_module import get_split_user_partitions
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from .runner import TaskProgress
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from .utils import upload_csv_to_report_store
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TASK_LOG = logging.getLogger('edx.celery.task')
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ENROLLED_IN_COURSE = 'enrolled'
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NOT_ENROLLED_IN_COURSE = 'unenrolled'
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def _user_enrollment_status(user, course_id):
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"""
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Returns the enrollment activation status in the given course
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for the given user.
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"""
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enrollment_is_active = CourseEnrollment.enrollment_mode_for_user(user, course_id)[1]
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if enrollment_is_active:
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return ENROLLED_IN_COURSE
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return NOT_ENROLLED_IN_COURSE
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def _flatten(iterable):
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return list(chain.from_iterable(iterable))
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class _CourseGradeReportContext(object):
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"""
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Internal class that provides a common context to use for a single grade
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report. When a report is parallelized across multiple processes,
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elements of this context are serialized and parsed across process
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boundaries.
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"""
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def __init__(self, _xmodule_instance_args, _entry_id, course_id, _task_input, action_name):
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self.task_info_string = (
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u'Task: {task_id}, '
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u'InstructorTask ID: {entry_id}, '
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u'Course: {course_id}, '
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u'Input: {task_input}'
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).format(
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task_id=_xmodule_instance_args.get('task_id') if _xmodule_instance_args is not None else None,
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entry_id=_entry_id,
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course_id=course_id,
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task_input=_task_input,
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)
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self.action_name = action_name
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self.course_id = course_id
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self.task_progress = TaskProgress(self.action_name, total=None, start_time=time())
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@lazy
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def course(self):
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return get_course_by_id(self.course_id)
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@lazy
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def course_structure(self):
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return get_course_in_cache(self.course_id)
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@lazy
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def course_experiments(self):
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return get_split_user_partitions(self.course.user_partitions)
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@lazy
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def teams_enabled(self):
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return self.course.teams_enabled
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@lazy
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def cohorts_enabled(self):
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return is_course_cohorted(self.course_id)
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@lazy
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def graded_assignments(self):
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"""
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Returns an OrderedDict that maps an assignment type to a dict of
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subsection-headers and average-header.
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"""
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grading_cxt = grading_context(self.course, self.course_structure)
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graded_assignments_map = OrderedDict()
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for assignment_type_name, subsection_infos in grading_cxt['all_graded_subsections_by_type'].iteritems():
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graded_subsections_map = OrderedDict()
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for subsection_index, subsection_info in enumerate(subsection_infos, start=1):
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subsection = subsection_info['subsection_block']
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header_name = u"{assignment_type} {subsection_index}: {subsection_name}".format(
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assignment_type=assignment_type_name,
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subsection_index=subsection_index,
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subsection_name=subsection.display_name,
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)
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graded_subsections_map[subsection.location] = header_name
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average_header = u"{assignment_type}".format(assignment_type=assignment_type_name)
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# Use separate subsection and average columns only if
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# there's more than one subsection.
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separate_subsection_avg_headers = len(subsection_infos) > 1
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if separate_subsection_avg_headers:
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average_header += u" (Avg)"
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graded_assignments_map[assignment_type_name] = {
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'subsection_headers': graded_subsections_map,
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'average_header': average_header,
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'separate_subsection_avg_headers': separate_subsection_avg_headers,
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'grader': grading_cxt['subsection_type_graders'].get(assignment_type_name),
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}
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return graded_assignments_map
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def update_status(self, message):
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"""
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Updates the status on the celery task to the given message.
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Also logs the update.
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"""
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TASK_LOG.info(u'%s, Task type: %s, %s', self.task_info_string, self.action_name, message)
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return self.task_progress.update_task_state(extra_meta={'step': message})
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class _CertificateBulkContext(object):
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def __init__(self, context, users):
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certificate_whitelist = CertificateWhitelist.objects.filter(course_id=context.course_id, whitelist=True)
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self.whitelisted_user_ids = [entry.user_id for entry in certificate_whitelist]
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self.certificates_by_user = {
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certificate.user.id: certificate
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for certificate in
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GeneratedCertificate.objects.filter(course_id=context.course_id, user__in=users)
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}
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class _TeamBulkContext(object):
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def __init__(self, context, users):
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self.enabled = context.teams_enabled
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if self.enabled:
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self.teams_by_user = {
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membership.user.id: membership.team.name
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for membership in
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CourseTeamMembership.objects.filter(team__course_id=context.course_id, user__in=users)
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}
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else:
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self.teams_by_user = {}
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class _EnrollmentBulkContext(object):
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def __init__(self, context, users):
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CourseEnrollment.bulk_fetch_enrollment_states(users, context.course_id)
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self.verified_users = [
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verified.user.id for verified in IDVerificationService.get_verified_users(users)
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]
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class _CourseGradeBulkContext(object):
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def __init__(self, context, users):
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self.certs = _CertificateBulkContext(context, users)
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self.teams = _TeamBulkContext(context, users)
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self.enrollments = _EnrollmentBulkContext(context, users)
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bulk_cache_cohorts(context.course_id, users)
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BulkRoleCache.prefetch(users)
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PersistentCourseGrade.prefetch(context.course_id, users)
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BulkCourseTags.prefetch(context.course_id, users)
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class CourseGradeReport(object):
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"""
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Class to encapsulate functionality related to generating Grade Reports.
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"""
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# Batch size for chunking the list of enrollees in the course.
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USER_BATCH_SIZE = 100
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@classmethod
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def generate(cls, _xmodule_instance_args, _entry_id, course_id, _task_input, action_name):
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"""
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Public method to generate a grade report.
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"""
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with modulestore().bulk_operations(course_id):
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context = _CourseGradeReportContext(_xmodule_instance_args, _entry_id, course_id, _task_input, action_name)
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return CourseGradeReport()._generate(context)
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def _generate(self, context):
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"""
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Internal method for generating a grade report for the given context.
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"""
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context.update_status(u'Starting grades')
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success_headers = self._success_headers(context)
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error_headers = self._error_headers()
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batched_rows = self._batched_rows(context)
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context.update_status(u'Compiling grades')
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success_rows, error_rows = self._compile(context, batched_rows)
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context.update_status(u'Uploading grades')
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self._upload(context, success_headers, success_rows, error_headers, error_rows)
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return context.update_status(u'Completed grades')
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def _success_headers(self, context):
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"""
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Returns a list of all applicable column headers for this grade report.
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"""
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return (
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["Student ID", "Email", "Username"] +
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self._grades_header(context) +
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(['Cohort Name'] if context.cohorts_enabled else []) +
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[u'Experiment Group ({})'.format(partition.name) for partition in context.course_experiments] +
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(['Team Name'] if context.teams_enabled else []) +
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['Enrollment Track', 'Verification Status'] +
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['Certificate Eligible', 'Certificate Delivered', 'Certificate Type'] +
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['Enrollment Status']
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)
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def _error_headers(self):
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"""
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Returns a list of error headers for this grade report.
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"""
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return ["Student ID", "Username", "Error"]
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def _batched_rows(self, context):
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"""
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A generator of batches of (success_rows, error_rows) for this report.
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"""
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for users in self._batch_users(context):
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users = filter(lambda u: u is not None, users)
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yield self._rows_for_users(context, users)
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def _compile(self, context, batched_rows):
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"""
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Compiles and returns the complete list of (success_rows, error_rows) for
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the given batched_rows and context.
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"""
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# partition and chain successes and errors
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success_rows, error_rows = izip(*batched_rows)
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success_rows = list(chain(*success_rows))
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error_rows = list(chain(*error_rows))
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# update metrics on task status
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context.task_progress.succeeded = len(success_rows)
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context.task_progress.failed = len(error_rows)
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context.task_progress.attempted = context.task_progress.succeeded + context.task_progress.failed
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context.task_progress.total = context.task_progress.attempted
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return success_rows, error_rows
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def _upload(self, context, success_headers, success_rows, error_headers, error_rows):
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"""
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Creates and uploads a CSV for the given headers and rows.
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"""
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date = datetime.now(UTC)
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upload_csv_to_report_store([success_headers] + success_rows, 'grade_report', context.course_id, date)
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if len(error_rows) > 0:
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error_rows = [error_headers] + error_rows
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upload_csv_to_report_store(error_rows, 'grade_report_err', context.course_id, date)
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def _grades_header(self, context):
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"""
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Returns the applicable grades-related headers for this report.
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"""
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graded_assignments = context.graded_assignments
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grades_header = ["Grade"]
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for assignment_info in graded_assignments.itervalues():
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if assignment_info['separate_subsection_avg_headers']:
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grades_header.extend(assignment_info['subsection_headers'].itervalues())
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grades_header.append(assignment_info['average_header'])
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return grades_header
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def _batch_users(self, context):
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"""
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Returns a generator of batches of users.
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"""
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def grouper(iterable, chunk_size=self.USER_BATCH_SIZE, fillvalue=None):
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args = [iter(iterable)] * chunk_size
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return izip_longest(*args, fillvalue=fillvalue)
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users = CourseEnrollment.objects.users_enrolled_in(context.course_id, include_inactive=True)
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users = users.select_related('profile')
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return grouper(users)
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def _user_grades(self, course_grade, context):
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"""
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Returns a list of grade results for the given course_grade corresponding
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to the headers for this report.
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"""
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grade_results = []
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for assignment_type, assignment_info in context.graded_assignments.iteritems():
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subsection_grades, subsection_grades_results = self._user_subsection_grades(
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course_grade,
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assignment_info['subsection_headers'],
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)
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grade_results.extend(subsection_grades_results)
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assignment_average = self._user_assignment_average(course_grade, subsection_grades, assignment_info)
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if assignment_average is not None:
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grade_results.append([assignment_average])
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return [course_grade.percent] + _flatten(grade_results)
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def _user_subsection_grades(self, course_grade, subsection_headers):
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"""
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Returns a list of grade results for the given course_grade corresponding
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to the headers for this report.
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"""
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subsection_grades = []
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grade_results = []
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for subsection_location in subsection_headers:
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subsection_grade = course_grade.subsection_grade(subsection_location)
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if subsection_grade.attempted_graded:
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grade_result = subsection_grade.percent_graded
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else:
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grade_result = u'Not Attempted'
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grade_results.append([grade_result])
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subsection_grades.append(subsection_grade)
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return subsection_grades, grade_results
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def _user_assignment_average(self, course_grade, subsection_grades, assignment_info):
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if assignment_info['separate_subsection_avg_headers']:
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if assignment_info['grader']:
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if course_grade.attempted:
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subsection_breakdown = [
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{'percent': subsection_grade.percent_graded}
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for subsection_grade in subsection_grades
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]
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assignment_average, _ = assignment_info['grader'].total_with_drops(subsection_breakdown)
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else:
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assignment_average = 0.0
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return assignment_average
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def _user_cohort_group_names(self, user, context):
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"""
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Returns a list of names of cohort groups in which the given user
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belongs.
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"""
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cohort_group_names = []
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if context.cohorts_enabled:
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group = get_cohort(user, context.course_id, assign=False, use_cached=True)
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cohort_group_names.append(group.name if group else '')
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return cohort_group_names
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def _user_experiment_group_names(self, user, context):
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"""
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Returns a list of names of course experiments in which the given user
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belongs.
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"""
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experiment_group_names = []
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for partition in context.course_experiments:
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group = PartitionService(context.course_id).get_group(user, partition, assign=False)
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experiment_group_names.append(group.name if group else '')
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return experiment_group_names
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def _user_team_names(self, user, bulk_teams):
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"""
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Returns a list of names of teams in which the given user belongs.
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"""
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team_names = []
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if bulk_teams.enabled:
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team_names = [bulk_teams.teams_by_user.get(user.id, '')]
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return team_names
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def _user_verification_mode(self, user, context, bulk_enrollments):
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"""
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Returns a list of enrollment-mode and verification-status for the
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given user.
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"""
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enrollment_mode = CourseEnrollment.enrollment_mode_for_user(user, context.course_id)[0]
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verification_status = IDVerificationService.verification_status_for_user(
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user,
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enrollment_mode,
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user_is_verified=user.id in bulk_enrollments.verified_users,
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)
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return [enrollment_mode, verification_status]
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def _user_certificate_info(self, user, context, course_grade, bulk_certs):
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"""
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Returns the course certification information for the given user.
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"""
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is_whitelisted = user.id in bulk_certs.whitelisted_user_ids
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certificate_info = certificate_info_for_user(
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user,
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context.course_id,
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course_grade.letter_grade,
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is_whitelisted,
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bulk_certs.certificates_by_user.get(user.id),
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)
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TASK_LOG.info(
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u'Student certificate eligibility: %s '
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u'(user=%s, course_id=%s, grade_percent=%s letter_grade=%s gradecutoffs=%s, allow_certificate=%s, '
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u'is_whitelisted=%s)',
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certificate_info[0],
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user,
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context.course_id,
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course_grade.percent,
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course_grade.letter_grade,
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context.course.grade_cutoffs,
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user.profile.allow_certificate,
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is_whitelisted,
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)
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return certificate_info
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def _rows_for_users(self, context, users):
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"""
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Returns a list of rows for the given users for this report.
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"""
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with modulestore().bulk_operations(context.course_id):
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bulk_context = _CourseGradeBulkContext(context, users)
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success_rows, error_rows = [], []
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for user, course_grade, error in CourseGradeFactory().iter(
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users,
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course=context.course,
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collected_block_structure=context.course_structure,
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course_key=context.course_id,
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):
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if not course_grade:
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# An empty gradeset means we failed to grade a student.
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error_rows.append([user.id, user.username, text_type(error)])
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else:
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success_rows.append(
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[user.id, user.email, user.username] +
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self._user_grades(course_grade, context) +
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self._user_cohort_group_names(user, context) +
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self._user_experiment_group_names(user, context) +
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self._user_team_names(user, bulk_context.teams) +
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self._user_verification_mode(user, context, bulk_context.enrollments) +
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self._user_certificate_info(user, context, course_grade, bulk_context.certs) +
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[_user_enrollment_status(user, context.course_id)]
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)
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return success_rows, error_rows
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|
|
|
|
class ProblemGradeReport(object):
|
|
@classmethod
|
|
def generate(cls, _xmodule_instance_args, _entry_id, course_id, _task_input, action_name):
|
|
"""
|
|
Generate a CSV containing all students' problem grades within a given
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`course_id`.
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|
"""
|
|
start_time = time()
|
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start_date = datetime.now(UTC)
|
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status_interval = 100
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enrolled_students = CourseEnrollment.objects.users_enrolled_in(course_id, include_inactive=True)
|
|
task_progress = TaskProgress(action_name, enrolled_students.count(), start_time)
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|
|
|
# This struct encapsulates both the display names of each static item in the
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|
# header row as values as well as the django User field names of those items
|
|
# as the keys. It is structured in this way to keep the values related.
|
|
header_row = OrderedDict([('id', 'Student ID'), ('email', 'Email'), ('username', 'Username')])
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|
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course = get_course_by_id(course_id)
|
|
graded_scorable_blocks = cls._graded_scorable_blocks_to_header(course)
|
|
|
|
# Just generate the static fields for now.
|
|
rows = [list(header_row.values()) + ['Enrollment Status', 'Grade'] + _flatten(graded_scorable_blocks.values())]
|
|
error_rows = [list(header_row.values()) + ['error_msg']]
|
|
current_step = {'step': 'Calculating Grades'}
|
|
|
|
# Bulk fetch and cache enrollment states so we can efficiently determine
|
|
# whether each user is currently enrolled in the course.
|
|
CourseEnrollment.bulk_fetch_enrollment_states(enrolled_students, course_id)
|
|
|
|
for student, course_grade, error in CourseGradeFactory().iter(enrolled_students, course):
|
|
student_fields = [getattr(student, field_name) for field_name in header_row]
|
|
task_progress.attempted += 1
|
|
|
|
if not course_grade:
|
|
err_msg = text_type(error)
|
|
# There was an error grading this student.
|
|
if not err_msg:
|
|
err_msg = u'Unknown error'
|
|
error_rows.append(student_fields + [err_msg])
|
|
task_progress.failed += 1
|
|
continue
|
|
|
|
enrollment_status = _user_enrollment_status(student, course_id)
|
|
|
|
earned_possible_values = []
|
|
for block_location in graded_scorable_blocks:
|
|
try:
|
|
problem_score = course_grade.problem_scores[block_location]
|
|
except KeyError:
|
|
earned_possible_values.append([u'Not Available', u'Not Available'])
|
|
else:
|
|
if problem_score.first_attempted:
|
|
earned_possible_values.append([problem_score.earned, problem_score.possible])
|
|
else:
|
|
earned_possible_values.append([u'Not Attempted', problem_score.possible])
|
|
|
|
rows.append(student_fields + [enrollment_status, course_grade.percent] + _flatten(earned_possible_values))
|
|
|
|
task_progress.succeeded += 1
|
|
if task_progress.attempted % status_interval == 0:
|
|
task_progress.update_task_state(extra_meta=current_step)
|
|
|
|
# Perform the upload if any students have been successfully graded
|
|
if len(rows) > 1:
|
|
upload_csv_to_report_store(rows, 'problem_grade_report', course_id, start_date)
|
|
# If there are any error rows, write them out as well
|
|
if len(error_rows) > 1:
|
|
upload_csv_to_report_store(error_rows, 'problem_grade_report_err', course_id, start_date)
|
|
|
|
return task_progress.update_task_state(extra_meta={'step': 'Uploading CSV'})
|
|
|
|
@classmethod
|
|
def _graded_scorable_blocks_to_header(cls, course):
|
|
"""
|
|
Returns an OrderedDict that maps a scorable block's id to its
|
|
headers in the final report.
|
|
"""
|
|
scorable_blocks_map = OrderedDict()
|
|
grading_context = grading_context_for_course(course)
|
|
for assignment_type_name, subsection_infos in grading_context['all_graded_subsections_by_type'].iteritems():
|
|
for subsection_index, subsection_info in enumerate(subsection_infos, start=1):
|
|
for scorable_block in subsection_info['scored_descendants']:
|
|
header_name = (
|
|
u"{assignment_type} {subsection_index}: "
|
|
u"{subsection_name} - {scorable_block_name}"
|
|
).format(
|
|
scorable_block_name=scorable_block.display_name,
|
|
assignment_type=assignment_type_name,
|
|
subsection_index=subsection_index,
|
|
subsection_name=subsection_info['subsection_block'].display_name,
|
|
)
|
|
scorable_blocks_map[scorable_block.location] = [header_name + " (Earned)",
|
|
header_name + " (Possible)"]
|
|
return scorable_blocks_map
|
|
|
|
|
|
class ProblemResponses(object):
|
|
@classmethod
|
|
def generate(cls, _xmodule_instance_args, _entry_id, course_id, task_input, action_name):
|
|
"""
|
|
For a given `course_id`, generate a CSV file containing
|
|
all student answers to a given problem, and store using a `ReportStore`.
|
|
"""
|
|
start_time = time()
|
|
start_date = datetime.now(UTC)
|
|
num_reports = 1
|
|
task_progress = TaskProgress(action_name, num_reports, start_time)
|
|
current_step = {'step': 'Calculating students answers to problem'}
|
|
task_progress.update_task_state(extra_meta=current_step)
|
|
|
|
# Compute result table and format it
|
|
problem_location = task_input.get('problem_location')
|
|
student_data = list_problem_responses(course_id, problem_location)
|
|
features = ['username', 'state']
|
|
header, rows = format_dictlist(student_data, features)
|
|
|
|
task_progress.attempted = task_progress.succeeded = len(rows)
|
|
task_progress.skipped = task_progress.total - task_progress.attempted
|
|
|
|
rows.insert(0, header)
|
|
|
|
current_step = {'step': 'Uploading CSV'}
|
|
task_progress.update_task_state(extra_meta=current_step)
|
|
|
|
# Perform the upload
|
|
problem_location = re.sub(r'[:/]', '_', problem_location)
|
|
csv_name = 'student_state_from_{}'.format(problem_location)
|
|
upload_csv_to_report_store(rows, csv_name, course_id, start_date)
|
|
|
|
return task_progress.update_task_state(extra_meta=current_step)
|