Files
edx-platform/lms/djangoapps/instructor_task/tasks_helper/grades.py
2020-01-28 14:04:02 +05:00

806 lines
34 KiB
Python

"""
Functionality for generating grade reports.
"""
import logging
import re
from collections import OrderedDict, defaultdict
from datetime import datetime
from itertools import chain
from time import time
import six
from django.conf import settings
from django.contrib.auth import get_user_model
from lazy import lazy
from pytz import UTC
from six import text_type
from six.moves import zip, zip_longest
from course_blocks.api import get_course_blocks
from course_modes.models import CourseMode
from lms.djangoapps.certificates.models import CertificateWhitelist, GeneratedCertificate, certificate_info_for_user
from lms.djangoapps.courseware.courses import get_course_by_id
from lms.djangoapps.courseware.user_state_client import DjangoXBlockUserStateClient
from lms.djangoapps.grades.api import CourseGradeFactory
from lms.djangoapps.grades.api import context as grades_context
from lms.djangoapps.grades.api import prefetch_course_and_subsection_grades
from lms.djangoapps.instructor_analytics.basic import list_problem_responses
from lms.djangoapps.instructor_analytics.csvs import format_dictlist
from lms.djangoapps.instructor_task.config.waffle import (
generate_grade_report_for_verified_only,
optimize_get_learners_switch_enabled
)
from lms.djangoapps.teams.models import CourseTeamMembership
from lms.djangoapps.verify_student.services import IDVerificationService
from opaque_keys.edx.keys import UsageKey
from openedx.core.djangoapps.content.block_structure.api import get_course_in_cache
from openedx.core.djangoapps.course_groups.cohorts import bulk_cache_cohorts, get_cohort, is_course_cohorted
from openedx.core.djangoapps.user_api.course_tag.api import BulkCourseTags
from student.models import CourseEnrollment
from student.roles import BulkRoleCache
from xmodule.modulestore.django import modulestore
from xmodule.partitions.partitions_service import PartitionService
from xmodule.split_test_module import get_split_user_partitions
from .runner import TaskProgress
from .utils import upload_csv_to_report_store
TASK_LOG = logging.getLogger('edx.celery.task')
ENROLLED_IN_COURSE = 'enrolled'
NOT_ENROLLED_IN_COURSE = 'unenrolled'
def _user_enrollment_status(user, course_id):
"""
Returns the enrollment activation status in the given course
for the given user.
"""
enrollment_is_active = CourseEnrollment.enrollment_mode_for_user(user, course_id)[1]
if enrollment_is_active:
return ENROLLED_IN_COURSE
return NOT_ENROLLED_IN_COURSE
def _flatten(iterable):
return list(chain.from_iterable(iterable))
class _CourseGradeReportContext(object):
"""
Internal class that provides a common context to use for a single grade
report. When a report is parallelized across multiple processes,
elements of this context are serialized and parsed across process
boundaries.
"""
def __init__(self, _xmodule_instance_args, _entry_id, course_id, _task_input, action_name):
self.task_info_string = (
u'Task: {task_id}, '
u'InstructorTask ID: {entry_id}, '
u'Course: {course_id}, '
u'Input: {task_input}'
).format(
task_id=_xmodule_instance_args.get('task_id') if _xmodule_instance_args is not None else None,
entry_id=_entry_id,
course_id=course_id,
task_input=_task_input,
)
self.action_name = action_name
self.course_id = course_id
self.task_progress = TaskProgress(self.action_name, total=None, start_time=time())
@lazy
def course(self):
return get_course_by_id(self.course_id)
@lazy
def course_structure(self):
return get_course_in_cache(self.course_id)
@lazy
def course_experiments(self):
return get_split_user_partitions(self.course.user_partitions)
@lazy
def teams_enabled(self):
return self.course.teams_enabled
@lazy
def cohorts_enabled(self):
return is_course_cohorted(self.course_id)
@lazy
def graded_assignments(self):
"""
Returns an OrderedDict that maps an assignment type to a dict of
subsection-headers and average-header.
"""
grading_cxt = grades_context.grading_context(self.course, self.course_structure)
graded_assignments_map = OrderedDict()
for assignment_type_name, subsection_infos in six.iteritems(grading_cxt['all_graded_subsections_by_type']):
graded_subsections_map = OrderedDict()
for subsection_index, subsection_info in enumerate(subsection_infos, start=1):
subsection = subsection_info['subsection_block']
header_name = u"{assignment_type} {subsection_index}: {subsection_name}".format(
assignment_type=assignment_type_name,
subsection_index=subsection_index,
subsection_name=subsection.display_name,
)
graded_subsections_map[subsection.location] = header_name
average_header = u"{assignment_type}".format(assignment_type=assignment_type_name)
# Use separate subsection and average columns only if
# there's more than one subsection.
separate_subsection_avg_headers = len(subsection_infos) > 1
if separate_subsection_avg_headers:
average_header += u" (Avg)"
graded_assignments_map[assignment_type_name] = {
'subsection_headers': graded_subsections_map,
'average_header': average_header,
'separate_subsection_avg_headers': separate_subsection_avg_headers,
'grader': grading_cxt['subsection_type_graders'].get(assignment_type_name),
}
return graded_assignments_map
def update_status(self, message):
"""
Updates the status on the celery task to the given message.
Also logs the update.
"""
TASK_LOG.info(u'%s, Task type: %s, %s', self.task_info_string, self.action_name, message)
return self.task_progress.update_task_state(extra_meta={'step': message})
class _CertificateBulkContext(object):
def __init__(self, context, users):
certificate_whitelist = CertificateWhitelist.objects.filter(course_id=context.course_id, whitelist=True)
self.whitelisted_user_ids = [entry.user_id for entry in certificate_whitelist]
self.certificates_by_user = {
certificate.user.id: certificate
for certificate in
GeneratedCertificate.objects.filter(course_id=context.course_id, user__in=users)
}
class _TeamBulkContext(object):
def __init__(self, context, users):
self.enabled = context.teams_enabled
if self.enabled:
self.teams_by_user = {
membership.user.id: membership.team.name
for membership in
CourseTeamMembership.objects.filter(team__course_id=context.course_id, user__in=users)
}
else:
self.teams_by_user = {}
class _EnrollmentBulkContext(object):
def __init__(self, context, users):
CourseEnrollment.bulk_fetch_enrollment_states(users, context.course_id)
self.verified_users = set(IDVerificationService.get_verified_user_ids(users))
class _CourseGradeBulkContext(object):
def __init__(self, context, users):
self.certs = _CertificateBulkContext(context, users)
self.teams = _TeamBulkContext(context, users)
self.enrollments = _EnrollmentBulkContext(context, users)
bulk_cache_cohorts(context.course_id, users)
BulkRoleCache.prefetch(users)
prefetch_course_and_subsection_grades(context.course_id, users)
BulkCourseTags.prefetch(context.course_id, users)
class CourseGradeReport(object):
"""
Class to encapsulate functionality related to generating Grade Reports.
"""
# Batch size for chunking the list of enrollees in the course.
USER_BATCH_SIZE = 100
@classmethod
def generate(cls, _xmodule_instance_args, _entry_id, course_id, _task_input, action_name):
"""
Public method to generate a grade report.
"""
with modulestore().bulk_operations(course_id):
context = _CourseGradeReportContext(_xmodule_instance_args, _entry_id, course_id, _task_input, action_name)
return CourseGradeReport()._generate(context)
def _generate(self, context):
"""
Internal method for generating a grade report for the given context.
"""
context.update_status(u'Starting grades')
success_headers = self._success_headers(context)
error_headers = self._error_headers()
batched_rows = self._batched_rows(context)
context.update_status(u'Compiling grades')
success_rows, error_rows = self._compile(context, batched_rows)
context.update_status(u'Uploading grades')
self._upload(context, success_headers, success_rows, error_headers, error_rows)
return context.update_status(u'Completed grades')
def _success_headers(self, context):
"""
Returns a list of all applicable column headers for this grade report.
"""
return (
["Student ID", "Email", "Username"] +
self._grades_header(context) +
(['Cohort Name'] if context.cohorts_enabled else []) +
[u'Experiment Group ({})'.format(partition.name) for partition in context.course_experiments] +
(['Team Name'] if context.teams_enabled else []) +
['Enrollment Track', 'Verification Status'] +
['Certificate Eligible', 'Certificate Delivered', 'Certificate Type'] +
['Enrollment Status']
)
def _error_headers(self):
"""
Returns a list of error headers for this grade report.
"""
return ["Student ID", "Username", "Error"]
def _batched_rows(self, context):
"""
A generator of batches of (success_rows, error_rows) for this report.
"""
for users in self._batch_users(context):
users = [u for u in users if u is not None]
yield self._rows_for_users(context, users)
def _compile(self, context, batched_rows):
"""
Compiles and returns the complete list of (success_rows, error_rows) for
the given batched_rows and context.
"""
# partition and chain successes and errors
success_rows, error_rows = zip(*batched_rows)
success_rows = list(chain(*success_rows))
error_rows = list(chain(*error_rows))
# update metrics on task status
context.task_progress.succeeded = len(success_rows)
context.task_progress.failed = len(error_rows)
context.task_progress.attempted = context.task_progress.succeeded + context.task_progress.failed
context.task_progress.total = context.task_progress.attempted
return success_rows, error_rows
def _upload(self, context, success_headers, success_rows, error_headers, error_rows):
"""
Creates and uploads a CSV for the given headers and rows.
"""
date = datetime.now(UTC)
upload_csv_to_report_store([success_headers] + success_rows, 'grade_report', context.course_id, date)
if len(error_rows) > 0:
error_rows = [error_headers] + error_rows
upload_csv_to_report_store(error_rows, 'grade_report_err', context.course_id, date)
def _grades_header(self, context):
"""
Returns the applicable grades-related headers for this report.
"""
graded_assignments = context.graded_assignments
grades_header = ["Grade"]
for assignment_info in six.itervalues(graded_assignments):
if assignment_info['separate_subsection_avg_headers']:
grades_header.extend(six.itervalues(assignment_info['subsection_headers']))
grades_header.append(assignment_info['average_header'])
return grades_header
def _batch_users(self, context):
"""
Returns a generator of batches of users.
"""
def grouper(iterable, chunk_size=self.USER_BATCH_SIZE, fillvalue=None):
args = [iter(iterable)] * chunk_size
return zip_longest(*args, fillvalue=fillvalue)
def get_enrolled_learners_for_course(course_id, verified_only=False):
"""
Get enrolled learners in a course.
Arguments:
course_id (CourseLocator): course_id to return enrollees for.
verified_only (boolean): is a boolean when True, returns only verified enrollees.
"""
if optimize_get_learners_switch_enabled():
TASK_LOG.info(u'%s, Creating Course Grade with optimization', task_log_message)
return users_for_course_v2(course_id, verified_only=verified_only)
TASK_LOG.info(u'%s, Creating Course Grade without optimization', task_log_message)
return users_for_course(course_id, verified_only=verified_only)
def users_for_course(course_id, verified_only=False):
"""
Get all the enrolled users in a course.
This method fetches & loads the enrolled user objects at once which may cause
out-of-memory errors in large courses. This method will be removed when
`OPTIMIZE_GET_LEARNERS_FOR_COURSE` waffle flag is removed.
"""
users = CourseEnrollment.objects.users_enrolled_in(
course_id,
include_inactive=True,
verified_only=verified_only,
)
users = users.select_related('profile')
return grouper(users)
def users_for_course_v2(course_id, verified_only=False):
"""
Get all the enrolled users in a course chunk by chunk.
This generator method fetches & loads the enrolled user objects on demand which in chunk
size defined. This method is a workaround to avoid out-of-memory errors.
"""
filter_kwargs = {
'courseenrollment__course_id': course_id,
}
if verified_only:
filter_kwargs['courseenrollment__mode'] = CourseMode.VERIFIED
user_ids_list = get_user_model().objects.filter(**filter_kwargs).values_list('id', flat=True).order_by('id')
user_chunks = grouper(user_ids_list)
for user_ids in user_chunks:
user_ids = [user_id for user_id in user_ids if user_id is not None]
min_id = min(user_ids)
max_id = max(user_ids)
users = get_user_model().objects.filter(
id__gte=min_id,
id__lte=max_id,
**filter_kwargs
).select_related('profile')
yield users
course_id = context.course_id
task_log_message = u'{}, Task type: {}'.format(context.task_info_string, context.action_name)
report_for_verified_only = generate_grade_report_for_verified_only()
return get_enrolled_learners_for_course(course_id=course_id, verified_only=report_for_verified_only)
def _user_grades(self, course_grade, context):
"""
Returns a list of grade results for the given course_grade corresponding
to the headers for this report.
"""
grade_results = []
for _, assignment_info in six.iteritems(context.graded_assignments):
subsection_grades, subsection_grades_results = self._user_subsection_grades(
course_grade,
assignment_info['subsection_headers'],
)
grade_results.extend(subsection_grades_results)
assignment_average = self._user_assignment_average(course_grade, subsection_grades, assignment_info)
if assignment_average is not None:
grade_results.append([assignment_average])
return [course_grade.percent] + _flatten(grade_results)
def _user_subsection_grades(self, course_grade, subsection_headers):
"""
Returns a list of grade results for the given course_grade corresponding
to the headers for this report.
"""
subsection_grades = []
grade_results = []
for subsection_location in subsection_headers:
subsection_grade = course_grade.subsection_grade(subsection_location)
if subsection_grade.attempted_graded or subsection_grade.override:
grade_result = subsection_grade.percent_graded
else:
grade_result = u'Not Attempted'
grade_results.append([grade_result])
subsection_grades.append(subsection_grade)
return subsection_grades, grade_results
def _user_assignment_average(self, course_grade, subsection_grades, assignment_info):
if assignment_info['separate_subsection_avg_headers']:
if assignment_info['grader']:
if course_grade.attempted:
subsection_breakdown = [
{'percent': subsection_grade.percent_graded}
for subsection_grade in subsection_grades
]
assignment_average, _ = assignment_info['grader'].total_with_drops(subsection_breakdown)
else:
assignment_average = 0.0
return assignment_average
def _user_cohort_group_names(self, user, context):
"""
Returns a list of names of cohort groups in which the given user
belongs.
"""
cohort_group_names = []
if context.cohorts_enabled:
group = get_cohort(user, context.course_id, assign=False, use_cached=True)
cohort_group_names.append(group.name if group else '')
return cohort_group_names
def _user_experiment_group_names(self, user, context):
"""
Returns a list of names of course experiments in which the given user
belongs.
"""
experiment_group_names = []
for partition in context.course_experiments:
group = PartitionService(context.course_id).get_group(user, partition, assign=False)
experiment_group_names.append(group.name if group else '')
return experiment_group_names
def _user_team_names(self, user, bulk_teams):
"""
Returns a list of names of teams in which the given user belongs.
"""
team_names = []
if bulk_teams.enabled:
team_names = [bulk_teams.teams_by_user.get(user.id, '')]
return team_names
def _user_verification_mode(self, user, context, bulk_enrollments):
"""
Returns a list of enrollment-mode and verification-status for the
given user.
"""
enrollment_mode = CourseEnrollment.enrollment_mode_for_user(user, context.course_id)[0]
verification_status = IDVerificationService.verification_status_for_user(
user,
enrollment_mode,
user_is_verified=user.id in bulk_enrollments.verified_users,
)
return [enrollment_mode, verification_status]
def _user_certificate_info(self, user, context, course_grade, bulk_certs):
"""
Returns the course certification information for the given user.
"""
is_whitelisted = user.id in bulk_certs.whitelisted_user_ids
certificate_info = certificate_info_for_user(
user,
context.course_id,
course_grade.letter_grade,
is_whitelisted,
bulk_certs.certificates_by_user.get(user.id),
)
TASK_LOG.info(
u'Student certificate eligibility: %s '
u'(user=%s, course_id=%s, grade_percent=%s letter_grade=%s gradecutoffs=%s, allow_certificate=%s, '
u'is_whitelisted=%s)',
certificate_info[0],
user,
context.course_id,
course_grade.percent,
course_grade.letter_grade,
context.course.grade_cutoffs,
user.profile.allow_certificate,
is_whitelisted,
)
return certificate_info
def _rows_for_users(self, context, users):
"""
Returns a list of rows for the given users for this report.
"""
with modulestore().bulk_operations(context.course_id):
bulk_context = _CourseGradeBulkContext(context, users)
success_rows, error_rows = [], []
for user, course_grade, error in CourseGradeFactory().iter(
users,
course=context.course,
collected_block_structure=context.course_structure,
course_key=context.course_id,
):
if not course_grade:
# An empty gradeset means we failed to grade a student.
error_rows.append([user.id, user.username, text_type(error)])
else:
success_rows.append(
[user.id, user.email, user.username] +
self._user_grades(course_grade, context) +
self._user_cohort_group_names(user, context) +
self._user_experiment_group_names(user, context) +
self._user_team_names(user, bulk_context.teams) +
self._user_verification_mode(user, context, bulk_context.enrollments) +
self._user_certificate_info(user, context, course_grade, bulk_context.certs) +
[_user_enrollment_status(user, context.course_id)]
)
return success_rows, error_rows
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
`course_id`.
"""
def log_task_info(message):
"""
Updates the status on the celery task to the given message.
Also logs the update.
"""
fmt = u'Task: {task_id}, InstructorTask ID: {entry_id}, Course: {course_id}, Input: {task_input}'
task_info_string = fmt.format(
task_id=task_id, entry_id=_entry_id, course_id=course_id, task_input=_task_input
)
TASK_LOG.info(u'%s, Task type: %s, %s, %s', task_info_string, action_name, message, task_progress.state)
start_time = time()
start_date = datetime.now(UTC)
status_interval = 100
task_id = _xmodule_instance_args.get('task_id') if _xmodule_instance_args is not None else None
report_for_verified_only = generate_grade_report_for_verified_only()
enrolled_students = CourseEnrollment.objects.users_enrolled_in(
course_id=course_id,
include_inactive=True,
verified_only=report_for_verified_only,
)
task_progress = TaskProgress(action_name, enrolled_students.count(), start_time)
# This struct encapsulates both the display names of each static item in the
# 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')])
course = get_course_by_id(course_id)
log_task_info(u'Retrieving graded scorable blocks')
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(list(graded_scorable_blocks.values()))
]
error_rows = [list(header_row.values()) + ['error_msg']]
# Bulk fetch and cache enrollment states so we can efficiently determine
# whether each user is currently enrolled in the course.
log_task_info(u'Fetching enrollment status')
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:
step = u'Calculating Grades'
task_progress.update_task_state(extra_meta={'step': step})
log_message = u'{0} {1}/{2}'.format(step, task_progress.attempted, task_progress.total)
log_task_info(log_message)
log_task_info('Uploading CSV to store')
# 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 = grades_context.grading_context_for_course(course)
for assignment_type_name, subsection_infos in six.iteritems(grading_context['all_graded_subsections_by_type']):
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 _build_problem_list(cls, course_blocks, root, path=None):
"""
Generate a tuple of display names, block location paths and block keys
for all problem blocks under the ``root`` block.
Arguments:
course_blocks (BlockStructureBlockData): Block structure for a course.
root (UsageKey): This block and its children will be used to generate
the problem list
path (List[str]): The list of display names for the parent of root block
Yields:
Tuple[str, List[str], UsageKey]: tuple of a block's display name, path, and
usage key
"""
name = course_blocks.get_xblock_field(root, 'display_name') or root.category
if path is None:
path = [name]
yield name, path, root
for block in course_blocks.get_children(root):
name = course_blocks.get_xblock_field(block, 'display_name') or block.category
for result in cls._build_problem_list(course_blocks, block, path + [name]):
yield result
@classmethod
def _build_student_data(cls, user_id, course_key, usage_key_str):
"""
Generate a list of problem responses for all problem under the
``problem_location`` root.
Arguments:
user_id (int): The user id for the user generating the report
course_key (CourseKey): The ``CourseKey`` for the course whose report
is being generated
usage_key_str (str): The generated report will include this
block and it child blocks.
Returns:
Tuple[List[Dict], List[str]]: Returns a list of dictionaries
containing the student data which will be included in the
final csv, and the features/keys to include in that CSV.
"""
usage_key = UsageKey.from_string(usage_key_str).map_into_course(course_key)
user = get_user_model().objects.get(pk=user_id)
course_blocks = get_course_blocks(user, usage_key)
student_data = []
max_count = settings.FEATURES.get('MAX_PROBLEM_RESPONSES_COUNT')
store = modulestore()
user_state_client = DjangoXBlockUserStateClient()
student_data_keys = set()
with store.bulk_operations(course_key):
for title, path, block_key in cls._build_problem_list(course_blocks, usage_key):
# Chapter and sequential blocks are filtered out since they include state
# which isn't useful for this report.
if block_key.block_type in ('sequential', 'chapter'):
continue
block = store.get_item(block_key)
generated_report_data = defaultdict(list)
# Blocks can implement the generate_report_data method to provide their own
# human-readable formatting for user state.
if hasattr(block, 'generate_report_data'):
try:
user_state_iterator = user_state_client.iter_all_for_block(block_key)
for username, state in block.generate_report_data(user_state_iterator, max_count):
generated_report_data[username].append(state)
except NotImplementedError:
pass
responses = []
for response in list_problem_responses(course_key, block_key, max_count):
response['title'] = title
# A human-readable location for the current block
response['location'] = ' > '.join(path)
# A machine-friendly location for the current block
response['block_key'] = str(block_key)
# A block that has a single state per user can contain multiple responses
# within the same state.
user_states = generated_report_data.get(response['username'], [])
if user_states:
# For each response in the block, copy over the basic data like the
# title, location, block_key and state, and add in the responses
for user_state in user_states:
user_response = response.copy()
user_response.update(user_state)
student_data_keys = student_data_keys.union(list(user_state.keys()))
responses.append(user_response)
else:
responses.append(response)
student_data += responses
if max_count is not None:
max_count -= len(responses)
if max_count <= 0:
break
# Keep the keys in a useful order, starting with username, title and location,
# then the columns returned by the xblock report generator in sorted order and
# finally end with the more machine friendly block_key and state.
student_data_keys_list = (
['username', 'title', 'location'] +
sorted(student_data_keys) +
['block_key', 'state']
)
return student_data, student_data_keys_list
@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)
problem_location = task_input.get('problem_location')
# Compute result table and format it
student_data, student_data_keys = cls._build_student_data(
user_id=task_input.get('user_id'),
course_key=course_id,
usage_key_str=problem_location
)
for data in student_data:
for key in student_data_keys:
data.setdefault(key, '')
header, rows = format_dictlist(student_data, student_data_keys)
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)
report_name = upload_csv_to_report_store(rows, csv_name, course_id, start_date)
current_step = {'step': 'CSV uploaded', 'report_name': report_name}
return task_progress.update_task_state(extra_meta=current_step)