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edx-platform
Commit 2aac2b9d by Nimisha Asthagiri
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Update Grade Report to distinguish between Not Attempted and 0

parent e87388e2
Showing with 91 additions and 107 deletions
lms/djangoapps/instructor_task/tasks_helper.py
......@@ -46,7 +46,8 @@ from certificates.models import (
)
from certificates.api import generate_user_certificates
from courseware.courses import get_course_by_id, get_problems_in_section
from lms.djangoapps.grades.course_grades import iterate_grades_for
from lms.djangoapps.grades.context import grading_context_for_course
from lms.djangoapps.grades.new.course_grade import CourseGradeFactory
from courseware.models import StudentModule
from courseware.model_data import DjangoKeyValueStore, FieldDataCache
from courseware.module_render import get_module_for_descriptor_internal
......@@ -62,7 +63,6 @@ from lms.djangoapps.instructor_task.models import ReportStore, InstructorTask, P
from lms.djangoapps.lms_xblock.runtime import LmsPartitionService
from openedx.core.djangoapps.course_groups.cohorts import get_cohort
from openedx.core.djangoapps.course_groups.models import CourseUserGroup
from openedx.core.djangoapps.content.course_structures.models import CourseStructure
from opaque_keys.edx.keys import UsageKey
from openedx.core.djangoapps.course_groups.cohorts import add_user_to_cohort, is_course_cohorted
from student.models import CourseEnrollment, CourseAccessRole
......@@ -670,7 +670,8 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
start_date = datetime.now(UTC)
status_interval = 100
enrolled_students = CourseEnrollment.objects.users_enrolled_in(course_id)
task_progress = TaskProgress(action_name, enrolled_students.count(), start_time)
total_enrolled_students = enrolled_students.count()
task_progress = TaskProgress(action_name, total_enrolled_students, start_time)
fmt = u'Task: {task_id}, InstructorTask ID: {entry_id}, Course: {course_id}, Input: {task_input}'
task_info_string = fmt.format(
......@@ -700,17 +701,16 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
err_rows = [["id", "username", "error_msg"]]
current_step = {'step': 'Calculating Grades'}
total_enrolled_students = enrolled_students.count()
student_counter = 0
TASK_LOG.info(
u'%s, Task type: %s, Current step: %s, Starting grade calculation for total students: %s',
task_info_string,
action_name,
current_step,
total_enrolled_students
total_enrolled_students,
)
for student, gradeset, err_msg in iterate_grades_for(course_id, enrolled_students):
# NAA TODO - Get the list of ALL subsections to put in the header
for student, course_grade, err_msg in CourseGradeFactory().iter(course, enrolled_students):
# Periodically update task status (this is a cache write)
if task_progress.attempted % status_interval == 0:
task_progress.update_task_state(extra_meta=current_step)
......@@ -728,11 +728,11 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
total_enrolled_students
)
if gradeset:
if course_grade:
# We were able to successfully grade this student for this course.
task_progress.succeeded += 1
if not header:
header = [section['label'] for section in gradeset[u'section_breakdown']]
header = [section['label'] for section in course_grade.summary[u'section_breakdown']]
rows.append(
["id", "email", "username", "grade"] + header + cohorts_header +
group_configs_header + teams_header +
......@@ -741,7 +741,7 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
percents = {
section['label']: section.get('percent', 0.0)
for section in gradeset[u'section_breakdown']
for section in course_grade.summary[u'section_breakdown']
if 'label' in section
}
......@@ -772,7 +772,7 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
certificate_info = certificate_info_for_user(
student,
course_id,
gradeset['grade'],
course_grade.letter_grade,
student.id in whitelisted_user_ids
)
......@@ -784,7 +784,7 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
# still have 100% for the course.
row_percents = [percents.get(label, 0.0) for label in header]
rows.append(
[student.id, student.email, student.username, gradeset['percent']] +
[student.id, student.email, student.username, course_grade.percent] +
row_percents + cohorts_group_name + group_configs_group_names + team_name +
[enrollment_mode] + [verification_status] + certificate_info
)
......@@ -819,54 +819,33 @@ def upload_grades_csv(_xmodule_instance_args, _entry_id, course_id, _task_input,
return task_progress.update_task_state(extra_meta=current_step)
def _order_problems(blocks):
def _order_graded_scorable_blocks(course_key):
"""
Sort the problems by the assignment type and assignment that it belongs to.
Args:
blocks (OrderedDict) - A course structure containing blocks that have been ordered
(i.e. when we iterate over them, we will see them in the order
that they appear in the course).
Sort each graded scorable block by the assignment type and
subsection that it belongs to.
Returns:
an OrderedDict that maps a problem id to its headers in the final report.
an OrderedDict that maps a scorable block's id to its
headers in the final report.
"""
problems = OrderedDict()
assignments = OrderedDict()
# First, sort out all the blocks into their correct assignments and all the
# assignments into their correct types.
for block in blocks:
# Put the assignments in order into the assignments list.
if blocks[block]['block_type'] == 'sequential':
block_format = blocks[block]['format']
if block_format not in assignments:
assignments[block_format] = OrderedDict()
assignments[block_format][block] = list()
# Put the problems into the correct order within their assignment.
if blocks[block]['block_type'] == 'problem' and blocks[block]['graded'] is True:
current = blocks[block]['parent']
# crawl up the tree for the sequential block
while blocks[current]['block_type'] != 'sequential':
current = blocks[current]['parent']
current_format = blocks[current]['format']
assignments[current_format][current].append(block)
# Now that we have a sorting and an order for the assignments and problems,
# iterate through them in order to generate the header row.
for assignment_type in assignments:
for assignment_index, assignment in enumerate(assignments[assignment_type].keys(), start=1):
for problem in assignments[assignment_type][assignment]:
header_name = u"{assignment_type} {assignment_index}: {assignment_name} - {block}".format(
block=blocks[problem]['display_name'],
assignment_type=assignment_type,
assignment_index=assignment_index,
assignment_name=blocks[assignment]['display_name']
scorable_blocks = OrderedDict()
grading_context = grading_context_for_course(course_key)
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):
subsection = subsection_info['subsection_block']
if subsection.graded:
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.display_name,
)
problems[problem] = [header_name + " (Earned)", header_name + " (Possible)"]
return problems
scorable_blocks[scorable_block.location] = [header_name + " (Earned)", header_name + " (Possible)"]
return scorable_blocks
def upload_problem_responses_csv(_xmodule_instance_args, _entry_id, course_id, task_input, action_name):
......@@ -919,49 +898,39 @@ def upload_problem_grade_report(_xmodule_instance_args, _entry_id, course_id, _t
# as the keys. It is structured in this way to keep the values related.
header_row = OrderedDict([('id', 'Student ID'), ('email', 'Email'), ('username', 'Username')])
try:
course_structure = CourseStructure.objects.get(course_id=course_id)
blocks = course_structure.ordered_blocks
problems = _order_problems(blocks)
except CourseStructure.DoesNotExist:
return task_progress.update_task_state(
extra_meta={'step': 'Generating course structure. Please refresh and try again.'}
)
graded_scorable_blocks = _order_graded_scorable_blocks(course_id)
# Just generate the static fields for now.
rows = [list(header_row.values()) + ['Final Grade'] + list(chain.from_iterable(problems.values()))]
rows = [list(header_row.values()) + ['Final Grade'] + list(chain.from_iterable(graded_scorable_blocks.values()))]
error_rows = [list(header_row.values()) + ['error_msg']]
current_step = {'step': 'Calculating Grades'}
for student, gradeset, err_msg in iterate_grades_for(course_id, enrolled_students):
course = get_course_by_id(course_id)
for student, course_grade, err_msg in CourseGradeFactory().iter(course, enrolled_students):
student_fields = [getattr(student, field_name) for field_name in header_row]
task_progress.attempted += 1
if 'percent' not in gradeset or 'raw_scores' not in gradeset:
if not course_grade:
# There was an error grading this student.
# Generally there will be a non-empty err_msg, but that is not always the case.
if not err_msg:
err_msg = u"Unknown error"
err_msg = 'Unknown error'
error_rows.append(student_fields + [err_msg])
task_progress.failed += 1
continue
final_grade = gradeset['percent']
# Only consider graded problems
problem_scores = {unicode(score.module_id): score for score in gradeset['raw_scores'] if score.graded}
earned_possible_values = list()
for problem_id in problems:
for block_location in graded_scorable_blocks:
try:
problem_score = problem_scores[problem_id]
earned_possible_values.append([problem_score.earned, problem_score.possible])
problem_score = course_grade.locations_to_scores[block_location]
except KeyError:
# The student has not been graded on this problem. For example,
# iterate_grades_for skips problems that students have never
# seen in order to speed up report generation. It could also be
# the case that the student does not have access to it (e.g. A/B
# test or cohorted courseware).
earned_possible_values.append(['N/A', 'N/A'])
rows.append(student_fields + [final_grade] + list(chain.from_iterable(earned_possible_values)))
earned_possible_values.append(['Not Accessible', 'Not Accessible'])
else:
if problem_score.attempted:
earned_possible_values.append([problem_score.earned, problem_score.possible])
else:
earned_possible_values.append(['Not Attempted', problem_score.possible])
rows.append(student_fields + [course_grade.percent] + list(chain.from_iterable(earned_possible_values)))
task_progress.succeeded += 1
if task_progress.attempted % status_interval == 0:
......
lms/djangoapps/instructor_task/tests/test_tasks_helper.py
......@@ -15,7 +15,7 @@ import urllib
import ddt
from freezegun import freeze_time
from mock import Mock, patch
from mock import Mock, patch, MagicMock
from nose.plugins.attrib import attr
import tempfile
import unicodecsv
......@@ -115,15 +115,14 @@ class TestInstructorGradeReport(InstructorGradeReportTestCase):
self.assertDictContainsSubset({'attempted': num_students, 'succeeded': num_students, 'failed': 0}, result)
@patch('lms.djangoapps.instructor_task.tasks_helper._get_current_task')
@patch('lms.djangoapps.instructor_task.tasks_helper.iterate_grades_for')
def test_grading_failure(self, mock_iterate_grades_for, _mock_current_task):
@patch('lms.djangoapps.grades.new.course_grade.CourseGradeFactory.iter')
def test_grading_failure(self, mock_grades_iter, _mock_current_task):
"""
Test that any grading errors are properly reported in the
progress dict and uploaded to the report store.
"""
# mock an error response from `iterate_grades_for`
mock_iterate_grades_for.return_value = [
(self.create_student('username', 'student@example.com'), {}, 'Cannot grade student')
mock_grades_iter.return_value = [
(self.create_student('username', 'student@example.com'), None, 'Cannot grade student')
]
result = upload_grades_csv(None, None, self.course.id, None, 'graded')
self.assertDictContainsSubset({'attempted': 1, 'succeeded': 0, 'failed': 1}, result)
......@@ -293,17 +292,20 @@ class TestInstructorGradeReport(InstructorGradeReportTestCase):
)
@patch('lms.djangoapps.instructor_task.tasks_helper._get_current_task')
@patch('lms.djangoapps.instructor_task.tasks_helper.iterate_grades_for')
def test_unicode_in_csv_header(self, mock_iterate_grades_for, _mock_current_task):
@patch('lms.djangoapps.grades.new.course_grade.CourseGradeFactory.iter')
def test_unicode_in_csv_header(self, mock_grades_iter, _mock_current_task):
"""
Tests that CSV grade report works if unicode in headers.
"""
# mock a response from `iterate_grades_for`
mock_iterate_grades_for.return_value = [
mock_course_grade = MagicMock()
mock_course_grade.summary = {'section_breakdown': [{'label': u'\u8282\u540e\u9898 01'}]}
mock_course_grade.letter_grade = None
mock_course_grade.percent = 0
mock_grades_iter.return_value = [
(
self.create_student('username', 'student@example.com'),
{'section_breakdown': [{'label': u'\u8282\u540e\u9898 01'}], 'percent': 0, 'grade': None},
'Cannot grade student'
mock_course_grade,
'',
)
]
result = upload_grades_csv(None, None, self.course.id, None, 'graded')
......@@ -631,7 +633,8 @@ class TestProblemGradeReport(TestReportMixin, InstructorTaskModuleTestCase):
unicode(self.student_1.id),
self.student_1.email,
self.student_1.username,
'0.01', '1.0', '2.0']
'0.01', '1.0', '2.0',
]
)),
dict(zip(
header_row,
......@@ -639,23 +642,22 @@ class TestProblemGradeReport(TestReportMixin, InstructorTaskModuleTestCase):
unicode(self.student_2.id),
self.student_2.email,
self.student_2.username,
'0.0', '0.0', '2'
'0.0', 'Not Attempted', '2.0',
]
))
])
@patch('lms.djangoapps.instructor_task.tasks_helper._get_current_task')
@patch('lms.djangoapps.instructor_task.tasks_helper.iterate_grades_for')
@patch('lms.djangoapps.grades.new.course_grade.CourseGradeFactory.iter')
@ddt.data(u'Cannot grade student', '')
def test_grading_failure(self, error_message, mock_iterate_grades_for, _mock_current_task):
def test_grading_failure(self, error_message, mock_grades_iter, _mock_current_task):
"""
Test that any grading errors are properly reported in the progress
dict and uploaded to the report store.
"""
# mock an error response from `iterate_grades_for`
student = self.create_student(u'username', u'student@example.com')
mock_iterate_grades_for.return_value = [
(student, {}, error_message)
mock_grades_iter.return_value = [
(student, None, error_message)
]
result = upload_problem_grade_report(None, None, self.course.id, None, 'graded')
self.assertDictContainsSubset({'attempted': 1, 'succeeded': 0, 'failed': 1}, result)
......@@ -694,7 +696,8 @@ class TestProblemReportSplitTestContent(TestReportMixin, TestConditionalContent,
In order to verify that the behavior of the grade report is correct, we submit answers for problems
that the student won't have access to. A/B tests won't restrict access to the problems, but it should
not show up in that student's course tree when generating the grade report, hence the N/A's in the grade report.
not show up in that student's course tree when generating the grade report, hence the Not Accessible's
in the grade report.
"""
# student A will get 100%, student B will get 50% because
# OPTION_1 is the correct option, and OPTION_2 is the
......@@ -723,7 +726,7 @@ class TestProblemReportSplitTestContent(TestReportMixin, TestConditionalContent,
unicode(self.student_a.id),
self.student_a.email,
self.student_a.username,
u'1.0', u'2.0', u'2.0', u'N/A', u'N/A'
u'1.0', u'2.0', u'2.0', u'Not Accessible', u'Not Accessible'
]
)),
dict(zip(
......@@ -731,7 +734,7 @@ class TestProblemReportSplitTestContent(TestReportMixin, TestConditionalContent,
[
unicode(self.student_b.id),
self.student_b.email,
self.student_b.username, u'0.5', u'N/A', u'N/A', u'1.0', u'2.0'
self.student_b.username, u'0.5', u'Not Accessible', u'Not Accessible', u'1.0', u'2.0'
]
))
])
......@@ -864,10 +867,22 @@ class TestProblemReportCohortedContent(TestReportMixin, ContentGroupTestCase, In
header_row += [problem + ' (Earned)', problem + ' (Possible)']
user_grades = [
{'user': self.staff_user, 'grade': [u'0.0', u'N/A', u'N/A', u'N/A', u'N/A']},
{'user': self.alpha_user, 'grade': [u'1.0', u'2.0', u'2.0', u'N/A', u'N/A']},
{'user': self.beta_user, 'grade': [u'0.5', u'N/A', u'N/A', u'1.0', u'2.0']},
{'user': self.non_cohorted_user, 'grade': [u'0.0', u'N/A', u'N/A', u'N/A', u'N/A']},
{
'user': self.staff_user,
'grade': [u'0.0', u'Not Accessible', u'Not Accessible', u'Not Accessible', u'Not Accessible'],
},
{
'user': self.alpha_user,
'grade': [u'1.0', u'2.0', u'2.0', u'Not Accessible', u'Not Accessible'],
},
{
'user': self.beta_user,
'grade': [u'0.5', u'Not Accessible', u'Not Accessible', u'1.0', u'2.0'],
},
{
'user': self.non_cohorted_user,
'grade': [u'0.0', u'Not Accessible', u'Not Accessible', u'Not Accessible', u'Not Accessible'],
},
]
# Verify generated grades and expected grades match
......
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