def grade(student, request, course, keep_raw_scores, field_data_cache, scores_client):
"""
This grades a student as quickly as possible. It returns the
output from the course grader, augmented with the final letter
grade. The keys in the output are:
course: a CourseDescriptor
- grade : A final letter grade.
- percent : The final percent for the class (rounded up).
- section_breakdown : A breakdown of each section that makes
up the grade. (For display)
- grade_breakdown : A breakdown of the major components that
make up the final grade. (For display)
- keep_raw_scores : if True, then value for key 'raw_scores' contains scores
for every graded module
More information on the format is in the docstring for CourseGrader.
"""
if field_data_cache is None:
with manual_transaction():
field_data_cache = field_data_cache_for_grading(course, student)
if scores_client is None:
scores_client = ScoresClient.from_field_data_cache(field_data_cache)
# Dict of item_ids -> (earned, possible) point tuples. This *only* grabs
# scores that were registered with the submissions API, which for the moment
# means only openassessment (edx-ora2)
submissions_scores = sub_api.get_scores(
course.id.to_deprecated_string(), anonymous_id_for_user(student, course.id)
)
max_scores_cache = MaxScoresCache.create_for_course(course)
# For the moment, we have to get scorable_locations from field_data_cache
# and not from scores_client, because scores_client is ignorant of things
# in the submissions API. As a further refactoring step, submissions should
# be hidden behind the ScoresClient.
max_scores_cache.fetch_from_remote(field_data_cache.scorable_locations)
grading_context = course.grading_context
raw_scores = []
totaled_scores = {}
# This next complicated loop is just to collect the totaled_scores, which is
# passed to the grader
for section_format, sections in grading_context['graded_sections'].iteritems():
format_scores = []
for section in sections:
section_descriptor = section['section_descriptor']
section_name = section_descriptor.display_name_with_default
# some problems have state that is updated independently of interaction
# with the LMS, so they need to always be scored. (E.g. foldit.,
# combinedopenended)
should_grade_section = any(
descriptor.always_recalculate_grades for descriptor in section['xmoduledescriptors']
)
# If there are no problems that always have to be regraded, check to
# see if any of our locations are in the scores from the submissions
# API. If scores exist, we have to calculate grades for this section.
if not should_grade_section:
should_grade_section = any(
descriptor.location.to_deprecated_string() in submissions_scores
for descriptor in section['xmoduledescriptors']
)
if not should_grade_section:
should_grade_section = any(
descriptor.location in scores_client for descriptor in section['xmoduledescriptors']
)
# If we haven't seen a single problem in the section, we don't have
# to grade it at all! We can assume 0%
if should_grade_section:
scores = []
def create_module(descriptor):
'''creates an XModule instance given a descriptor'''
# TODO: We need the request to pass into here. If we could forego that, our arguments
# would be simpler
return get_module_for_descriptor(
student, request, descriptor, field_data_cache, course.id, course=course
)
descendants = yield_dynamic_descriptor_descendants(section_descriptor, student.id, create_module)
for module_descriptor in descendants:
(correct, total) = get_score(
student,
module_descriptor,
create_module,
scores_client,
submissions_scores,
max_scores_cache,
)
if correct is None and total is None:
continue
if settings.GENERATE_PROFILE_SCORES: # for debugging!
if total > 1:
correct = random.randrange(max(total - 2, 1), total + 1)
else:
correct = total
graded = module_descriptor.graded
if not total > 0:
# We simply cannot grade a problem that is 12/0, because we might need it as a percentage
graded = False
scores.append(
Score(
correct,
total,
graded,
module_descriptor.display_name_with_default,
module_descriptor.location
)
)
__, graded_total = aggregate_section_scores(
scores, section_name, getattr(section_descriptor, 'weight', 1.0)
)
if keep_raw_scores:
raw_scores += scores
else:
graded_total = WeightedScore(
0.0, 1.0, True, section_name, None, getattr(section_descriptor, 'weight', 1.0)
)
# Add the graded total to totaled_scores
if graded_total.possible > 0:
format_scores.append(graded_total)
else:
log.info(
"Unable to grade a section with a total possible score of zero. {}".format(
section_descriptor.location
)
)
totaled_scores[section_format] = format_scores
# Grading policy might be overriden by a CCX, need to reset it
course.set_grading_policy(course.grading_policy)
grade_summary = course.grader.grade(totaled_scores, generate_random_scores=settings.GENERATE_PROFILE_SCORES)
# We round the grade here, to make sure that the grade is an whole percentage and
# doesn't get displayed differently than it gets grades
grade_summary['percent'] = round(grade_summary['percent'] * 100 + 0.05) / 100
letter_grade = grade_for_percentage(
course.grade_cutoffs, grade_summary['percent'], grade_summary['sections_passed']
)
grade_summary['grade'] = letter_grade
grade_summary['totaled_scores'] = totaled_scores # make this available, eg for instructor download & debugging
if keep_raw_scores:
# way to get all RAW scores out to instructor
# so grader can be double-checked
grade_summary['raw_scores'] = raw_scores
max_scores_cache.push_to_remote()
return grade_summary
def test_grade_for_percentage(self, percent, sections_passed, expected):
actual = grade_for_percentage(self.GRADE_CUTOFFS, percent, sections_passed)
self.assertEqual(actual, expected)
def grade(student, request, course, keep_raw_scores, field_data_cache,
scores_client):
"""
This grades a student as quickly as possible. It returns the
output from the course grader, augmented with the final letter
grade. The keys in the output are:
course: a CourseDescriptor
- grade : A final letter grade.
- percent : The final percent for the class (rounded up).
- section_breakdown : A breakdown of each section that makes
up the grade. (For display)
- grade_breakdown : A breakdown of the major components that
make up the final grade. (For display)
- keep_raw_scores : if True, then value for key 'raw_scores' contains scores
for every graded module
More information on the format is in the docstring for CourseGrader.
"""
if field_data_cache is None:
with manual_transaction():
field_data_cache = field_data_cache_for_grading(
course, student)
if scores_client is None:
scores_client = ScoresClient.from_field_data_cache(
field_data_cache)
# Dict of item_ids -> (earned, possible) point tuples. This *only* grabs
# scores that were registered with the submissions API, which for the moment
# means only openassessment (edx-ora2)
submissions_scores = sub_api.get_scores(
course.id.to_deprecated_string(),
anonymous_id_for_user(student, course.id))
max_scores_cache = MaxScoresCache.create_for_course(course)
# For the moment, we have to get scorable_locations from field_data_cache
# and not from scores_client, because scores_client is ignorant of things
# in the submissions API. As a further refactoring step, submissions should
# be hidden behind the ScoresClient.
max_scores_cache.fetch_from_remote(field_data_cache.scorable_locations)
grading_context = course.grading_context
raw_scores = []
totaled_scores = {}
# This next complicated loop is just to collect the totaled_scores, which is
# passed to the grader
for section_format, sections in grading_context[
'graded_sections'].iteritems():
format_scores = []
for section in sections:
section_descriptor = section['section_descriptor']
section_name = section_descriptor.display_name_with_default
# some problems have state that is updated independently of interaction
# with the LMS, so they need to always be scored. (E.g. foldit.,
# combinedopenended)
should_grade_section = any(
descriptor.always_recalculate_grades
for descriptor in section['xmoduledescriptors'])
# If there are no problems that always have to be regraded, check to
# see if any of our locations are in the scores from the submissions
# API. If scores exist, we have to calculate grades for this section.
if not should_grade_section:
should_grade_section = any(
descriptor.location.to_deprecated_string() in
submissions_scores
for descriptor in section['xmoduledescriptors'])
if not should_grade_section:
should_grade_section = any(
descriptor.location in scores_client
for descriptor in section['xmoduledescriptors'])
# If we haven't seen a single problem in the section, we don't have
# to grade it at all! We can assume 0%
if should_grade_section:
scores = []
def create_module(descriptor):
'''creates an XModule instance given a descriptor'''
# TODO: We need the request to pass into here. If we could forego that, our arguments
# would be simpler
return get_module_for_descriptor(student,
request,
descriptor,
field_data_cache,
course.id,
course=course)
descendants = yield_dynamic_descriptor_descendants(
section_descriptor, student.id, create_module)
for module_descriptor in descendants:
(correct, total) = get_score(
student,
module_descriptor,
create_module,
scores_client,
submissions_scores,
max_scores_cache,
)
if correct is None and total is None:
continue
if settings.GENERATE_PROFILE_SCORES: # for debugging!
if total > 1:
correct = random.randrange(
max(total - 2, 1), total + 1)
else:
correct = total
graded = module_descriptor.graded
if not total > 0:
# We simply cannot grade a problem that is 12/0, because we might need it as a percentage
graded = False
scores.append(
Score(correct, total, graded,
module_descriptor.display_name_with_default,
module_descriptor.location))
__, graded_total = aggregate_section_scores(
scores, section_name,
getattr(section_descriptor, 'weight', 1.0))
if keep_raw_scores:
raw_scores += scores
else:
graded_total = WeightedScore(
0.0, 1.0, True, section_name, None,
getattr(section_descriptor, 'weight', 1.0))
# Add the graded total to totaled_scores
if graded_total.possible > 0:
format_scores.append(graded_total)
else:
log.info(
"Unable to grade a section with a total possible score of zero. {}"
.format(section_descriptor.location))
totaled_scores[section_format] = format_scores
# Grading policy might be overriden by a CCX, need to reset it
course.set_grading_policy(course.grading_policy)
grade_summary = course.grader.grade(
totaled_scores,
generate_random_scores=settings.GENERATE_PROFILE_SCORES)
# We round the grade here, to make sure that the grade is an whole percentage and
# doesn't get displayed differently than it gets grades
grade_summary['percent'] = round(grade_summary['percent'] * 100 +
0.05) / 100
letter_grade = grade_for_percentage(course.grade_cutoffs,
grade_summary['percent'],
grade_summary['sections_passed'])
grade_summary['grade'] = letter_grade
grade_summary[
'totaled_scores'] = totaled_scores # make this available, eg for instructor download & debugging
if keep_raw_scores:
# way to get all RAW scores out to instructor
# so grader can be double-checked
grade_summary['raw_scores'] = raw_scores
max_scores_cache.push_to_remote()
return grade_summary
