def test_get_training_example_invalid_rubric(self):
# Rubric is missing a very important key!
invalid_rubric = copy.deepcopy(RUBRIC)
del invalid_rubric['criteria']
with self.assertRaises(StudentTrainingRequestError):
training_api.get_training_example(self.submission_uuid, invalid_rubric, EXAMPLES)
def test_get_training_example_invalid_rubric(self):
# Rubric is missing a very important key!
invalid_rubric = copy.deepcopy(RUBRIC)
del invalid_rubric['criteria']
with self.assertRaises(StudentTrainingRequestError):
training_api.get_training_example(self.submission_uuid, invalid_rubric, EXAMPLES)
def test_assess_training_example_database_error(self, mock_db):
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
mock_db.side_effect = DatabaseError("Kaboom!")
with self.assertRaises(StudentTrainingInternalError):
training_api.assess_training_example(
self.submission_uuid, EXAMPLES[0]['options_selected'])
def test_get_num_completed_num_queries(self):
# Complete the first training example
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
# Check the number completed
with self.assertNumQueries(2):
training_api.get_num_completed(self.submission_uuid)
def test_get_same_example(self):
# Retrieve a training example
retrieved = training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
# If we retrieve an example without completing the current example,
# we should get the same one.
next_retrieved = training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
self.assertEqual(retrieved, next_retrieved)
def test_assess_training_example_num_queries(self):
# Populate the cache with training examples and rubrics
self._warm_cache(RUBRIC, EXAMPLES)
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
with self.assertNumQueries(3):
training_api.assess_training_example(
self.submission_uuid, EXAMPLES[0]['options_selected'])
def test_get_same_example(self):
# Retrieve a training example
retrieved = training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
# If we retrieve an example without completing the current example,
# we should get the same one.
next_retrieved = training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
self.assertEqual(retrieved, next_retrieved)
def test_get_num_completed_num_queries(self):
# Complete the first training example
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
# Check the number completed
with self.assertNumQueries(2):
training_api.get_num_completed(self.submission_uuid)
def test_submitter_is_finished_num_queries(self):
# Complete the first training example
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
# Check whether we've completed the requirements
requirements = {'num_required': 2}
with self.assertNumQueries(2):
training_api.submitter_is_finished(self.submission_uuid, requirements)
def test_assess_training_example_completed_workflow(self):
for example in EXAMPLES:
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, example['options_selected'])
# Try to assess again, and expect an error
with self.assertRaises(StudentTrainingRequestError):
training_api.assess_training_example(
self.submission_uuid, EXAMPLES[0]['options_selected']
)
def test_assess_training_example_completed_workflow(self):
for example in EXAMPLES:
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, example['options_selected'])
# Try to assess again, and expect an error
with self.assertRaises(StudentTrainingRequestError):
training_api.assess_training_example(
self.submission_uuid, EXAMPLES[0]['options_selected']
)
def test_submitter_is_finished_num_queries(self):
# Complete the first training example
training_api.on_start(self.submission_uuid)
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
# Check whether we've completed the requirements
requirements = {'num_required': 2}
with self.assertNumQueries(2):
training_api.submitter_is_finished(self.submission_uuid, requirements)
def test_assess_training_example_database_error(self):
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
with patch(
'openassessment.assessment.models.student_training.StudentTrainingWorkflow.objects.get'
) as mock_db:
mock_db.side_effect = DatabaseError("Kaboom!")
with self.assertRaises(StudentTrainingInternalError):
training_api.assess_training_example(
self.submission_uuid, EXAMPLES[0]['options_selected'])
def test_get_training_example_none_available(self):
for example in EXAMPLES:
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, example['options_selected'])
# Now we should be complete
self._assert_workflow_status(self.submission_uuid, 2, 2)
# ... and if we try to get another example, we should get None
self.assertIs(
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES),
None
)
def test_get_training_example_none_available(self):
for example in EXAMPLES:
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
training_api.assess_training_example(self.submission_uuid, example['options_selected'])
# Now we should be complete
self._assert_workflow_status(self.submission_uuid, 2, 2)
# ... and if we try to get another example, we should get None
self.assertIs(
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES),
None
)
def test_assess_without_update(self):
# Assess the first training example the same way the instructor did
# but do NOT update the workflow
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
corrections = training_api.assess_training_example(
self.submission_uuid,
EXAMPLES[0]['options_selected'],
update_workflow=False)
# Expect that we're still on the first step
self.assertEqual(corrections, dict())
self._assert_workflow_status(self.submission_uuid, 0, 2)
def test_assess_without_update(self):
# Assess the first training example the same way the instructor did
# but do NOT update the workflow
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
corrections = training_api.assess_training_example(
self.submission_uuid,
EXAMPLES[0]['options_selected'],
update_workflow=False
)
# Expect that we're still on the first step
self.assertEqual(corrections, dict())
self._assert_workflow_status(self.submission_uuid, 0, 2)
def _warm_cache(self, rubric, examples):
"""
Create a submission and complete student training.
This will populate the cache with training examples and rubrics,
which are immutable and shared for all students training on a particular problem.
Args:
rubric (dict): Serialized rubric model.
examples (list of dict): Serialized training examples
Returns:
None
"""
pre_submission = sub_api.create_submission(STUDENT_ITEM, ANSWER)
for example in examples:
training_api.get_training_example(pre_submission['uuid'], rubric, examples)
training_api.assess_training_example(pre_submission['uuid'], example['options_selected'])
def _warm_cache(self, rubric, examples):
"""
Create a submission and complete student training.
This will populate the cache with training examples and rubrics,
which are immutable and shared for all students training on a particular problem.
Args:
rubric (dict): Serialized rubric model.
examples (list of dict): Serialized training examples
Returns:
None
"""
pre_submission = sub_api.create_submission(STUDENT_ITEM, ANSWER)
training_api.on_start(pre_submission['uuid'])
for example in examples:
training_api.get_training_example(pre_submission['uuid'], rubric, examples)
training_api.assess_training_example(pre_submission['uuid'], example['options_selected'])
def test_get_training_example_num_queries(self):
# Run through the training example once using a different submission
# Training examples and rubrics will be cached and shared for other
# students working on the same problem.
self._warm_cache(RUBRIC, EXAMPLES)
# First training example
# This will need to create the student training workflow and the first item
# NOTE: we *could* cache the rubric model to reduce the number of queries here,
# but we're selecting it by content hash, which is indexed and should be plenty fast.
with self.assertNumQueries(8):
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
# Without assessing the first training example, try to retrieve a training example.
# This should return the same example as before, so we won't need to create
# any workflows or workflow items.
with self.assertNumQueries(5):
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
# Assess the current training example
training_api.assess_training_example(self.submission_uuid,
EXAMPLES[0]['options_selected'])
# Retrieve the next training example, which requires us to create
# a new workflow item (but not a new workflow).
with self.assertNumQueries(8):
training_api.get_training_example(self.submission_uuid, RUBRIC,
EXAMPLES)
def test_get_training_example_num_queries(self):
# Run through the training example once using a different submission
# Training examples and rubrics will be cached and shared for other
# students working on the same problem.
self._warm_cache(RUBRIC, EXAMPLES)
# First training example
# This will need to create the student training workflow and the first item
# NOTE: we *could* cache the rubric model to reduce the number of queries here,
# but we're selecting it by content hash, which is indexed and should be plenty fast.
with self.assertNumQueries(6):
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
# Without assessing the first training example, try to retrieve a training example.
# This should return the same example as before, so we won't need to create
# any workflows or workflow items.
with self.assertNumQueries(3):
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
# Assess the current training example
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
# Retrieve the next training example, which requires us to create
# a new workflow item (but not a new workflow).
with self.assertNumQueries(4):
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
def _assert_get_example(self, submission_uuid, order_num, input_examples, input_rubric):
"""
Check the training example we get from the API.
Args:
submission_uuid (str): The submission UUID associated with the student being trained.
order_num (int): The order number of the example we expect to retrieve.
input_examples (list of dict): The examples we used to configure the training workflow.
input_rubric (dict): The rubric we used to configure the training workflow.
Returns:
None
Raises:
AssertionError
"""
example = training_api.get_training_example(submission_uuid, input_rubric, input_examples)
expected_example = self._expected_example(input_examples[order_num], input_rubric)
self.assertItemsEqual(example, expected_example)
def _assert_get_example(self, submission_uuid, order_num, input_examples, input_rubric):
"""
Check the training example we get from the API.
Args:
submission_uuid (str): The submission UUID associated with the student being trained.
order_num (int): The order number of the example we expect to retrieve.
input_examples (list of dict): The examples we used to configure the training workflow.
input_rubric (dict): The rubric we used to configure the training workflow.
Returns:
None
Raises:
AssertionError
"""
example = training_api.get_training_example(submission_uuid, input_rubric, input_examples)
expected_example = self._expected_example(input_examples[order_num], input_rubric)
six.assertCountEqual(self, example, expected_example)
def training_path_and_context(self):
"""
Return the template path and context used to render the student training step.
Returns:
tuple of `(path, context)` where `path` is the path to the template and
`context` is a dict.
"""
# Retrieve the status of the workflow.
# If no submissions have been created yet, the status will be None.
workflow_status = self.get_workflow_info().get('status')
problem_closed, reason, start_date, due_date = self.is_closed(
step="student-training")
context = {}
template = 'openassessmentblock/student_training/student_training_unavailable.html'
# add allow_latex field to the context
context['allow_latex'] = self.allow_latex
if not workflow_status:
return template, context
# If the student has completed the training step, then show that the step is complete.
# We put this condition first so that if a student has completed the step, it *always*
# shows as complete.
# We're assuming here that the training step always precedes the other assessment steps
# (peer/self) -- we may need to make this more flexible later.
if workflow_status == 'cancelled':
template = 'openassessmentblock/student_training/student_training_cancelled.html'
elif workflow_status and workflow_status != "training":
template = 'openassessmentblock/student_training/student_training_complete.html'
# If the problem is closed, then do not allow students to access the training step
elif problem_closed and reason == 'start':
context['training_start'] = start_date
template = 'openassessmentblock/student_training/student_training_unavailable.html'
elif problem_closed and reason == 'due':
context['training_due'] = due_date
template = 'openassessmentblock/student_training/student_training_closed.html'
# If we're on the training step, show the student an example
# We do this last so we can avoid querying the student training API if possible.
else:
training_module = self.get_assessment_module('student-training')
if not training_module:
return template, context
if due_date < DISTANT_FUTURE:
context['training_due'] = due_date
# Report progress in the student training workflow (completed X out of Y)
context['training_num_available'] = len(
training_module["examples"])
context[
'training_num_completed'] = student_training.get_num_completed(
self.submission_uuid)
context[
'training_num_current'] = context['training_num_completed'] + 1
# Retrieve the example essay for the student to submit
# This will contain the essay text, the rubric, and the options the instructor selected.
examples = convert_training_examples_list_to_dict(
training_module["examples"])
example = student_training.get_training_example(
self.submission_uuid, {
'prompt': self.prompt,
'criteria': self.rubric_criteria_with_labels
}, examples)
if example:
context['training_essay'] = create_submission_dict(
{'answer': example['answer']}, self.prompts)
context['training_rubric'] = {
'criteria': example['rubric']['criteria'],
'points_possible': example['rubric']['points_possible']
}
template = 'openassessmentblock/student_training/student_training.html'
else:
logger.error(
"No training example was returned from the API for student "
"with Submission UUID {}".format(self.submission_uuid))
template = "openassessmentblock/student_training/student_training_error.html"
return template, context
def training_path_and_context(self):
"""
Return the template path and context used to render the student training step.
Returns:
tuple of `(path, context)` where `path` is the path to the template and
`context` is a dict.
"""
# Retrieve the status of the workflow.
# If no submissions have been created yet, the status will be None.
workflow_status = self.get_workflow_info().get('status')
problem_closed, reason, start_date, due_date = self.is_closed(step="student-training")
context = {}
template = 'openassessmentblock/student_training/student_training_unavailable.html'
# add allow_latex field to the context
context['allow_latex'] = self.allow_latex
if not workflow_status:
return template, context
# If the student has completed the training step, then show that the step is complete.
# We put this condition first so that if a student has completed the step, it *always*
# shows as complete.
# We're assuming here that the training step always precedes the other assessment steps
# (peer/self) -- we may need to make this more flexible later.
if workflow_status == 'cancelled':
template = 'openassessmentblock/student_training/student_training_cancelled.html'
elif workflow_status and workflow_status != "training":
template = 'openassessmentblock/student_training/student_training_complete.html'
# If the problem is closed, then do not allow students to access the training step
elif problem_closed and reason == 'start':
context['training_start'] = start_date
template = 'openassessmentblock/student_training/student_training_unavailable.html'
elif problem_closed and reason == 'due':
context['training_due'] = due_date
template = 'openassessmentblock/student_training/student_training_closed.html'
# If we're on the training step, show the student an example
# We do this last so we can avoid querying the student training API if possible.
else:
training_module = self.get_assessment_module('student-training')
if not training_module:
return template, context
if due_date < DISTANT_FUTURE:
context['training_due'] = due_date
# Report progress in the student training workflow (completed X out of Y)
context['training_num_available'] = len(training_module["examples"])
context['training_num_completed'] = student_training.get_num_completed(self.submission_uuid)
context['training_num_current'] = context['training_num_completed'] + 1
# Retrieve the example essay for the student to submit
# This will contain the essay text, the rubric, and the options the instructor selected.
examples = convert_training_examples_list_to_dict(training_module["examples"])
example = student_training.get_training_example(
self.submission_uuid,
{
'prompt': self.prompt,
'criteria': self.rubric_criteria_with_labels
},
examples
)
if example:
context['training_essay'] = create_submission_dict({'answer': example['answer']}, self.prompts)
context['training_rubric'] = {
'criteria': example['rubric']['criteria'],
'points_possible': example['rubric']['points_possible']
}
template = 'openassessmentblock/student_training/student_training.html'
else:
logger.error(
"No training example was returned from the API for student "
"with Submission UUID {}".format(self.submission_uuid)
)
template = "openassessmentblock/student_training/student_training_error.html"
return template, context
def test_get_training_example_no_submission(self):
with self.assertRaises(StudentTrainingRequestError):
training_api.get_training_example("no_such_submission", RUBRIC,
EXAMPLES)
def test_assess_training_example_num_queries(self):
# Populate the cache with training examples and rubrics
self._warm_cache(RUBRIC, EXAMPLES)
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
with self.assertNumQueries(4):
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
def test_assess_training_example_database_error(self, mock_db):
training_api.get_training_example(self.submission_uuid, RUBRIC, EXAMPLES)
mock_db.side_effect = DatabaseError("Kaboom!")
with self.assertRaises(StudentTrainingInternalError):
training_api.assess_training_example(self.submission_uuid, EXAMPLES[0]['options_selected'])
def test_get_training_example_no_submission(self):
with self.assertRaises(StudentTrainingRequestError):
training_api.get_training_example("no_such_submission", RUBRIC, EXAMPLES)