def post_attempt_report(request):
"""Store and process result of a single attempt
POST params:
task-instance-id: int,
attempt: int, counted from 1,
solved: bool,
time: int, number of seconds,
Returns:
task-solved-first-time: bool
earned-credits: int
"""
if request.method != "POST":
return HttpResponseBadRequest('Has to be POST request.')
logger.log_request(request)
body_unicode = request.body.decode('utf-8')
data = json.loads(body_unicode)
processing_result = practice_service.process_attempt_report(
user=request.user, report=data)
response = {
'task-solved-first-time': processing_result.task_solved_first_time,
'time': processing_result.time,
'percentil': processing_result.percentil,
'speed-bonus': processing_result.speed_bonus,
'earned-credits': processing_result.credits,
'progress': [progress_level_to_json(pl) for pl in processing_result.progress]
}
return JsonResponse(response)
def post_attempt_report(request):
"""Store and process result of a single attempt
POST params:
task-instance-id: int,
attempt: int, counted from 1,
solved: bool,
time: int, number of seconds,
Returns:
task-solved-first-time: bool
earned-credits: int
"""
if request.method != "POST":
return HttpResponseBadRequest('Has to be POST request.')
logger.log_request(request)
body_unicode = request.body.decode('utf-8')
data = json.loads(body_unicode)
processing_result = practice_service.process_attempt_report(
user=request.user, report=data)
response = {
'task-solved-first-time':
processing_result.task_solved_first_time,
'time':
processing_result.time,
'percentil':
processing_result.percentil,
'speed-bonus':
processing_result.speed_bonus,
'earned-credits':
processing_result.credits,
'progress':
[progress_level_to_json(pl) for pl in processing_result.progress]
}
return JsonResponse(response)
def run_simulation(self):
"""
Run the simulation and create simulation log as a list of dictionaries,
each dictonary for one task instance taken.
"""
# TODO: decomposition
# create some task instances to avoid time bonuses for poor performances
any_student = StudentModel.objects.create(user=User.objects.create(username='******'))
for task in TaskModel.objects.all():
TaskInstanceModel.objects.create(task=task, student=any_student,
solved=True, time_spent=300)
user = User.objects.create()
instances_count, time_spent = 0, 0
while instances_count < self.max_instances and time_spent < self.max_time:
self.logger.new_round()
self.logger.log('instance', instances_count + 1)
task_info = practice_service.get_next_task_in_session(user)
task_id = task_info.task.pk
task_difficulty = TasksDifficultyModel.objects.get(task_id=task_id)
student = StudentModel.objects.get(user=user)
self.logger.log('level', student.level.block_level)
self.logger.log('total-credits', student.total_credits)
self.logger.log('free-credits', student.free_credits)
student_skill = student.get_skill_dict()
for factor in FlowFactors.student_factors():
self.logger.log('student-' + factor.name, student_skill[factor])
self.logger.log('task-id', task_id)
self.logger.log('task-title', task_info.task.title)
self.logger.log('task-level', task_info.task.level)
task_difficulty = task_difficulty.get_difficulty_dict()
for factor in FlowFactors.task_factors():
self.logger.log('task-' + factor.name, task_difficulty[factor])
self.logger.log('instructions', ' '.join(task_info.instructions))
#self.logger.log('flow-prediction', TaskInstanceModel.objects
# .get(id=task_info.task_instance.['task-instance-id']).predicted_flow)
self.logger.log('flow-prediction', task_info.task_instance.predicted_flow)
solved, time = self.behavior.solve_task(task_difficulty)
self.logger.log('solved', solved)
self.logger.log('time-spent', time)
result = practice_service.process_attempt_report(user, report={
'task-instance-id': task_info.task_instance.pk,
'attempt': 1,
'solved': solved,
'time': time,
})
instance_pk = task_info.task_instance.pk
if solved:
flow = self.behavior.report_flow()
practice_service.process_flow_report(
user=user,
task_instance_id=instance_pk,
reported_flow=flow)
else:
practice_service.process_giveup_report(
user=user,
task_instance_id=instance_pk,
time_spent=time)
self.logger.log('flow-report',
TaskInstanceModel.objects.get(pk=instance_pk).reported_flow)
self.logger.log('result-earned-credits', result.credits)
self.logger.log('result-speed-bonus', result.speed_bonus)
self.logger.log('result-new-blocks', len(result.purchases))
self.logger.log('updated-task-difficulty',
TasksDifficultyModel.objects.get(task_id=task_id) \
.get_difficulty_dict()[FlowFactors.TASK_BIAS])
instances_count += 1
time_spent += time
def run_simulation(self):
"""
Run the simulation and create simulation log as a list of dictionaries,
each dictonary for one task instance taken.
"""
# TODO: decomposition
# create some task instances to avoid time bonuses for poor performances
any_student = StudentModel.objects.create(user=User.objects.create(
username='******'))
for task in TaskModel.objects.all():
TaskInstanceModel.objects.create(task=task,
student=any_student,
solved=True,
time_spent=300)
user = User.objects.create()
instances_count, time_spent = 0, 0
while instances_count < self.max_instances and time_spent < self.max_time:
self.logger.new_round()
self.logger.log('instance', instances_count + 1)
task_info = practice_service.get_next_task_in_session(user)
task_id = task_info.task.pk
task_difficulty = TasksDifficultyModel.objects.get(task_id=task_id)
student = StudentModel.objects.get(user=user)
self.logger.log('level', student.level.block_level)
self.logger.log('total-credits', student.total_credits)
self.logger.log('free-credits', student.free_credits)
student_skill = student.get_skill_dict()
for factor in FlowFactors.student_factors():
self.logger.log('student-' + factor.name,
student_skill[factor])
self.logger.log('task-id', task_id)
self.logger.log('task-title', task_info.task.title)
self.logger.log('task-level', task_info.task.level)
task_difficulty = task_difficulty.get_difficulty_dict()
for factor in FlowFactors.task_factors():
self.logger.log('task-' + factor.name, task_difficulty[factor])
self.logger.log('instructions', ' '.join(task_info.instructions))
#self.logger.log('flow-prediction', TaskInstanceModel.objects
# .get(id=task_info.task_instance.['task-instance-id']).predicted_flow)
self.logger.log('flow-prediction',
task_info.task_instance.predicted_flow)
solved, time = self.behavior.solve_task(task_difficulty)
self.logger.log('solved', solved)
self.logger.log('time-spent', time)
result = practice_service.process_attempt_report(
user,
report={
'task-instance-id': task_info.task_instance.pk,
'attempt': 1,
'solved': solved,
'time': time,
})
instance_pk = task_info.task_instance.pk
if solved:
flow = self.behavior.report_flow()
practice_service.process_flow_report(
user=user,
task_instance_id=instance_pk,
reported_flow=flow)
else:
practice_service.process_giveup_report(
user=user, task_instance_id=instance_pk, time_spent=time)
self.logger.log(
'flow-report',
TaskInstanceModel.objects.get(pk=instance_pk).reported_flow)
self.logger.log('result-earned-credits', result.credits)
self.logger.log('result-speed-bonus', result.speed_bonus)
self.logger.log('result-new-blocks', len(result.purchases))
self.logger.log('updated-task-difficulty',
TasksDifficultyModel.objects.get(task_id=task_id) \
.get_difficulty_dict()[FlowFactors.TASK_BIAS])
instances_count += 1
time_spent += time