def run(self):
query = EventEntity.all()
query.filter('source', 'unenrolled')
query.order('-recorded_on')
for survey in query.run():
yield transforms.loads(survey.data)
def run(self):
query = EventEntity.all()
query.filter('source', 'unenrolled')
query.order('-recorded_on')
for survey in query.run():
yield transforms.loads(survey.data)
def run(self):
"""Computes submitted question answers statistics."""
question_stats = self.MultipleChoiceQuestionAggregator(self._course)
mapper = models_utils.QueryMapper(
EventEntity.all(), batch_size=500, report_every=1000)
mapper.run(question_stats.visit)
return (question_stats.id_to_questions_dict,
question_stats.id_to_assessments_dict)
def run(self):
"""Computes submitted question answers statistics."""
question_stats = self.MultipleChoiceQuestionAggregator(self._course)
mapper = models_utils.QueryMapper(
EventEntity.all(), batch_size=500, report_every=1000)
mapper.run(question_stats.visit)
return (question_stats.id_to_questions_dict,
question_stats.id_to_assessments_dict)
def run(self):
# find the student's user_id..
student = Student.get_enrolled_student_by_email(self.student_email)
if not student:
raise ValueError('That student was not found!')
user_id = student.user_id
query = EventEntity.all()
query.filter('user_id', str(user_id))
query.filter('source', 'edit-wiki-page')
query.order('-recorded_on')
edits = query.run(limit=2000)
for edit in edits:
fields = transforms.loads(edit.data)
fields['recorded_on'] = edit.recorded_on
yield fields
def run(self):
# find the student's user_id..
student = Student.get_enrolled_student_by_email(self.student_email)
if not student:
raise ValueError('That student was not found!')
user_id = student.user_id
query = EventEntity.all()
query.filter('user_id', str(user_id))
query.filter('source', 'edit-wiki-page')
query.order('-recorded_on')
edits = query.run(limit=2000)
for edit in edits:
fields = transforms.loads(edit.data)
fields['recorded_on'] = edit.recorded_on
yield fields
def get_activity_scores(cls, student_user_ids, course, force_refresh=True):
"""Retrieve activity data for student using EventEntity.
For each student, launch a Query of EventEntities to retrieve student
scores. The Query is launched as a map-reduce background process that
will return up to 500 results, reporting back every second. It reports
back by calling the map_fn callback, which in turn calls parse_activity
scores.
As soon as the Query is launched (in the background) the foreground
process calls build_missing_scores() to construct a student_answer.dict
that will be updated as score data for that student is received.
Events properties include a userid (a number) and a source (e.g.,
tag-assessement), a recorded-on date (timestamp) and data (a dictionary).
Here's a typeical data dict:
{"loc": {"city": "mililani", "language": "en-US,en;q=0.8", "locale": "en_US",
"country": "US", "region": "hi", "long": -158.01528099999999, "lat": 21.451331,
"page_locale": "en_US"}, "instanceid": "yOkVTqWogdaF", "quid": "5733935958982656",
"score": 1, "location": "https://mobilecsp-201608.appspot.com/mobilecsp/unit?unit=1&lesson=45",
"answer": [0, 1, 2, 4], "type": "McQuestion", "user_agent":
"Mozilla/5.0 ..."}
Note that it includes the unit_id and lesson_id as part of the Url
"""
# Instantiate parser object
cached_date = datetime.datetime.now()
activityParser = ActivityScoreParser()
if force_refresh:
activityParser.params = activityParser.build_additional_mapper_params(
course.app_context)
# Launch a background Query for each student's activity data. This is expensive.
for user_id in student_user_ids:
# if GLOBAL_DEBUG:
logging.debug('***RAM*** launching a query for student ' +
str(user_id))
mapper = models_utils.QueryMapper(
EventEntity.all().filter('user_id in', [user_id]) \
.filter('recorded_on >= ', cls.CUTOFF_DATE), \
batch_size=1000, report_every=1000)
# Callback function -- e.g., 45-50 callbacks per query
def map_fn(activity_attempt):
# if GLOBAL_DEBUG:
# logging.debug('***RAM*** map_fn ' + str(activity_attempt))
activityParser.parse_activity_scores(activity_attempt)
mapper.run(map_fn)
# In the foreground create the student_answer_dict, which is stored at:
# activity_scores[student][unit][lesson][sequence] where sequence is
# the question's sequential position within the lesson.
# So each question in the lesson will have a question_answer_dict.
activityParser.build_missing_scores()
#Lets cache results for each student
for user_id in student_user_ids:
cached_student_data = {}
cached_student_data['date'] = cached_date
student = Student.get_by_user_id(user_id)
cached_student_data[
'scores'] = activityParser.activity_scores.get(
student.email, {})
cached_student_data[
'attempts'] = activityParser.num_attempts_dict.get(
student.email, {})
MemcacheManager.set(
cls._memcache_key_for_student(student.email),
cached_student_data)
else:
uncached_students = []
for student_id in student_user_ids:
if student_id != '':
student = Student.get_by_user_id(student_id)
temp_email = student.email
temp_mem = cls._memcache_key_for_student(temp_email)
scores_for_student = MemcacheManager.get(temp_mem)
if scores_for_student:
cached_date = scores_for_student['date']
activityParser.activity_scores[
student_id] = scores_for_student['scores']
activityParser.num_attempts_dict[
student_id] = scores_for_student['scores']
else:
uncached_students.append(student_id)
if len(uncached_students) > 0:
if cached_date == None or datetime.datetime.now(
) < cached_date:
cached_date = datetime.datetime.now()
activityParser.params = activityParser.build_additional_mapper_params(
course.app_context)
for user_id in uncached_students:
mapper = models_utils.QueryMapper(
EventEntity.all().filter('user_id in', [user_id]) \
.filter('recorded_on >= ', cls.CUTOFF_DATE), \
batch_size=1000, report_every=1000)
def map_fn(activity_attempt):
activityParser.parse_activity_scores(activity_attempt)
mapper.run(map_fn)
activityParser.build_missing_scores()
#Lets cache results for each student
for user_id in uncached_students:
cached_student_data = {}
cached_student_data['date'] = cached_date
student = Student.get_by_user_id(user_id)
cached_student_data[
'scores'] = activityParser.activity_scores.get(
student.email, {})
MemcacheManager.set(
cls._memcache_key_for_student(student.email),
cached_student_data)
score_data = {}
score_data['date'] = cached_date
score_data['scores'] = activityParser.activity_scores
score_data['attempts'] = activityParser.num_attempts_dict
if GLOBAL_DEBUG:
logging.debug('***RAM*** get_activity_scores returning scores: ' +
str(score_data['scores']))
return score_data
def get_activity_scores(cls, student_user_ids, course, force_refresh = True):
"""Retrieve activity data for student using EventEntity.
For each student, launch a Query of EventEntities to retrieve student
scores. The Query is launched as a map-reduce background process that
will return up to 500 results, reporting back every second. It reports
back by calling the map_fn callback, which in turn calls parse_activity
scores.
As soon as the Query is launched (in the background) the foreground
process calls build_missing_scores() to construct a student_answer.dict
that will be updated as score data for that student is received.
Events properties include a userid (a number) and a source (e.g.,
tag-assessement), a recorded-on date (timestamp) and data (a dictionary).
Here's a typeical data dict:
{"loc": {"city": "mililani", "language": "en-US,en;q=0.8", "locale": "en_US",
"country": "US", "region": "hi", "long": -158.01528099999999, "lat": 21.451331,
"page_locale": "en_US"}, "instanceid": "yOkVTqWogdaF", "quid": "5733935958982656",
"score": 1, "location": "https://mobilecsp-201608.appspot.com/mobilecsp/unit?unit=1&lesson=45",
"answer": [0, 1, 2, 4], "type": "McQuestion", "user_agent":
"Mozilla/5.0 ..."}
Note that it includes the unit_id and lesson_id as part of the Url
"""
# Instantiate parser object
cached_date = datetime.datetime.now()
activityParser = ActivityScoreParser()
if force_refresh:
activityParser.params = activityParser.build_additional_mapper_params(course.app_context)
# Launch a background Query for each student's activity data. This is expensive.
for user_id in student_user_ids:
# if GLOBAL_DEBUG:
# logging.debug('***RAM*** launching a query for student ' + str(user_id))
mapper = models_utils.QueryMapper(
EventEntity.all().filter('user_id in', [user_id]) \
.filter('recorded_on >= ', cls.CUTOFF_DATE), \
batch_size=1000, report_every=1000)
# Callback function -- e.g., 45-50 callbacks per query
def map_fn(activity_attempt):
# if GLOBAL_DEBUG:
# logging.debug('***RAM*** map_fn ' + str(activity_attempt))
activityParser.parse_activity_scores(activity_attempt)
mapper.run(map_fn)
# In the foreground create the student_answer_dict, which is stored at:
# activity_scores[student][unit][lesson][sequence] where sequence is
# the question's sequential position within the lesson.
# So each question in the lesson will have a question_answer_dict.
activityParser.build_missing_scores()
#Lets cache results for each student
for user_id in student_user_ids:
cached_student_data = {}
cached_student_data['date'] = cached_date
student = Student.get_by_user_id(user_id)
cached_student_data['scores'] = activityParser.activity_scores.get(student.email, {})
cached_student_data['attempts'] = activityParser.num_attempts_dict.get(student.email, {})
MemcacheManager.set(cls._memcache_key_for_student(student.email),cached_student_data)
else:
uncached_students = []
for student_id in student_user_ids:
if student_id != '':
student = Student.get_by_user_id(student_id)
temp_email = student.email
temp_mem = cls._memcache_key_for_student(temp_email)
scores_for_student = MemcacheManager.get(temp_mem)
if scores_for_student:
cached_date = scores_for_student['date']
activityParser.activity_scores[student_id] = scores_for_student['scores']
activityParser.num_attempts_dict[student_id] = scores_for_student['scores']
else:
uncached_students.append(student_id)
if len(uncached_students) > 0:
if cached_date == None or datetime.datetime.now() < cached_date:
cached_date = datetime.datetime.now()
activityParser.params = activityParser.build_additional_mapper_params(course.app_context)
for user_id in uncached_students:
mapper = models_utils.QueryMapper(
EventEntity.all().filter('user_id in', [user_id]) \
.filter('recorded_on >= ', cls.CUTOFF_DATE), \
batch_size=1000, report_every=1000)
def map_fn(activity_attempt):
activityParser.parse_activity_scores(activity_attempt)
mapper.run(map_fn)
activityParser.build_missing_scores()
#Lets cache results for each student
for user_id in uncached_students:
cached_student_data = {}
cached_student_data['date'] = cached_date
student = Student.get_by_user_id(user_id)
cached_student_data['scores'] = activityParser.activity_scores.get(student.email, {})
MemcacheManager.set(cls._memcache_key_for_student(student.email),cached_student_data)
score_data = {}
score_data['date'] = cached_date
score_data['scores'] = activityParser.activity_scores
score_data['attempts'] = activityParser.num_attempts_dict
if GLOBAL_DEBUG:
logging.debug('***RAM*** get_activity_scores returning scores: ' + str(score_data['scores']))
return score_data
def get_activity_scores(cls, student_user_ids, course, force_refresh = False):
"""Retrieve activity data for student using EventEntity"""
#instantiate parser object
cached_date = datetime.datetime.now()
activityParser = ActivityScoreParser()
if force_refresh:
activityParser.params = activityParser.build_additional_mapper_params(course.app_context)
for user_id in student_user_ids:
mapper = models_utils.QueryMapper(
EventEntity.all().filter('user_id in', [user_id]), batch_size=500, report_every=1000)
def map_fn(activity_attempt):
activityParser.parse_activity_scores(activity_attempt)
mapper.run(map_fn)
activityParser.build_missing_scores()
#Lets cache results for each student
for user_id in student_user_ids:
cached_student_data = {}
cached_student_data['date'] = cached_date
cached_student_data['scores'] = activityParser.activity_scores.get(Student.get_student_by_user_id(
user_id).email, {})
MemcacheManager.set(cls._memcache_key_for_student(Student.get_student_by_user_id(user_id).email),
cached_student_data)
else:
uncached_students = []
for student_id in student_user_ids:
scores_for_student = MemcacheManager.get(cls._memcache_key_for_student(Student.get_student_by_user_id(
student_id).email))
if scores_for_student:
cached_date = scores_for_student['date']
activityParser.activity_scores[student_id] = scores_for_student['scores']
else:
uncached_students.append(student_id)
if len(uncached_students) > 0:
if cached_date == None or datetime.datetime.now() < cached_date:
cached_date = datetime.datetime.now()
activityParser.params = activityParser.build_additional_mapper_params(course.app_context)
for user_id in uncached_students:
mapper = models_utils.QueryMapper(
EventEntity.all().filter('user_id in', [user_id]), batch_size=500, report_every=1000)
def map_fn(activity_attempt):
activityParser.parse_activity_scores(activity_attempt)
mapper.run(map_fn)
activityParser.build_missing_scores()
#Lets cache results for each student
for user_id in uncached_students:
cached_student_data = {}
cached_student_data['date'] = cached_date
cached_student_data['scores'] = activityParser.activity_scores.get(Student.get_student_by_user_id(
user_id).email, {})
MemcacheManager.set(cls._memcache_key_for_student(Student.get_student_by_user_id(user_id).email),
cached_student_data)
score_data = {}
score_data['date'] = cached_date
score_data['scores'] = activityParser.activity_scores
return score_data