def get(self):
user_data = UserData.current()
if user_data:
user_data_override = self.request_user_data("coach_email")
if user_util.is_current_user_developer() and user_data_override:
user_data = user_data_override
invalid_student = self.request_bool("invalid_student",
default=False)
coach_requests = [
x.student_requested_data.email
for x in CoachRequest.get_for_coach(user_data)
if x.student_requested_data
]
student_lists_models = StudentList.get_for_coach(user_data.key())
student_lists_list = []
for student_list in student_lists_models:
student_lists_list.append({
'key': str(student_list.key()),
'name': student_list.name,
})
student_lists_dict = dict(
(g['key'], g) for g in student_lists_list)
students_data = user_data.get_students_data()
students = map(
lambda s: {
'key':
str(s.key()),
'email':
s.email,
'nickname':
s.nickname,
'student_lists': [
l for l in [
student_lists_dict.get(str(list_id))
for list_id in s.student_lists
] if l
],
}, students_data)
students.sort(key=lambda s: s['nickname'])
template_values = {
"students": students,
"students_json": json.dumps(students),
"student_lists": student_lists_list,
"student_lists_json": json.dumps(student_lists_list),
"invalid_student": invalid_student,
"coach_requests": coach_requests,
"coach_requests_json": json.dumps(coach_requests),
'selected_nav_link': 'coach'
}
self.render_jinja2_template('viewstudentlists.html',
template_values)
else:
self.redirect(util.create_login_url(self.request.uri))
def get(self):
user_data = UserData.current()
user_data_override = self.request_user_data("coach_email")
if user_util.is_current_user_developer() and user_data_override:
user_data = user_data_override
invalid_student = self.request_bool("invalid_student", default=False)
coach_requests = [req.student_requested_identifier
for req in CoachRequest.get_for_coach(user_data)
if req.student_requested_data]
student_lists_models = StudentList.get_for_coach(user_data.key())
student_lists_list = []
for student_list in student_lists_models:
student_lists_list.append({
'key': str(student_list.key()),
'name': student_list.name,
})
student_lists_dict = dict((g['key'], g) for g in student_lists_list)
def student_to_dict(s):
"""Convert the UserData s to a dictionary for rendering."""
return {
'key': str(s.key()),
'email': s.email,
'username': s.username,
# Note that child users don't have an email.
'identifier': s.username or s.email,
'nickname': s.nickname,
'profile_root': s.profile_root,
'can_modify_coaches': s.can_modify_coaches(),
'studentLists':
[l for l in [student_lists_dict.get(str(list_id))
for list_id in s.student_lists] if l],
}
students_data = user_data.get_students_data()
students = map(student_to_dict, students_data)
students.sort(key=lambda s: s['nickname'])
child_accounts = map(student_to_dict, user_data.get_child_users())
template_values = {
'students': students,
'child_accounts': child_accounts,
'child_account_keyset': set([c['key'] for c in child_accounts]),
'students_json': json.dumps(students),
'student_lists': student_lists_list,
'student_lists_json': json.dumps(student_lists_list),
'invalid_student': invalid_student,
'coach_requests': coach_requests,
'coach_requests_json': json.dumps(coach_requests),
'selected_nav_link': 'coach',
'email': user_data.email,
}
self.render_jinja2_template('viewstudentlists.html', template_values)
def get(self):
if not user_util.is_current_user_developer():
if App.dashboard_secret and self.request_string("x", default=None) != App.dashboard_secret:
self.redirect(users.create_login_url(self.request.uri))
return
kinds = self.request_string("kinds", Dashboard.DEFAULT_KINDS).split(',')
graphs = []
for kind in kinds:
d = daily_graph_context(EntityStatistic(kind), "data")
d['kind_name'] = kind
d['title'] = "%s created per day" % kind
graphs.append(d)
self.render_jinja2_template("dashboard/dashboard.html", {'graphs': graphs})
def get(self):
if not user_util.is_current_user_developer():
if App.dashboard_secret and self.request_string("x", default=None) != App.dashboard_secret:
self.redirect(users.create_login_url(self.request.uri))
return
kinds = self.request_string("kinds", Dashboard.DEFAULT_KINDS).split(',')
graphs = []
for kind in kinds:
d = daily_graph_context(EntityStatistic(kind), "data")
d['kind_name'] = kind
d['title'] = "%s created per day" % kind
graphs.append(d)
self.render_jinja2_template("dashboard/dashboard.html", {'graphs': graphs})
def get(self):
user_data = UserData.current()
if user_data:
user_data_override = self.request_user_data("coach_email")
if user_util.is_current_user_developer() and user_data_override:
user_data = user_data_override
invalid_student = self.request_bool("invalid_student", default = False)
coach_requests = [x.student_requested_data.email for x in CoachRequest.get_for_coach(user_data) if x.student_requested_data]
student_lists_models = StudentList.get_for_coach(user_data.key())
student_lists_list = [];
for student_list in student_lists_models:
student_lists_list.append({
'key': str(student_list.key()),
'name': student_list.name,
})
student_lists_dict = dict((g['key'], g) for g in student_lists_list)
students_data = user_data.get_students_data()
students = map(lambda s: {
'key': str(s.key()),
'email': s.email,
'nickname': s.nickname,
'profile_root': s.profile_root,
'studentLists': [l for l in [student_lists_dict.get(str(list_id)) for list_id in s.student_lists] if l],
}, students_data)
students.sort(key=lambda s: s['nickname'])
template_values = {
"students": students,
"students_json": json.dumps(students),
"student_lists": student_lists_list,
"student_lists_json": json.dumps(student_lists_list),
"invalid_student": invalid_student,
"coach_requests": coach_requests,
"coach_requests_json": json.dumps(coach_requests),
'selected_nav_link': 'coach'
}
self.render_jinja2_template('viewstudentlists.html', template_values)
else:
self.redirect(util.create_login_url(self.request.uri))
def attempt_problem(user_data, user_exercise, problem_number, attempt_number,
attempt_content, sha1, seed, completed, count_hints, time_taken,
review_mode, exercise_non_summative, problem_type, ip_address):
if user_exercise and user_exercise.belongs_to(user_data):
dt_now = datetime.datetime.now()
exercise = user_exercise.exercise_model
old_graph = user_exercise.get_user_exercise_graph()
user_exercise.last_done = dt_now
user_exercise.seconds_per_fast_problem = exercise.seconds_per_fast_problem
user_exercise.summative = exercise.summative
user_data.record_activity(user_exercise.last_done)
# If a non-admin tries to answer a problem out-of-order, just ignore it
if problem_number != user_exercise.total_done + 1 and not user_util.is_current_user_developer():
# Only admins can answer problems out of order.
raise QuietException("Problem number out of order (%s vs %s) for user_id: %s submitting attempt content: %s with seed: %s" % (problem_number, user_exercise.total_done + 1, user_data.user_id, attempt_content, seed))
if len(sha1) <= 0:
raise Exception("Missing sha1 hash of problem content.")
if len(seed) <= 0:
raise Exception("Missing seed for problem content.")
if len(attempt_content) > 500:
raise Exception("Attempt content exceeded maximum length.")
# Build up problem log for deferred put
problem_log = models.ProblemLog(
key_name=models.ProblemLog.key_for(user_data, user_exercise.exercise, problem_number),
user=user_data.user,
exercise=user_exercise.exercise,
problem_number=problem_number,
time_taken=time_taken,
time_done=dt_now,
count_hints=count_hints,
hint_used=count_hints > 0,
correct=completed and not count_hints and (attempt_number == 1),
sha1=sha1,
seed=seed,
problem_type=problem_type,
count_attempts=attempt_number,
attempts=[attempt_content],
ip_address=ip_address,
review_mode=review_mode,
)
if exercise.summative:
problem_log.exercise_non_summative = exercise_non_summative
first_response = (attempt_number == 1 and count_hints == 0) or (count_hints == 1 and attempt_number == 0)
if user_exercise.total_done > 0 and user_exercise.streak == 0 and first_response:
bingo('hints_keep_going_after_wrong')
just_earned_proficiency = False
# Users can only attempt problems for themselves, so the experiment
# bucket always corresponds to the one for this current user
struggling_model = StrugglingExperiment.get_alternative_for_user(
user_data, current_user=True) or StrugglingExperiment.DEFAULT
if completed:
user_exercise.total_done += 1
if problem_log.correct:
proficient = user_data.is_proficient_at(user_exercise.exercise)
explicitly_proficient = user_data.is_explicitly_proficient_at(user_exercise.exercise)
suggested = user_data.is_suggested(user_exercise.exercise)
problem_log.suggested = suggested
problem_log.points_earned = points.ExercisePointCalculator(user_exercise, suggested, proficient)
user_data.add_points(problem_log.points_earned)
# Streak only increments if problem was solved correctly (on first attempt)
user_exercise.total_correct += 1
user_exercise.streak += 1
user_exercise.longest_streak = max(user_exercise.longest_streak, user_exercise.streak)
user_exercise.update_proficiency_model(correct=True)
bingo([
'struggling_problems_correct',
'suggested_activity_problems_correct',
])
if user_exercise.progress >= 1.0 and not explicitly_proficient:
bingo([
'hints_gained_proficiency_all',
'struggling_gained_proficiency_all',
'suggested_activity_gained_proficiency_all',
])
if not user_exercise.has_been_proficient():
bingo('hints_gained_new_proficiency')
if user_exercise.history_indicates_struggling(struggling_model):
bingo('struggling_gained_proficiency_post_struggling')
user_exercise.set_proficient(user_data)
user_data.reassess_if_necessary()
just_earned_proficiency = True
problem_log.earned_proficiency = True
util_badges.update_with_user_exercise(
user_data,
user_exercise,
include_other_badges=True,
action_cache=last_action_cache.LastActionCache.get_cache_and_push_problem_log(user_data, problem_log))
# Update phantom user notifications
util_notify.update(user_data, user_exercise)
bingo([
'hints_problems_done',
'struggling_problems_done',
'suggested_activity_problems_done',
])
else:
# Only count wrong answer at most once per problem
if first_response:
user_exercise.update_proficiency_model(correct=False)
bingo([
'hints_wrong_problems',
'struggling_problems_wrong',
'suggested_activity_problems_wrong',
])
if user_exercise.is_struggling(struggling_model):
bingo('struggling_struggled_binary')
# If this is the first attempt, update review schedule appropriately
if attempt_number == 1:
user_exercise.schedule_review(completed)
user_exercise_graph = models.UserExerciseGraph.get_and_update(user_data, user_exercise)
goals_updated = GoalList.update_goals(user_data,
lambda goal: goal.just_did_exercise(user_data, user_exercise,
just_earned_proficiency))
user_data.uservideocss_version += 1
if user_exercise.progress >= 1.0:
UserVideoCss.set_completed(user_data.key(), exercise.key(), user_data.uservideocss_version)
else:
UserVideoCss.set_started(user_data.key(), exercise.key(), user_data.uservideocss_version)
# Bulk put
db.put([user_data, user_exercise, user_exercise_graph.cache])
# Defer the put of ProblemLog for now, as we think it might be causing hot tablets
# and want to shift it off to an automatically-retrying task queue.
# http://ikaisays.com/2011/01/25/app-engine-datastore-tip-monotonically-increasing-values-are-bad/
deferred.defer(models.commit_problem_log, problem_log,
_queue="problem-log-queue")
if user_data is not None and user_data.coaches:
# Making a separate queue for the log summaries so we can clearly see how much they are getting used
deferred.defer(models.commit_log_summary_coaches, problem_log, user_data.coaches,
_queue="log-summary-queue",
)
return user_exercise, user_exercise_graph, goals_updated
def attempt_problem(user_data, user_exercise, problem_number, attempt_number,
attempt_content, sha1, seed, completed, count_hints, time_taken,
exercise_non_summative, problem_type, ip_address):
if user_exercise and user_exercise.belongs_to(user_data):
dt_now = datetime.datetime.now()
exercise = user_exercise.exercise_model
prev_last_done = user_exercise.last_done
user_exercise.last_done = dt_now
user_exercise.seconds_per_fast_problem = exercise.seconds_per_fast_problem
user_exercise.summative = exercise.summative
user_data.record_activity(user_exercise.last_done)
# If a non-admin tries to answer a problem out-of-order, just ignore it
if problem_number != user_exercise.total_done + 1 and not user_util.is_current_user_developer():
# Only admins can answer problems out of order.
raise Exception("Problem number out of order (%s vs %s) for user_id: %s submitting attempt content: %s with seed: %s" % (problem_number, user_exercise.total_done + 1, user_data.user_id, attempt_content, seed))
if len(sha1) <= 0:
raise Exception("Missing sha1 hash of problem content.")
if len(seed) <= 0:
raise Exception("Missing seed for problem content.")
if len(attempt_content) > 500:
raise Exception("Attempt content exceeded maximum length.")
# Build up problem log for deferred put
problem_log = models.ProblemLog(
key_name = "problemlog_%s_%s_%s" % (user_data.key_email, user_exercise.exercise, problem_number),
user = user_data.user,
exercise = user_exercise.exercise,
problem_number = problem_number,
time_taken = time_taken,
time_done = dt_now,
count_hints = count_hints,
hint_used = count_hints > 0,
correct = completed and not count_hints and (attempt_number == 1),
sha1 = sha1,
seed = seed,
problem_type = problem_type,
count_attempts = attempt_number,
attempts = [attempt_content],
ip_address = ip_address,
)
if exercise.summative:
problem_log.exercise_non_summative = exercise_non_summative
first_response = (attempt_number == 1 and count_hints == 0) or (count_hints == 1 and attempt_number == 0)
if user_exercise.total_done == 0 and first_response:
user_exercise.bingo_proficiency_model('prof_new_exercises_attempted')
if user_exercise.total_done > 0 and user_exercise.streak == 0 and first_response:
user_exercise.bingo_proficiency_model('prof_keep_going_after_wrong')
bingo('hints_keep_going_after_wrong')
first_problem_after_proficiency = prev_last_done and user_exercise.proficient_date and (
abs(prev_last_done - user_exercise.proficient_date) <= datetime.timedelta(seconds=1))
if first_problem_after_proficiency:
user_exercise.bingo_proficiency_model('prof_does_problem_just_after_proficiency')
if completed:
user_exercise.total_done += 1
if problem_log.correct:
proficient = user_data.is_proficient_at(user_exercise.exercise)
explicitly_proficient = user_data.is_explicitly_proficient_at(user_exercise.exercise)
suggested = user_data.is_suggested(user_exercise.exercise)
problem_log.suggested = suggested
problem_log.points_earned = points.ExercisePointCalculator(user_exercise, suggested, proficient)
user_data.add_points(problem_log.points_earned)
# Streak only increments if problem was solved correctly (on first attempt)
user_exercise.total_correct += 1
user_exercise.streak += 1
user_exercise.longest_streak = max(user_exercise.longest_streak, user_exercise.streak)
user_exercise.update_proficiency_model(correct=True)
if user_exercise.summative and user_exercise.streak % consts.CHALLENGE_STREAK_BARRIER == 0:
user_exercise.streak_start = 0.0
if user_exercise.progress >= 1.0 and not explicitly_proficient:
bingo("hints_gained_proficiency_all")
user_exercise.set_proficient(True, user_data)
user_data.reassess_if_necessary()
problem_log.earned_proficiency = True
if first_problem_after_proficiency:
user_exercise.bingo_proficiency_model('prof_problem_correct_just_after_proficiency')
util_badges.update_with_user_exercise(
user_data,
user_exercise,
include_other_badges = True,
action_cache=last_action_cache.LastActionCache.get_cache_and_push_problem_log(user_data, problem_log))
# Update phantom user notifications
util_notify.update(user_data, user_exercise)
user_exercise.bingo_proficiency_model('prof_problems_done')
bingo('hints_problems_done')
else:
if user_exercise.streak == 0:
# 2+ in a row wrong -> not proficient
user_exercise.set_proficient(False, user_data)
# Only count wrong answer at most once per problem
if first_response:
user_exercise.update_proficiency_model(correct=False)
user_exercise.bingo_proficiency_model('prof_wrong_problems')
bingo('hints_wrong_problems')
# If this is the first attempt, update review schedule appropriately
if attempt_number == 1:
user_exercise.schedule_review(completed)
user_exercise_graph = models.UserExerciseGraph.get_and_update(user_data, user_exercise)
# Bulk put
db.put([user_data, user_exercise, user_exercise_graph.cache])
# Defer the put of ProblemLog for now, as we think it might be causing hot tablets
# and want to shift it off to an automatically-retrying task queue.
# http://ikaisays.com/2011/01/25/app-engine-datastore-tip-monotonically-increasing-values-are-bad/
deferred.defer(models.commit_problem_log, problem_log,
_queue="problem-log-queue",
_url="/_ah/queue/deferred_problemlog")
if user_data is not None and user_data.coaches:
# Making a separate queue for the log summaries so we can clearly see how much they are getting used
deferred.defer(models.commit_log_summary_coaches, problem_log, user_data.coaches,
_queue = "log-summary-queue",
_url = "/_ah/queue/deferred_log_summary")
return user_exercise, user_exercise_graph
def get(self):
user_data = UserData.current()
user_data_override = self.request_user_data("coach_email")
if user_util.is_current_user_developer() and user_data_override:
user_data = user_data_override
invalid_student = self.request_bool("invalid_student", default=False)
coach_requests = [
req.student_requested_identifier
for req in CoachRequest.get_for_coach(user_data)
if req.student_requested_data
]
student_lists_models = StudentList.get_for_coach(user_data.key())
student_lists_list = []
for student_list in student_lists_models:
student_lists_list.append({
'key': str(student_list.key()),
'name': student_list.name,
})
student_lists_dict = dict((g['key'], g) for g in student_lists_list)
def student_to_dict(s):
"""Convert the UserData s to a dictionary for rendering."""
return {
'key':
str(s.key()),
'email':
s.email,
'username':
s.username,
# Note that child users don't have an email.
'identifier':
s.username or s.email,
'nickname':
s.nickname,
'profile_root':
s.profile_root,
'can_modify_coaches':
s.can_modify_coaches(),
'studentLists': [
l for l in [
student_lists_dict.get(str(list_id))
for list_id in s.student_lists
] if l
],
}
students_data = user_data.get_students_data()
students = map(student_to_dict, students_data)
students.sort(key=lambda s: s['nickname'])
child_accounts = map(student_to_dict, user_data.get_child_users())
template_values = {
'students': students,
'child_accounts': child_accounts,
'child_account_keyset': set([c['key'] for c in child_accounts]),
'students_json': json.dumps(students),
'student_lists': student_lists_list,
'student_lists_json': json.dumps(student_lists_list),
'invalid_student': invalid_student,
'coach_requests': coach_requests,
'coach_requests_json': json.dumps(coach_requests),
'selected_nav_link': 'coach',
'email': user_data.email,
}
self.render_jinja2_template('viewstudentlists.html', template_values)
def attempt_problem(user_data, user_exercise, problem_number, attempt_number,
attempt_content, sha1, seed, completed, count_hints,
time_taken, exercise_non_summative, problem_type,
ip_address):
if user_exercise and user_exercise.belongs_to(user_data):
dt_now = datetime.datetime.now()
exercise = user_exercise.exercise_model
prev_last_done = user_exercise.last_done
user_exercise.last_done = dt_now
user_exercise.seconds_per_fast_problem = exercise.seconds_per_fast_problem
user_exercise.summative = exercise.summative
user_data.record_activity(user_exercise.last_done)
# If a non-admin tries to answer a problem out-of-order, just ignore it
if problem_number != user_exercise.total_done + 1 and not user_util.is_current_user_developer(
):
# Only admins can answer problems out of order.
raise Exception(
"Problem number out of order (%s vs %s) for user_id: %s submitting attempt content: %s with seed: %s"
% (problem_number, user_exercise.total_done + 1,
user_data.user_id, attempt_content, seed))
if len(sha1) <= 0:
raise Exception("Missing sha1 hash of problem content.")
if len(seed) <= 0:
raise Exception("Missing seed for problem content.")
if len(attempt_content) > 500:
raise Exception("Attempt content exceeded maximum length.")
# Build up problem log for deferred put
problem_log = models.ProblemLog(
key_name="problemlog_%s_%s_%s" %
(user_data.key_email, user_exercise.exercise, problem_number),
user=user_data.user,
exercise=user_exercise.exercise,
problem_number=problem_number,
time_taken=time_taken,
time_done=dt_now,
count_hints=count_hints,
hint_used=count_hints > 0,
correct=completed and not count_hints and (attempt_number == 1),
sha1=sha1,
seed=seed,
problem_type=problem_type,
count_attempts=attempt_number,
attempts=[attempt_content],
ip_address=ip_address,
)
if exercise.summative:
problem_log.exercise_non_summative = exercise_non_summative
first_response = (attempt_number == 1
and count_hints == 0) or (count_hints == 1
and attempt_number == 0)
if user_exercise.total_done == 0 and first_response:
user_exercise.bingo_proficiency_model(
'prof_new_exercises_attempted')
if user_exercise.total_done > 0 and user_exercise.streak == 0 and first_response:
user_exercise.bingo_proficiency_model(
'prof_keep_going_after_wrong')
bingo('hints_keep_going_after_wrong')
first_problem_after_proficiency = prev_last_done and user_exercise.proficient_date and (
abs(prev_last_done - user_exercise.proficient_date) <=
datetime.timedelta(seconds=1))
if first_problem_after_proficiency:
user_exercise.bingo_proficiency_model(
'prof_does_problem_just_after_proficiency')
if completed:
user_exercise.total_done += 1
if problem_log.correct:
proficient = user_data.is_proficient_at(user_exercise.exercise)
explicitly_proficient = user_data.is_explicitly_proficient_at(
user_exercise.exercise)
suggested = user_data.is_suggested(user_exercise.exercise)
problem_log.suggested = suggested
problem_log.points_earned = points.ExercisePointCalculator(
user_exercise, suggested, proficient)
user_data.add_points(problem_log.points_earned)
# Streak only increments if problem was solved correctly (on first attempt)
user_exercise.total_correct += 1
user_exercise.streak += 1
user_exercise.longest_streak = max(
user_exercise.longest_streak, user_exercise.streak)
user_exercise.update_proficiency_model(correct=True)
if user_exercise.summative and user_exercise.streak % consts.CHALLENGE_STREAK_BARRIER == 0:
user_exercise.streak_start = 0.0
if user_exercise.progress >= 1.0 and not explicitly_proficient:
bingo("hints_gained_proficiency_all")
user_exercise.set_proficient(True, user_data)
user_data.reassess_if_necessary()
problem_log.earned_proficiency = True
if first_problem_after_proficiency:
user_exercise.bingo_proficiency_model(
'prof_problem_correct_just_after_proficiency')
util_badges.update_with_user_exercise(
user_data,
user_exercise,
include_other_badges=True,
action_cache=last_action_cache.LastActionCache.
get_cache_and_push_problem_log(user_data, problem_log))
# Update phantom user notifications
util_notify.update(user_data, user_exercise)
user_exercise.bingo_proficiency_model('prof_problems_done')
bingo('hints_problems_done')
else:
if user_exercise.streak == 0:
# 2+ in a row wrong -> not proficient
user_exercise.set_proficient(False, user_data)
# Only count wrong answer at most once per problem
if first_response:
user_exercise.update_proficiency_model(correct=False)
user_exercise.bingo_proficiency_model('prof_wrong_problems')
bingo('hints_wrong_problems')
# If this is the first attempt, update review schedule appropriately
if attempt_number == 1:
user_exercise.schedule_review(completed)
user_exercise_graph = models.UserExerciseGraph.get_and_update(
user_data, user_exercise)
# Bulk put
db.put([user_data, user_exercise, user_exercise_graph.cache])
# Defer the put of ProblemLog for now, as we think it might be causing hot tablets
# and want to shift it off to an automatically-retrying task queue.
# http://ikaisays.com/2011/01/25/app-engine-datastore-tip-monotonically-increasing-values-are-bad/
deferred.defer(models.commit_problem_log,
problem_log,
_queue="problem-log-queue",
_url="/_ah/queue/deferred_problemlog")
if user_data is not None and user_data.coaches:
# Making a separate queue for the log summaries so we can clearly see how much they are getting used
deferred.defer(models.commit_log_summary_coaches,
problem_log,
user_data.coaches,
_queue="log-summary-queue",
_url="/_ah/queue/deferred_log_summary")
return user_exercise, user_exercise_graph
def has_privilege(user_data, points_required):
return user_util.is_current_user_developer() or \
user_data.moderator or \
user_data.points >= points_required
def is_allowed(self):
return len(self.purge()) < self.hourly_limit or \
user_util.is_current_user_developer() or \
self.user_data.moderator
def has_privilege(user_data, points_required):
return user_util.is_current_user_developer() or \
user_data.moderator or \
user_data.points >= points_required
def attempt_problem(user_data,
user_exercise,
problem_number,
attempt_number,
attempt_content,
sha1,
seed,
completed,
count_hints,
time_taken,
review_mode,
topic_mode,
problem_type,
ip_address,
async_problem_log_put=True):
if user_exercise and user_exercise.belongs_to(user_data):
dt_now = datetime.datetime.now()
exercise = user_exercise.exercise_model
old_graph = user_exercise.get_user_exercise_graph()
user_exercise.last_done = dt_now
user_exercise.seconds_per_fast_problem = exercise.seconds_per_fast_problem
user_data.record_activity(user_exercise.last_done)
# If a non-admin tries to answer a problem out-of-order, just ignore it
if problem_number != user_exercise.total_done + 1 and not user_util.is_current_user_developer(
):
# Only admins can answer problems out of order.
raise custom_exceptions.QuietException(
"Problem number out of order (%s vs %s) for user_id: %s submitting attempt content: %s with seed: %s"
% (problem_number, user_exercise.total_done + 1,
user_data.user_id, attempt_content, seed))
if len(sha1) <= 0:
raise Exception("Missing sha1 hash of problem content.")
if len(seed) <= 0:
raise Exception("Missing seed for problem content.")
if len(attempt_content) > 500:
raise Exception("Attempt content exceeded maximum length.")
# Build up problem log for deferred put
problem_log = exercise_models.ProblemLog(
key_name=exercise_models.ProblemLog.key_for(
user_data, user_exercise.exercise, problem_number),
user=user_data.user,
exercise=user_exercise.exercise,
problem_number=problem_number,
time_taken=time_taken,
time_done=dt_now,
count_hints=count_hints,
hint_used=count_hints > 0,
correct=completed and not count_hints and (attempt_number == 1),
sha1=sha1,
seed=seed,
problem_type=problem_type,
count_attempts=attempt_number,
attempts=[attempt_content],
ip_address=ip_address,
review_mode=review_mode,
topic_mode=topic_mode,
)
first_response = (attempt_number == 1
and count_hints == 0) or (count_hints == 1
and attempt_number == 0)
if user_exercise.total_done > 0 and user_exercise.streak == 0 and first_response:
bingo('hints_keep_going_after_wrong')
just_earned_proficiency = False
# Users can only attempt problems for themselves, so the experiment
# bucket always corresponds to the one for this current user
struggling_model = StrugglingExperiment.get_alternative_for_user(
user_data, current_user=True) or StrugglingExperiment.DEFAULT
if completed:
user_exercise.total_done += 1
if problem_log.correct:
proficient = user_data.is_proficient_at(user_exercise.exercise)
explicitly_proficient = user_data.is_explicitly_proficient_at(
user_exercise.exercise)
suggested = user_data.is_suggested(user_exercise.exercise)
problem_log.suggested = suggested
problem_log.points_earned = points.ExercisePointCalculator(
user_exercise, topic_mode, suggested, proficient)
user_data.add_points(problem_log.points_earned)
# Streak only increments if problem was solved correctly (on first attempt)
user_exercise.total_correct += 1
user_exercise.streak += 1
user_exercise.longest_streak = max(
user_exercise.longest_streak, user_exercise.streak)
user_exercise.update_proficiency_model(correct=True)
bingo([
'struggling_problems_correct',
])
if user_exercise.progress >= 1.0 and not explicitly_proficient:
bingo([
'hints_gained_proficiency_all',
'struggling_gained_proficiency_all',
])
if not user_exercise.has_been_proficient():
bingo('hints_gained_new_proficiency')
if user_exercise.history_indicates_struggling(
struggling_model):
bingo('struggling_gained_proficiency_post_struggling')
user_exercise.set_proficient(user_data)
user_data.reassess_if_necessary()
just_earned_proficiency = True
problem_log.earned_proficiency = True
badges.util_badges.update_with_user_exercise(
user_data,
user_exercise,
include_other_badges=True,
action_cache=badges.last_action_cache.LastActionCache.
get_cache_and_push_problem_log(user_data, problem_log))
# Update phantom user notifications
phantom_users.util_notify.update(user_data, user_exercise)
bingo([
'hints_problems_done',
'struggling_problems_done',
])
else:
# Only count wrong answer at most once per problem
if first_response:
user_exercise.update_proficiency_model(correct=False)
bingo([
'hints_wrong_problems',
'struggling_problems_wrong',
])
if user_exercise.is_struggling(struggling_model):
bingo('struggling_struggled_binary')
# If this is the first attempt, update review schedule appropriately
if attempt_number == 1:
user_exercise.schedule_review(completed)
user_exercise_graph = exercise_models.UserExerciseGraph.get_and_update(
user_data, user_exercise)
goals_updated = GoalList.update_goals(
user_data, lambda goal: goal.just_did_exercise(
user_data, user_exercise, just_earned_proficiency))
# Bulk put
db.put([user_data, user_exercise, user_exercise_graph.cache])
if async_problem_log_put:
# Defer the put of ProblemLog for now, as we think it might be causing hot tablets
# and want to shift it off to an automatically-retrying task queue.
# http://ikaisays.com/2011/01/25/app-engine-datastore-tip-monotonically-increasing-values-are-bad/
deferred.defer(exercise_models.commit_problem_log,
problem_log,
_queue="problem-log-queue",
_url="/_ah/queue/deferred_problemlog")
else:
exercise_models.commit_problem_log(problem_log)
if user_data is not None and user_data.coaches:
# Making a separate queue for the log summaries so we can clearly see how much they are getting used
deferred.defer(video_models.commit_log_summary_coaches,
problem_log,
user_data.coaches,
_queue="log-summary-queue",
_url="/_ah/queue/deferred_log_summary")
return user_exercise, user_exercise_graph, goals_updated
def is_allowed(self):
return len(self.purge()) < self.hourly_limit or \
user_util.is_current_user_developer() or \
self.user_data.moderator
