def fill_class_summaries_from_logs(user_data_coach, students_data, dt_start_utc):
dt_end_utc = dt_start_utc + datetime.timedelta(days = 1)
# Asynchronously grab all student data at once
async_queries = []
for user_data_student in students_data:
query_problem_logs = ProblemLog.get_for_user_data_between_dts(user_data_student, dt_start_utc, dt_end_utc)
query_video_logs = VideoLog.get_for_user_data_between_dts(user_data_student, dt_start_utc, dt_end_utc)
async_queries.append(query_problem_logs)
async_queries.append(query_video_logs)
# Wait for all queries to finish
results = util.async_queries(async_queries, limit=10000)
for i, user_data_student in enumerate(students_data):
logging.info("working on student "+str(user_data_student.user))
problem_and_video_logs = []
problem_logs = results[i * 2].get_result()
video_logs = results[i * 2 + 1].get_result()
for problem_log in problem_logs:
problem_and_video_logs.append(problem_log)
for video_log in video_logs:
problem_and_video_logs.append(video_log)
problem_and_video_logs = sorted(problem_and_video_logs, key=lambda log: log.time_started())
if problem_and_video_logs:
LogSummary.add_or_update_entry(user_data_coach, problem_and_video_logs, ClassDailyActivitySummary, LogSummaryTypes.CLASS_DAILY_ACTIVITY, 1440)
def fill_class_summaries_from_logs(user_data_coach, students_data,
dt_start_utc):
dt_end_utc = dt_start_utc + datetime.timedelta(days=1)
# Asynchronously grab all student data at once
async_queries = []
for user_data_student in students_data:
query_problem_logs = ProblemLog.get_for_user_data_between_dts(
user_data_student, dt_start_utc, dt_end_utc)
query_video_logs = VideoLog.get_for_user_data_between_dts(
user_data_student, dt_start_utc, dt_end_utc)
async_queries.append(query_problem_logs)
async_queries.append(query_video_logs)
# Wait for all queries to finish
results = util.async_queries(async_queries, limit=10000)
for i, user_data_student in enumerate(students_data):
logging.info("working on student " + str(user_data_student.user))
problem_and_video_logs = []
problem_logs = results[i * 2].get_result()
video_logs = results[i * 2 + 1].get_result()
for problem_log in problem_logs:
problem_and_video_logs.append(problem_log)
for video_log in video_logs:
problem_and_video_logs.append(video_log)
problem_and_video_logs = sorted(problem_and_video_logs,
key=lambda log: log.time_started())
if problem_and_video_logs:
LogSummary.add_or_update_entry(
user_data_coach, problem_and_video_logs,
ClassDailyActivitySummary,
LogSummaryTypes.CLASS_DAILY_ACTIVITY, 1440)
def get_classtime_table_by_coach(self, user_data_coach, students_data,
dt_start_utc):
logging.info("getting classtime table for " + str(dt_start_utc))
#ctz will be from midnight to midnight on the day they are looking at
dt_start_ctz = self.dt_to_ctz(dt_start_utc)
dt_end_ctz = dt_start_ctz + datetime.timedelta(days=1)
classtime_table = ClassTimeTable(dt_start_ctz, dt_end_ctz)
# midnight at PST is 7AM UTC and hence the coach's day in UTC goes from 7AM to 7AM the next day, spanning two different UTC days
dt_end_utc = dt_start_utc + datetime.timedelta(days=1)
# find the first utc days that spans the teacher's day
dt_start_utc1 = datetime.datetime(dt_start_utc.year,
dt_start_utc.month, dt_start_utc.day)
dt_end_utc1 = dt_start_utc1 + datetime.timedelta(days=1)
# get the query to get the summary shards from the first day
log_summary_query_1 = LogSummary.get_by_name(
LogSummary.get_name_by_dates(user_data_coach,
LogSummaryTypes.CLASS_DAILY_ACTIVITY,
dt_start_utc1, dt_end_utc1))
# find the second utc day that spans the teacher's day
dt_start_utc2 = dt_end_utc1
dt_end_utc2 = dt_start_utc2 + datetime.timedelta(days=1)
log_summary_query_2 = LogSummary.get_by_name(
LogSummary.get_name_by_dates(user_data_coach,
LogSummaryTypes.CLASS_DAILY_ACTIVITY,
dt_start_utc2, dt_end_utc2))
results = util.async_queries(
[log_summary_query_1, log_summary_query_2], limit=10000)
class_summary_shards = results[0].get_result()
class_summary = None
if class_summary_shards:
class_summary = reduce(
lambda x, y: x.merge_shard(y),
map(lambda x: x.summary, class_summary_shards))
class_summary_day2_shards = results[1].get_result()
class_summary_day2 = None
if class_summary_day2_shards:
class_summary_day2 = reduce(
lambda x, y: x.merge_shard(y),
map(lambda x: x.summary, class_summary_day2_shards))
if class_summary_day2 is not None:
if class_summary is not None:
class_summary.merge_day(class_summary_day2)
else:
class_summary = class_summary_day2
if not class_summary:
return classtime_table
rows = 0
# only consider sudents that are in the coach's currently looked at list (some students might have stopped having their current coach, or we might only be interested in a coach's student_list
for i, user_data_student in enumerate(students_data):
# check to see if the current student has had any activity
if class_summary.student_dict.has_key(user_data_student.user):
# loop over all chunks of that day
for adjacent_activity_summary in class_summary.student_dict[
user_data_student.user]:
# make sure the chunk falls within the day specified by the coach's timezone
if adjacent_activity_summary.start > dt_start_utc and adjacent_activity_summary.start < dt_end_utc:
rows += 1
adjacent_activity_summary.setTimezoneOffset(
self.timezone_offset)
classtime_table.drop_into_column(
adjacent_activity_summary, i)
logging.info("summary by coach rows=" + str(rows))
return classtime_table
def get_classtime_table_by_coach(self, user_data_coach, students_data, dt_start_utc):
logging.info("getting classtime table for "+str(dt_start_utc))
#ctz will be from midnight to midnight on the day they are looking at
dt_start_ctz = self.dt_to_ctz(dt_start_utc)
dt_end_ctz = dt_start_ctz + datetime.timedelta(days = 1)
classtime_table = ClassTimeTable(dt_start_ctz, dt_end_ctz)
# midnight at PST is 7AM UTC and hence the coach's day in UTC goes from 7AM to 7AM the next day, spanning two different UTC days
dt_end_utc = dt_start_utc + datetime.timedelta(days = 1)
# find the first utc days that spans the teacher's day
dt_start_utc1 = datetime.datetime(dt_start_utc.year, dt_start_utc.month, dt_start_utc.day)
dt_end_utc1 = dt_start_utc1 + datetime.timedelta(days = 1)
# get the query to get the summary shards from the first day
log_summary_query_1 = LogSummary.get_by_name(LogSummary.get_name_by_dates(user_data_coach, LogSummaryTypes.CLASS_DAILY_ACTIVITY, dt_start_utc1, dt_end_utc1))
# find the second utc day that spans the teacher's day
dt_start_utc2 = dt_end_utc1
dt_end_utc2 = dt_start_utc2 + datetime.timedelta(days = 1)
log_summary_query_2 = LogSummary.get_by_name(LogSummary.get_name_by_dates(user_data_coach, LogSummaryTypes.CLASS_DAILY_ACTIVITY, dt_start_utc2, dt_end_utc2))
results = util.async_queries([log_summary_query_1, log_summary_query_2], limit = 10000)
class_summary_shards = results[0].get_result()
class_summary = None
if class_summary_shards:
class_summary = reduce(lambda x, y: x.merge_shard(y), map(lambda x: x.summary, class_summary_shards))
class_summary_day2_shards = results[1].get_result()
class_summary_day2 = None
if class_summary_day2_shards:
class_summary_day2 = reduce(lambda x, y: x.merge_shard(y), map(lambda x: x.summary, class_summary_day2_shards))
if class_summary_day2 is not None:
if class_summary is not None :
class_summary.merge_day(class_summary_day2)
else:
class_summary = class_summary_day2
if not class_summary:
return classtime_table
rows = 0
# only consider sudents that are in the coach's currently looked at list (some students might have stopped having their current coach, or we might only be interested in a coach's student_list
for i, user_data_student in enumerate(students_data):
# check to see if the current student has had any activity
if class_summary.student_dict.has_key(user_data_student.user):
# loop over all chunks of that day
for adjacent_activity_summary in class_summary.student_dict[user_data_student.user]:
# make sure the chunk falls within the day specified by the coach's timezone
if adjacent_activity_summary.start > dt_start_utc and adjacent_activity_summary.start < dt_end_utc:
rows += 1
adjacent_activity_summary.setTimezoneOffset(self.timezone_offset)
classtime_table.drop_into_column(adjacent_activity_summary, i)
logging.info("summary by coach rows="+str(rows))
return classtime_table
