def after_request():
msTimeNow = time.time()
duration = msTimeNow - request.params.start_ts
print ("END %s %s %s %s %s " % (datetime.now(), request.method, request.path, request.params.user_uuid, duration))
logging.debug("END %s %s %s %s " % (request.method, request.path, request.params.user_uuid, duration))
# Keep track of the time and duration for each call
stats.storeServerEntry(request.params.user_uuid, "%s %s" % (request.method, request.path), msTimeNow, duration)
def after_request():
msTimeNow = time.time()
duration = msTimeNow - request.params.start_ts
print("END %s %s %s %s %s " % (datetime.now(), request.method, request.path, request.params.user_uuid, duration))
logging.debug("END %s %s %s %s " % (request.method, request.path, request.params.user_uuid, duration))
# Keep track of the time and duration for each call
stats.storeServerEntry(request.params.user_uuid, "%s %s" % (request.method, request.path),
msTimeNow, duration)
def queryUnclassifiedSections(uuid):
now = datetime.now()
weekago = now - timedelta(weeks=1)
user_uuid = uuid
clientSpecificQuery = getClientSpecificQueryFilter(user_uuid)
Sections = get_section_db()
logging.debug("section.count = %s" % Sections.count())
# Theoretically, we shouldn't need the 'predicted_mode' code because we
# predict values right after reading the trips from moves. However, there
# is still a small race window in which we are reading trips for other
# users and haven't yet run the classifier. As we get more users, this
# window can only grow, and it is easy to handle it, so let's just do so now.
defaultQueryList = [
{"source": "Shankari"},
{"user_id": user_uuid},
{"predicted_mode": {"$exists": True}},
{"confirmed_mode": ""},
{"retained": True},
{"type": "move"},
{"section_end_datetime": {"$gt": weekago}},
]
completeQueryList = defaultQueryList + clientSpecificQuery
unclassifiedSections = Sections.find({"$and": completeQueryList})
# totalUnclassifiedSections are for debugging only, can remove after we know that this works well
totalUnclassifiedSections = Sections.find(
{"$and": [{"source": "Shankari"}, {"user_id": user_uuid}, {"confirmed_mode": ""}, {"type": "move"}]}
)
unclassifiedSectionCount = unclassifiedSections.count()
totalUnclassifiedSectionCount = totalUnclassifiedSections.count()
logging.debug("Unsec.count = %s" % unclassifiedSectionCount)
logging.debug("Total Unsec.count = %s" % totalUnclassifiedSectionCount)
# Keep track of what percent of sections are stripped out.
# Sections can be stripped out for various reasons:
# - they are too old
# - they have enough confidence that above the magic threshold (90%) AND
# the client has requested stripping out
# - they have already been identified as being too short by the filter label
stats.storeServerEntry(
user_uuid,
stats.STAT_TRIP_MGR_PCT_SHOWN,
time.time(),
0 if totalUnclassifiedSectionCount == 0 else float(unclassifiedSectionCount) / totalUnclassifiedSectionCount,
)
return unclassifiedSections
def queryUnclassifiedSections(uuid):
now = datetime.now()
weekago = now - timedelta(weeks=1)
user_uuid = uuid
clientSpecificQuery = getClientSpecificQueryFilter(user_uuid)
Sections = get_section_db()
logging.debug('section.count = %s' % Sections.count())
# Theoretically, we shouldn't need the 'predicted_mode' code because we
# predict values right after reading the trips from moves. However, there
# is still a small race window in which we are reading trips for other
# users and haven't yet run the classifier. As we get more users, this
# window can only grow, and it is easy to handle it, so let's just do so now.
defaultQueryList = [{
'source': 'Shankari'
}, {
'user_id': user_uuid
}, {
'predicted_mode': {
'$exists': True
}
}, {
'confirmed_mode': ''
}, {
'retained': True
}, {
'type': 'move'
}, {
'section_end_datetime': {
"$gt": weekago
}
}]
completeQueryList = defaultQueryList + clientSpecificQuery
unclassifiedSections = Sections.find({"$and": completeQueryList})
# totalUnclassifiedSections are for debugging only, can remove after we know that this works well
totalUnclassifiedSections = Sections.find({
"$and": [{
'source': 'Shankari'
}, {
'user_id': user_uuid
}, {
'confirmed_mode': ''
}, {
'type': 'move'
}]
})
unclassifiedSectionCount = unclassifiedSections.count()
totalUnclassifiedSectionCount = totalUnclassifiedSections.count()
logging.debug('Unsec.count = %s' % unclassifiedSectionCount)
logging.debug('Total Unsec.count = %s' % totalUnclassifiedSectionCount)
# Keep track of what percent of sections are stripped out.
# Sections can be stripped out for various reasons:
# - they are too old
# - they have enough confidence that above the magic threshold (90%) AND
# the client has requested stripping out
# - they have already been identified as being too short by the filter label
stats.storeServerEntry(
user_uuid, stats.STAT_TRIP_MGR_PCT_SHOWN, time.time(),
0 if totalUnclassifiedSectionCount == 0 else
float(unclassifiedSectionCount) / totalUnclassifiedSectionCount)
return unclassifiedSections