def testStatsList(self):
us = UserStats('userid', 'itemid')
us.save(1,2)
us.save(1,3)
us.save(1,4)
us.save(2,2)
us.save(2,3)
us.save(3,4)
us.save(4,4)
toplist = us.get_Top_N('userid', 3)
print toplist
self.assertEqual(len(toplist), 3, "toplist has not enough entries")
toplist = us.get_Top_N('userid', 4)
self.assertEqual(len(toplist), 4, "toplist has not enough entries")
self.assertEqual(int(toplist[0][0]), 1, "")
self.assertEqual(int(toplist[0][1]), 3, "")
timestamp = message['timestamp']
domainid = message['domainid']
additional_filter = {'domainid': domainid}
if config_global.SAVE_RANDOM_RECOMMENDER in backends:
fb = Random_Recommender()
fb.set_recommendables(itemid, additional_filter)
if config_global.SAVE_HADOOP_SINK in backends:
hS = HadoopSink(append=True)
rating = 1
hS.save_mode2(userid, itemid, domainid, timestamp)
if config_global.SAVE_USER_STATS in backends:
us = UserStats('userid', 'itemid')
us.save(userid, itemid)
#save sync
else:
body_message = {'message': message,
'api': api,
'backends': backends}
body_message = pickle.dumps(body_message)
self.enqueue(body_message)
#from contest.packages.queues.RawJsonDumpWorker import rawJsonDumpWorker
#raw = rawJsonDumpWorker(mode='redis')
#raw.enqueue(message)
if (SAVE_DIMENSION_LIST):
dimension = 'user_ids'
dL = DimensionListModel( dimension )
if(debug):
print "userid:\t" + str(flattenedJson['client_id'])
dL.save( dimension_id = flattenedJson['client_id'], timestamp = timestamp_sec )
"""
n += 1
if ( n % cycle_count == 0 and debug2):
print n
if (not debug3):
result = r.fetch_row(maxrows = n_maxrows) # fetch N row maximum
else: result = False
if (not debug3): db.close() #close the database connection
replay_time = time2.time() - replay_time
print "time it took: " + str(replay_time)
print 'It took {0:1f} seconds per item'.format(replay_time/n)
us = UserStats('userid', 'itemid')
the_list = us.get_Top_N('userid', 100)
print the_list
pH = Plot_Helper()
pH.make_plot(the_list)