def test_size_of_logs_in_cache(self): """ [recommendation.cache.SimpleLogger] Test size of cache is 10 for all users in system """ for user in USERS: user = User.get_user_by_external_id(user["external_id"]) assert len(LogEntry.get_logs_for(user.pk)) == 10, \ "logs size are bigger than predicted (%s != 10)" % len(LogEntry.get_logs_for(user.pk))
def test_size_of_logs_in_cache(self): """ [recommendation.cache.SimpleLogger] Test size of cache is 10 for all users in system """ for user in USERS: user = User.get_user_by_external_id(user["external_id"]) assert len(LogEntry.get_logs_for(user.pk)) == 10, \ "logs size are bigger than predicted (%s != 10)" % len(LogEntry.get_logs_for(user.pk))
def __call__(self, user, recommendation, size=4, **kwargs): """ Calculate the new rank based on logs """ logs = LogEntry.get_logs_for(user.pk) #m = recommendation.mean() #print m #rec = {v: k for k, v in enumerate(recommendation, start=1)} for log in logs: try: recommendation[log.item_id-1] += (self.evaluate(log, size) * 0.01) except IndexError: pass return recommendation
def __call__(self, user, recommendation, size=4, **kwargs): """ Calculate the new rank based on logs """ logs = LogEntry.get_logs_for(user.pk) #m = recommendation.mean() #print m #rec = {v: k for k, v in enumerate(recommendation, start=1)} for log in logs: try: recommendation[log.item_id - 1] += (self.evaluate(log, size) * 0.01) except IndexError: pass return recommendation