def filtertwInteractionsBufr(user_id, company_id, start_date, end_date, interaction_type, series_type, query_type, page_number, items_per_page, system_type, offset, code, chart_name):
#print 'start is ' + str(time.time())
if start_date is not None:
local_start_date_naive = datetime.fromtimestamp(float(start_date))
local_start_date = _str_from_date(local_start_date_naive, "short")
#local_start_date = get_current_timezone().localize(local_start_date_naive, is_dst=None)
#print 'start2 is ' + str(time.time())
if end_date is not None:
local_end_date_naive = datetime.fromtimestamp(float(end_date))
local_end_date = _str_from_date(local_end_date_naive, "short")
#print 'start3 is ' + str(time.time())
#local_end_date = get_current_timezone().localize(local_end_date_naive, is_dst=None)
#print 'filter start us ' + str(local_start_date) + ' and edn is ' + str(local_end_date)
#code = _get_code(company_id, system_type)
try:
interactions = []
company_field_qry = 'company_id'
chart_name_qry = 'chart_name'
system_type_qry = 'system_type'
date_qry = 'date'
querydict = {company_field_qry: company_id, system_type_qry: system_type, date_qry: local_start_date, chart_name_qry: chart_name}
print 'qd is ' + str(querydict)
analyticsIds = AnalyticsIds.objects(**querydict).only('results').first()
#print 'start3 is ' + str(time.time())
if analyticsIds is None:
return []
print 'interaction tupe is ' + interaction_type
ids = analyticsIds['results'].get(interaction_type, None)
print 'ids is ' + str(ids)
publishedTweets = PublishedTweet.objects(interaction_id__in=ids).skip(offset).limit(items_per_page).order_by('published_date')
#print 'start5 is ' + str(time.time())
#now do the calculations
total = PublishedTweet.objects(interaction_id__in=ids).count() #len(leads)
#print 'start6 is ' + str(time.time())
serializer = PublishedTweetSerializer(publishedTweets, many=True)
return JsonResponse({'count' : total, 'results': serializer.data})
except Exception as e:
return JsonResponse({'Error' : str(e)})
def saveBufrTwInteractionsToMaster(user_id=None, company_id=None, job_id=None, run_type=None): #behaves differently because it directly saves the data to the AnalyticsData collection
if run_type == 'initial':
tw_interactions = TempData.objects(Q(company_id=company_id) & Q(record_type='tw_interaction') & Q(source_system='bufr') & Q(job_id=job_id) ).only('source_record')
else:
tw_interactions = TempDataDelta.objects(Q(company_id=company_id) & Q(record_type='tw_interaction') & Q(source_system='bufr') & Q(job_id=job_id) ).only('source_record')
company_query = 'company_id'
interaction_id_query = 'interaction_id'
tw_interactionsList = list(tw_interactions)
tw_interactionsList = [i['source_record'] for i in tw_interactionsList]
try:
for interaction in tw_interactionsList:
profile_id = interaction['profile_id']
published_date = datetime.fromtimestamp(float(interaction['sent_at']))
local_published_date = get_current_timezone().localize(published_date, is_dst=None)
date = local_published_date.strftime('%Y-%m-%d')
queryDict = {company_query : company_id, interaction_id_query: interaction['id']}
publishedTweet = PublishedTweet.objects(**queryDict).first()
if publishedTweet is None: #this tweet's record not found
publishedTweet = PublishedTweet()
publishedTweet.company_id = company_id
publishedTweet.interaction_id = interaction['id']
publishedTweet.published_date = date
publishedTweet.published_timestamp = interaction['sent_at']
publishedTweet.data = interaction
publishedTweet.save()
#
except Exception as e:
send_notification(dict(type='error', success=False, message=str(e)))
