def test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict,
online_pattern_dict, character_start_ts):
status = False
print 'start cron_text_attribute'
uid_list = user_keywords_dict.keys()
#get user flow information: hashtag, activity_geo, keywords
print 'get flow result'
flow_result = get_flow_information(uid_list)
print 'flow result len:', len(flow_result)
#get user profile information
print 'get register result'
register_result = get_profile_information(uid_list)
print 'register result len:', len(register_result)
#get user topic and domain by bulk action
print 'get topic and domain, politics'
topic_results_dict, topic_results_label = topic_classfiy(
uid_list, user_keywords_dict)
domain_results = domain_classfiy(uid_list, user_keywords_dict)
politics_results = political_classify(uid_list, user_keywords_dict)
print "topic: ", topic_results_dict, topic_results_label
print "domain: ", domain_results
print "politics:", politics_results
#get user character attribute
#print 'get character result'
#type_mark = 0/1 for identify the task input status---just sentiment or text
#character_start_time = ts2datetime(character_start_ts)
#character_end_time = ts2datetime(character_start_ts + DAY * CHARACTER_TIME_GAP - DAY)
#print 'character_start_time:', character_start_time
#print 'character_end_time:', character_end_time
#character_sentiment_result_dict = classify_sentiment(uid_list, user_weibo_dict, character_start_time, character_end_time, WEIBO_API_INPUT_TYPE)
#character_text_result_dict = classify_topic(uid_list, user_keywords_dict)
#print 'character result len:', len(character_sentiment_result_dict), len(character_text_result_dict)
#get user fansnum max
fansnum_max = get_fansnum_max()
#get user activeness by bulk_action
print 'get activeness results'
activeness_results = get_activity_time(uid_list)
print 'activeness result len:', len(activeness_results)
#get user inlfuence by bulk action
print 'get influence'
influence_results = get_influence(uid_list)
print 'influence results len:', len(influence_results)
# compute text attribute
bulk_action = []
count = 0
for user in uid_list:
count += 1
results = {}
#get user text attribute: online_pattern
results['online_pattern'] = json.dumps(online_pattern_dict[user])
try:
results['online_pattern_aggs'] = '&'.join(
online_pattern_dict[user].keys())
except:
results['online_pattern_aggs'] = ''
results['uid'] = str(user)
#add user flow information: hashtag, activity_geo, keywords
flow_dict = flow_result[str(user)]
results = dict(results, **flow_dict)
#add user topic attribute
user_topic_dict = topic_results_dict[user]
user_label_dict = topic_results_label[user]
results['topic'] = json.dumps(
user_topic_dict) # {'topic1_en':pro1, 'topic2_en':pro2...}
results['topic_string'] = topic_en2ch(
user_label_dict) # 'topic1_ch&topic2_ch&topic3_ch'
#add user domain attribute
user_domain_dict = domain_results[user]
domain_list = domain_en2ch(user_domain_dict)
if domain_list:
results['domain_list'] = json.dumps(
domain_list) # [label1_en, label2_en, label3_en]
results['domain'] = domain_list[0] # label_ch
else:
results['domain'] = "其他"
results['domain_list'] = json.dumps(["其他"])
politics_label = politics_results[user]
results['politics'] = politics_en2ch(politics_label)
#add user character_sentiment attribute
#character_sentiment = character_sentiment_result_dict[user]
#results['character_sentiment'] = character_sentiment
#add user character_text attribtue
#character_text = character_text_result_dict[user]
#results['character_text'] = character_text
#add user profile attribute
register_dict = register_result[str(user)]
results = dict(results, **register_dict)
#add user_evaluate attribute---importance
results['importance'] = get_importance(results['domain'],
results['topic_string'],
results['fansnum'], fansnum_max)
#add user_evaluate attribute---activeness
user_activeness_time = activeness_results[user]
user_activeness_geo = json.loads(results['activity_geo_dict'])[-1]
results['activeness'] = get_activeness(user_activeness_geo,
user_activeness_time)
#add user_evaluate attribute---influence
results['influence'] = influence_results[user]
#bulk_action
action = {'index': {'_id': str(user)}}
bulk_action.extend([action, results])
status = save_user_results(bulk_action)
print "status:", status
return status
def test_cron_text_attribute_v2(user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts):
status = False
print 'start cron_text_attribute'
uid_list = user_keywords_dict.keys()
#get user flow information: hashtag, activity_geo, keywords
print 'get flow result'
flow_result = get_flow_information(uid_list)
print 'flow result len:', len(flow_result)
#get user profile information
print 'get register result'
register_result = get_profile_information(uid_list)
print 'register result len:', len(register_result)
#get user topic and domain by bulk action
print 'get topic and domain, politics'
topic_results_dict, topic_results_label = topic_classfiy(uid_list, user_keywords_dict)
domain_results = domain_classfiy(uid_list, user_keywords_dict)
politics_results = political_classify(uid_list, user_keywords_dict)
print "topic: ", topic_results_dict, topic_results_label
print "domain: ", domain_results
print "politics:", politics_results
#get user character attribute
#print 'get character result'
#type_mark = 0/1 for identify the task input status---just sentiment or text
#character_start_time = ts2datetime(character_start_ts)
#character_end_time = ts2datetime(character_start_ts + DAY * CHARACTER_TIME_GAP - DAY)
#print 'character_start_time:', character_start_time
#print 'character_end_time:', character_end_time
#character_sentiment_result_dict = classify_sentiment(uid_list, user_weibo_dict, character_start_time, character_end_time, WEIBO_API_INPUT_TYPE)
#character_text_result_dict = classify_topic(uid_list, user_keywords_dict)
#print 'character result len:', len(character_sentiment_result_dict), len(character_text_result_dict)
#get user fansnum max
fansnum_max = get_fansnum_max()
#get user activeness by bulk_action
print 'get activeness results'
activeness_results = get_activity_time(uid_list)
print 'activeness result len:', len(activeness_results)
#get user inlfuence by bulk action
print 'get influence'
influence_results = get_influence(uid_list)
print 'influence results len:', len(influence_results)
# compute text attribute
bulk_action = []
count = 0
for user in uid_list:
count += 1
results = {}
#get user text attribute: online_pattern
results['online_pattern'] = json.dumps(online_pattern_dict[user])
try:
results['online_pattern_aggs'] = '&'.join(online_pattern_dict[user].keys())
except:
results['online_pattern_aggs'] = ''
results['uid'] = str(user)
#add user flow information: hashtag, activity_geo, keywords
flow_dict = flow_result[str(user)]
results = dict(results, **flow_dict)
#add user topic attribute
user_topic_dict = topic_results_dict[user]
user_label_dict = topic_results_label[user]
results['topic'] = json.dumps(user_topic_dict) # {'topic1_en':pro1, 'topic2_en':pro2...}
results['topic_string'] = topic_en2ch(user_label_dict) # 'topic1_ch&topic2_ch&topic3_ch'
#add user domain attribute
user_domain_dict = domain_results[user]
domain_list = domain_en2ch(user_domain_dict)
if domain_list:
results['domain_list'] = json.dumps(domain_list) # [label1_en, label2_en, label3_en]
results['domain'] = domain_list[0] # label_ch
else:
results['domain'] = "其他"
results['domain_list'] = json.dumps(["其他"])
politics_label = politics_results[user]
results['politics'] = politics_en2ch(politics_label)
#add user character_sentiment attribute
#character_sentiment = character_sentiment_result_dict[user]
#results['character_sentiment'] = character_sentiment
#add user character_text attribtue
#character_text = character_text_result_dict[user]
#results['character_text'] = character_text
#add user profile attribute
register_dict = register_result[str(user)]
results = dict(results, **register_dict)
#add user_evaluate attribute---importance
results['importance'] = get_importance(results['domain'], results['topic_string'], results['fansnum'], fansnum_max)
#add user_evaluate attribute---activeness
user_activeness_time = activeness_results[user]
user_activeness_geo = json.loads(results['activity_geo_dict'])[-1]
results['activeness'] = get_activeness(user_activeness_geo, user_activeness_time)
#add user_evaluate attribute---influence
results['influence'] = influence_results[user]
#bulk_action
action = {'index':{'_id': str(user)}}
bulk_action.extend([action, results])
status = save_user_results(bulk_action)
print "status:", status
return status
def deal_bulk_action(user_info_list, fansnum_max):
start_ts = time.time()
uid_list = user_info_list.keys()
#acquire bulk user weibo data
if WEIBO_API_INPUT_TYPE == 0:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text_sentiment(uid_list)
else:
user_keywords_dict, user_weibo_dict, online_pattern_dict, character_start_ts = read_flow_text(uid_list)
#compute attribute--keywords, topic, online_pattern
#get user topic results by bulk action
topic_results_dict, topic_results_label = topic_classfiy(uid_list, user_keywords_dict)
domain_results = domain_classfiy(uid_list, user_keywords_dict)
politics_results = political_classify(uid_list, user_keywords_dict)
#update school attribute---is_school/school_string/school_dict
#school_results_dict = get_school(uid_list)
#get bulk action
bulk_action = []
for uid in uid_list:
results = {}
results['uid'] = uid
#results['is_school'] = school_results_dict[uid]['is_school']
#results['school_string'] = school_results_dict[uid]['school_string']
#results['school_dict'] = school_results_dict[uid]['school_dict']
#print 'is_school, school_string, school_dict:', results['is_school'],type(results['is_school']) ,results['school_string'],type(results['school_string']), results['school_dict'], type(results['school_dict'])
#add user topic attribute
user_topic_dict = topic_results_dict[uid]
user_label_dict = topic_results_label[uid]
results['topic'] = json.dumps(user_topic_dict)
results['topic_string'] = topic_en2ch(user_label_dict)
#add user domain attribute
user_domain_dict = domain_results[uid]
domain_list = domain_en2ch(user_domain_dict)
if domain_list:
results['domain_list'] = json.dumps(domain_list)
results['domain'] = domain_list[0]
else:
results['domain'] = "其他"
results['domain_list'] = json.dumps(["其他"])
politics_label = politics_results[uid]
results['politics'] = politics_en2ch(politics_label)
#add user keywords attribute
try:
keywords_dict = user_keywords_dict[uid]
except:
keywords_dict = {}
keywords_top50 = sorted(keywords_dict.items(), key=lambda x:x[1], reverse=True)[:50]
keywords_top50_string = '&'.join([keyword_item[0] for keyword_item in keywords_top50])
results['keywords'] = json.dumps(keywords_top50)
results['keywords_string'] = keywords_top50_string
#add online_pattern
try:
user_online_pattern = json.dumps(online_pattern_dict[uid])
except:
user_online_pattern = json.dumps({})
results['online_pattern'] = user_online_pattern
try:
results['online_pattern_aggs'] = '&'.join(user_online_pattern.keys())
except:
results['online_pattern_aggs'] = ''
#add user importance
user_domain = user_info_list[uid]['domain'].encode('utf-8')
user_fansnum = user_info_list[uid]['fansnum']
results['importance'] = get_importance(user_domain, results['topic_string'], user_fansnum, fansnum_max)
# politics
politics_label = politics_results[user]
results['politics'] = politics_en2ch(politics_label)
#bulk action
action = {'update':{'_id': uid}}
bulk_action.extend([action, {'doc': results}])
print 'bulk_action:', bulk_action
#es_user_portrait.bulk(bulk_action, index=portrait_index_name, doc_type=portrait_index_type)
end_ts = time.time()
#log_should_delete
#print '%s sec count %s' % (end_ts - start_ts, len(uid_list))
#log_should_delete
start_ts = end_ts
