def search_top_index(index_name, top_k=1, index_type="bci", top=False, sort_order="user_index"):
query_body = {
"query": {
"match_all": {}
},
"size": top_k,
"sort": [{sort_order: {"order": "desc"}}]
}
if top:
result = es.search(index=index_name, doc_type=index_type, body=query_body)['hits']['hits'][0]['_source'][sort_order]
else:
search_result = es.search(index=index_name, doc_type=index_type, body=query_body)['hits']['hits']
uid_list = []
for item in search_result:
uid_list.append(item['_id'])
profile_result = es_profile.mget(index="weibo_user",doc_type="user", body={"ids":uid_list}, _source=True)['docs']
portrait_result = es_portrait.mget(index="user_portrait", doc_type="user", body={"ids":uid_list}, _source=True)['docs']
result = []
rank = 1
for i in range(len(search_result)):
info = ['','','','']
info[0] = rank
if profile_result[i]['found']:
info[1] = profile_result[i]['_source'].get('photo_url','')
info[3] = profile_result[i]['_source'].get('nick_name','')
info[2] = search_result[i].get('_id','')
if sort_order in ["user_index","origin_weibo_retweeted_brust_average","origin_weibo_comment_brust_average"]:
info.append(search_result[i]['_source'][sort_order])
if portrait_result[i]['found']:
info.append("1")
else:
info.append("0")
elif sort_order == "origin_weibo_retweeted_top_number":
info.append(search_result[i]['_source']['origin_weibo_retweeted_top_number'])
mid = search_result[i]['_source']['origin_weibo_top_retweeted_id']
info.append(weiboinfo2url(info[2],mid))
if portrait_result[i]['found']:
info.append("1")
else:
info.append("0")
elif sort_order == "origin_weibo_comment_top_number":
info.append(search_result[i]['_source']['origin_weibo_comment_top_number'])
mid = search_result[i]['_source']['origin_weibo_top_comment_id']
info.append(weiboinfo2url(info[2],mid))
if portrait_result[i]['found']:
info.append("1")
else:
info.append("0")
rank += 1
result.append(info)
return result
def search_max_single_field(field, index_name, doctype, top_k=3):
# field = "origin_weibo_retweeted_top_number", "origin_weibo_comment_top_number"
query_body = {
"query": {
"match_all": {}
},
"sort": [{field: {"order": "desc"}}],
"size": top_k
}
return_list = []
rank = 1
count_c = 0
start = 0
while 1:
search_list = []
user_list = search_k(es, index_name, doctype, start, field, 100)
start += 100
for item in user_list:
uid = item.get('user','0')
search_list.append(uid) # uid list
search_result = es_portrait.mget(index="user_portrait", doc_type="user", body={"ids": search_list}, _source=True)["docs"]
profile_result = es_profile.mget(index="weibo_user", doc_type="user", body={"ids": search_list}, _source=True)["docs"]
for i in range(len(search_result)):
if search_result[i]['found']:
info = ['','','','','','','1']
info[0] = rank
info[2] = search_result[i].get('_id','')
if profile_result[i]['found']:
info[1] = profile_result[i]['_source'].get('photo_url','')
info[3] = profile_result[i]['_source'].get('nick_name','')
if 'retweeted' in field:
temp_mid = user_list[i]['origin_weibo_top_retweeted_id']
info[5] = weiboinfo2url(info[2], temp_mid)
info[4] = user_list[i]['origin_weibo_retweeted_top_number']
else:
temp_mid = user_list[i]['origin_weibo_top_comment_id']
info[5] = weiboinfo2url(info[2], temp_mid)
info[4] = user_list[i]['origin_weibo_comment_top_number']
rank += 1
return_list.append(info)
if rank >= int(top_k)+1:
return return_list
def group_user_weibo(task_name, submit_user, sort_type):
weibo_list = []
now_date = ts2datetime(time.time())
if sort_type == 'retweet':
sort_type = 'retweeted'
#run_type
if RUN_TYPE == 0:
now_date = RUN_TEST_TIME
sort_type = 'timestamp'
#step1: get group user
task_id = submit_user + '-' + task_name
try:
group_exist_result = es_group_result.get(index=group_index_name, doc_type=group_index_type,\
id=task_id)['_source']
except:
group_exist_result = {}
if not group_exist_result:
return 'group no exist'
#step2: get user weibo list
uid_list = group_exist_result['uid_list']
for i in range(6,-1,-1):
iter_date = ts2datetime(datetime2ts(now_date) - i * DAY)
index_name = flow_text_index_name_pre + iter_date
try:
weibo_result = es_flow_text.search(index=index_name, doc_type=flow_text_index_type,\
body={'query':{'filtered':{'filter':{'terms':{'uid': uid_list}}}}, 'sort':[{sort_type: {'order': 'desc'}}], 'size':100})['hits']['hits']
except:
weibo_result = []
if weibo_result:
weibo_list.extend(weibo_result)
#sort_weibo_list = sorted(weibo_list, key=lambda x:x['_source'][sort_type], reverse=True)[:100]
sort_weibo_list = weibo_list
#step3: get user name
try:
portrait_exist_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, \
body={'ids':uid_list})['docs']
except:
portrait_exist_result = []
uid2uname_dict = {}
for portrait_item in portrait_exist_result:
uid = portrait_item['_id']
if portrait_item['found'] == True:
source = portrait_item['_source']
uname = source['uname']
else:
uname = 'unknown'
uid2uname_dict[uid] = uname
weibo_list = []
for weibo_item in sort_weibo_list:
source = weibo_item['_source']
mid = source['mid']
uid = source['uid']
uname = uid2uname_dict[uid]
text = source['text']
ip = source['geo']
timestamp = source['timestamp']
date = ts2date(timestamp)
sentiment = source['sentiment']
weibo_url = weiboinfo2url(uid, mid)
#run_type:
if RUN_TYPE == 1:
try:
retweet_count = source['retweeted']
except:
retweet_count = 0
try:
comment_count = source['comment']
except:
comment_count = 0
try:
sensitive_score = source['sensitive']
except:
sensitive_score = 0
else:
retweet_count = 0
comment_count = 0
sensitive_score = 0
city = ip2city(ip)
weibo_list.append([mid, uid, uname, text, ip, city, timestamp, date, retweet_count, comment_count, sensitive_score, weibo_url])
if sort_type == 'timestamp':
new_weibo_list = sorted(weibo_list, key=lambda x:x[6], reverse=True)
elif sort_type == 'retweeted':
new_weibo_list = sorted(weibo_list, key=lambda x:x[8], reverse=True)
elif sort_type == 'comment':
new_weibo_list = sorted(weibo_list, key=lambda x:x[9], reverse=True)
elif sort_type == 'sensitive':
new_weibo_list = sorted(weibo_list, key=lambda x:x[10], reverse=True)
return new_weibo_list
def get_group_results(task_name, module):
result = []
try:
es_result = es.get(index=index_name, doc_type=index_type,
id=task_name)['_source']
#print 'result:', result
except:
return None
#basic module: gender, count, verified
if module == 'overview':
task_name = es_result['task_name']
submit_date = es_result['submit_date']
state = es_result['state']
tightness = es_result['tightness']
activeness = es_result['activeness']
importance = es_result['importance']
influence = es_result['influence']
result = [
task_name, submit_date, state, tightness, activeness, importance,
influence
]
if module == 'basic':
gender_dict = json.loads(es_result['gender'])
count = es_result['count']
verified = es_result['verified']
if verified:
verified_dict = json.loads(verified)
result = [gender_dict, count, verified]
if module == 'activity':
activity_geo_dict = json.loads(es_result['activity_geo'])
sort_activity_geo = sorted(activity_geo_dict.items(),
key=lambda x: x[1],
reverse=True)
activity_geo = sort_activity_geo[:50]
activity_trend = json.loads(es_result['activity_trend'])
online_pattern_dict = json.loads(es_result['online_pattern'])
sort_online_pattern = sorted(online_pattern_dict.items(),
key=lambda x: x[1],
reverse=True)
online_pattern = sort_online_pattern[:50]
geo_track = json.loads(es_result['geo_track'])
result = [activity_geo, activity_trend, online_pattern, geo_track]
if module == 'social':
#degree_his = json.loads(es_result['degree_his'])
density = es_result['density']
retweet_weibo_count = es_result['retweet_weibo_count']
retweet_user_count = es_result['retweet_user_count']
retweet_relation = json.loads(es_result['retweet_relation'])
uid_list = []
for relation in retweet_relation:
uid_list.append(relation[0])
uid_list.append(relation[1])
es_portrait_result = es.mget(index='user_portrait',
doc_type='user',
body={'ids': uid_list})['docs']
es_count = 0
new_retweet_relation = []
for relation in retweet_relation:
source_uid = relation[0]
source_item = es_portrait_result[es_count]
try:
source = source_item['_source']
source_uname = source['uname']
except:
source_uname = ''
target_uid = relation[1]
es_count += 1
target_item = es_portrait_result[es_count]
try:
source = target_item['_source']
target_uname = source['uname']
except:
target_uname = ''
count = relation[2]
new_retweet_relation.append(
[source_uid, source_uname, target_uid, target_uname, count])
uid_list = []
out_beretweet_relation = json.loads(
es_result['out_beretweet_relation'])
uid_list = []
uid_list = [item[0] for item in out_beretweet_relation]
es_portrait_result = es.mget(index='user_portrait',
doc_type='user',
body={'ids': uid_list})['docs']
es_count = 0
new_out_beretweet_relation = []
for i in range(len(uid_list)):
item = es_portrait_result[i]
uid = item['_id']
try:
source = item['_source']
uname = source['uname']
except:
uname = ''
out_relation_item = out_beretweet_relation[i][1:]
a = [uid, uname]
a.extend(out_relation_item)
#print 'add_item:', add_item
new_out_beretweet_relation.append(a)
result = [
new_retweet_relation, density, retweet_weibo_count,
retweet_user_count, new_out_beretweet_relation
]
if module == 'think':
domain_dict = json.loads(es_result['domain'])
topic_dict = json.loads(es_result['topic'])
psycho_status = json.loads(es_result['psycho_status'])
psycho_feature = json.loads(es_result['psycho_feature'])
result = [domain_dict, topic_dict, psycho_status, psycho_feature]
if module == 'text':
hashtag_dict = json.loads(es_result['hashtag'])
sort_hashtag = sorted(hashtag_dict.items(),
key=lambda x: x[1],
reverse=True)
hashtag = sort_hashtag[:50]
emoticon_dict = json.loads(es_result['emoticon'])
sort_emoticon = sorted(emoticon_dict.items(),
key=lambda x: x[1],
reverse=True)
emoticon = sort_emoticon[:5]
keyword_dict = json.loads(es_result['keywords'])
sort_keyword = sorted(keyword_dict.items(),
key=lambda x: x[1],
reverse=True)
keyword = sort_keyword[:50]
result = [hashtag, keyword, emoticon]
if module == 'influence':
importance_dis = json.loads(es_result['importance_his'])
activeness_his = json.loads(es_result['activeness_his'])
influence_his = json.loads(es_result['influence_his'])
user_influence_list = json.loads(es_result['user_influence_list'])
user_influence_result = []
for user_item in user_influence_list:
uid = user_item[0]
result_item = user_item[:5]
for i in range(5, 9):
item = user_item[i]
mid = item[1]
number = item[0]
if mid != 0 and uid:
weibolink = weiboinfo2url(uid, mid)
else:
weibolink = None
result_item.append((number, mid, weibolink))
user_influence_result.append(result_item)
'''
origin_max_retweeted_number =es_result['origin_max_retweeted_number']
origin_max_retweeted_id = es_result['origin_max_retweeted_id']
origin_max_retweeted_user = es_result['origin_max_retweeted_user']
if origin_max_retweeted_id != 0 and origin_max_retweeted_user != 0:
origin_max_retweeted_weibolink = weiboinfo2url(origin_max_retweeted_user, origin_max_retweeted_id)
else:
origin_max_retweeted_weibolink = None
origin_max_comment_number = es_result['origin_max_comment_number']
origin_max_comment_id = es_result['origin_max_comment_id']
origin_max_comment_user = es_result['origin_max_comment_user']
if origin_max_comment_id !=0 and origin_max_comment_user != 0:
origin_max_comment_weibolink = weiboinfo2url(origin_max_comment_user, origin_max_comment_id)
else:
origin_max_comment_weibolink = None
retweet_max_retweeted_number = es_result['retweet_max_retweeted_number']
retweet_max_retweeted_id = es_result['retweet_max_retweeted_id']
retweet_max_retweeted_user = es_result['retweet_max_retweeted_user']
if retweet_max_retweeted_id != 0 and retweet_max_retweeted_user != 0:
retweet_max_retweeted_weibolink = weiboinfo2url(retweet_max_retweeted_user, retweet_max_retweeted_id)
else:
retweet_max_retweeted_weibolink = None
retweet_max_comment_number = es_result['retweet_max_comment_number']
retweet_max_comment_id = es_result['retweet_max_comment_id']
retweet_max_comment_user = es_result['retweet_max_comment_user']
if retweet_max_comment_id != 0 and retweet_max_comment_user != 0:
retweet_max_comment_weibolink = weiboinfo2url(retweet_max_comment_user, retweet_max_comment_id)
else:
retweet_max_comment_weibolink = None
'''
result = [
importance_dis, activeness_his, influence_his,
user_influence_result
]
#print result
return result
def group_user_weibo(task_name, submit_user, sort_type):
weibo_list = []
now_date = ts2datetime(time.time())
#run_type
if RUN_TYPE == 0:
now_date = RUN_TEST_TIME
sort_type = 'timestamp'
#step1: get group user
task_id = submit_user + '-' + task_name
try:
group_exist_result = es_group_result.get(index=group_index_name, doc_type=group_index_type,\
id=task_id)['_source']
except:
group_exist_result = {}
if not group_exist_result:
return 'group no exist'
#step2: get user weibo list
uid_list = group_exist_result['uid_list']
for i in range(7, 0, -1):
iter_date = ts2datetime(datetime2ts(now_date) - i * DAY)
index_name = flow_text_index_name_pre + iter_date
try:
weibo_result = es_flow_text.search(index=index_name, doc_type=flow_text_index_type,\
body={'query':{'filtered':{'filter':{'terms':{'uid': uid_list}}}}, 'sort':sort_type, 'size':100})['hits']['hits']
except:
weibo_result = []
if weibo_result:
weibo_list.extend(weibo_result)
sort_weibo_list = sorted(weibo_list,
key=lambda x: x['_source'][sort_type],
reverse=True)[:100]
#step3: get user name
try:
portrait_exist_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, \
body={'ids':uid_list})['docs']
except:
portrait_exist_result = []
uid2uname_dict = {}
for portrait_item in portrait_exist_result:
uid = portrait_item['_id']
if portrait_item['found'] == True:
source = portrait_item['_source']
uname = source['uname']
else:
uname = 'unknown'
uid2uname_dict[uid] = uname
weibo_list = []
for weibo_item in sort_weibo_list:
source = weibo_item['_source']
mid = source['mid']
uid = source['uid']
uname = uid2uname_dict[uid]
text = source['text']
ip = source['geo']
timestamp = source['timestamp']
date = ts2date(timestamp)
sentiment = source['sentiment']
weibo_url = weiboinfo2url(uid, mid)
#run_type:
if RUN_TYPE == 1:
retweet_count = source['retweet_count']
comment_count = source['comment_count']
sensitive_score = source['sensitive_score']
else:
retweet_count = 0
comment_count = 0
sensitive_score = 0
city = ip2city(ip)
weibo_list.append([
mid, uid, uname, text, ip, city, timestamp, date, retweet_count,
comment_count, sensitive_score, weibo_url
])
return weibo_list
def get_group_results(task_name, module):
result = []
try:
es_result = es.get(index=index_name, doc_type=index_type, id=task_name)['_source']
#print 'result:', result
except:
return None
#basic module: gender, count, verified
if module=='overview':
task_name = es_result['task_name']
submit_date = es_result['submit_date']
state = es_result['state']
tightness = es_result['tightness']
activeness = es_result['activeness']
importance = es_result['importance']
influence = es_result['influence']
result = [task_name, submit_date, state, tightness, activeness, importance, influence]
if module=='basic':
gender_dict = json.loads(es_result['gender'])
count = es_result['count']
verified = es_result['verified']
if verified:
verified_dict = json.loads(verified)
result = [gender_dict, count, verified]
if module=='activity':
activity_geo_dict = json.loads(es_result['activity_geo'])
sort_activity_geo = sorted(activity_geo_dict.items(), key=lambda x:x[1], reverse=True)
activity_geo = sort_activity_geo[:50]
activity_trend = json.loads(es_result['activity_trend'])
online_pattern_dict = json.loads(es_result['online_pattern'])
sort_online_pattern = sorted(online_pattern_dict.items(), key=lambda x:x[1], reverse=True)
online_pattern = sort_online_pattern[:50]
geo_track = json.loads(es_result['geo_track'])
result = [activity_geo, activity_trend, online_pattern, geo_track]
if module=='social':
#degree_his = json.loads(es_result['degree_his'])
density = es_result['density']
retweet_weibo_count = es_result['retweet_weibo_count']
retweet_user_count = es_result['retweet_user_count']
retweet_relation = json.loads(es_result['retweet_relation'])
uid_list = []
for relation in retweet_relation:
uid_list.append(relation[0])
uid_list.append(relation[1])
es_portrait_result = es.mget(index='user_portrait', doc_type='user', body={'ids':uid_list})['docs']
es_count = 0
new_retweet_relation = []
for relation in retweet_relation:
source_uid = relation[0]
source_item = es_portrait_result[es_count]
try:
source = source_item['_source']
source_uname = source['uname']
except:
source_uname = ''
target_uid = relation[1]
es_count += 1
target_item = es_portrait_result[es_count]
try:
source = target_item['_source']
target_uname = source['uname']
except:
target_uname = ''
count = relation[2]
new_retweet_relation.append([source_uid, source_uname, target_uid, target_uname, count])
uid_list = []
out_beretweet_relation = json.loads(es_result['out_beretweet_relation'])
uid_list = []
uid_list = [item[0] for item in out_beretweet_relation]
es_portrait_result = es.mget(index='user_portrait', doc_type='user', body={'ids':uid_list})['docs']
es_count = 0
new_out_beretweet_relation = []
for i in range(len(uid_list)):
item = es_portrait_result[i]
uid = item['_id']
try:
source = item['_source']
uname = source['uname']
except:
uname = ''
out_relation_item = out_beretweet_relation[i][1:]
a = [uid, uname]
a.extend(out_relation_item)
#print 'add_item:', add_item
new_out_beretweet_relation.append(a)
result = [new_retweet_relation, density, retweet_weibo_count, retweet_user_count, new_out_beretweet_relation]
if module=='think':
domain_dict = json.loads(es_result['domain'])
topic_dict = json.loads(es_result['topic'])
psycho_status = json.loads(es_result['psycho_status'])
psycho_feature = json.loads(es_result['psycho_feature'])
result = [domain_dict, topic_dict, psycho_status, psycho_feature]
if module=='text':
hashtag_dict = json.loads(es_result['hashtag'])
sort_hashtag = sorted(hashtag_dict.items(), key=lambda x:x[1], reverse=True)
hashtag = sort_hashtag[:50]
emoticon_dict = json.loads(es_result['emoticon'])
sort_emoticon = sorted(emoticon_dict.items(), key=lambda x:x[1], reverse=True)
emoticon = sort_emoticon[:5]
keyword_dict = json.loads(es_result['keywords'])
sort_keyword = sorted(keyword_dict.items(), key=lambda x:x[1], reverse=True)
keyword = sort_keyword[:50]
result = [hashtag, keyword, emoticon]
if module=='influence':
importance_dis = json.loads(es_result['importance_his'])
activeness_his = json.loads(es_result['activeness_his'])
influence_his = json.loads(es_result['influence_his'])
user_influence_list = json.loads(es_result['user_influence_list'])
user_influence_result = []
for user_item in user_influence_list:
uid = user_item[0]
result_item = user_item[:5]
for i in range(5,9):
item = user_item[i]
mid = item[1]
number = item[0]
if mid != 0 and uid:
weibolink = weiboinfo2url(uid, mid)
else:
weibolink = None
result_item.append((number, mid, weibolink))
user_influence_result.append(result_item)
'''
origin_max_retweeted_number =es_result['origin_max_retweeted_number']
origin_max_retweeted_id = es_result['origin_max_retweeted_id']
origin_max_retweeted_user = es_result['origin_max_retweeted_user']
if origin_max_retweeted_id != 0 and origin_max_retweeted_user != 0:
origin_max_retweeted_weibolink = weiboinfo2url(origin_max_retweeted_user, origin_max_retweeted_id)
else:
origin_max_retweeted_weibolink = None
origin_max_comment_number = es_result['origin_max_comment_number']
origin_max_comment_id = es_result['origin_max_comment_id']
origin_max_comment_user = es_result['origin_max_comment_user']
if origin_max_comment_id !=0 and origin_max_comment_user != 0:
origin_max_comment_weibolink = weiboinfo2url(origin_max_comment_user, origin_max_comment_id)
else:
origin_max_comment_weibolink = None
retweet_max_retweeted_number = es_result['retweet_max_retweeted_number']
retweet_max_retweeted_id = es_result['retweet_max_retweeted_id']
retweet_max_retweeted_user = es_result['retweet_max_retweeted_user']
if retweet_max_retweeted_id != 0 and retweet_max_retweeted_user != 0:
retweet_max_retweeted_weibolink = weiboinfo2url(retweet_max_retweeted_user, retweet_max_retweeted_id)
else:
retweet_max_retweeted_weibolink = None
retweet_max_comment_number = es_result['retweet_max_comment_number']
retweet_max_comment_id = es_result['retweet_max_comment_id']
retweet_max_comment_user = es_result['retweet_max_comment_user']
if retweet_max_comment_id != 0 and retweet_max_comment_user != 0:
retweet_max_comment_weibolink = weiboinfo2url(retweet_max_comment_user, retweet_max_comment_id)
else:
retweet_max_comment_weibolink = None
'''
result = [importance_dis, activeness_his, influence_his, user_influence_result]
#print result
return result
def search_max_single_field(field, index_name, doctype, top_k=3):
# field = "origin_weibo_retweeted_top_number", "origin_weibo_comment_top_number"
query_body = {
"query": {
"match_all": {}
},
"sort": [{
field: {
"order": "desc"
}
}],
"size": top_k
}
return_list = []
rank = 1
count_c = 0
start = 0
while 1:
search_list = []
user_list = search_k(es, index_name, doctype, start, field, 100)
start += 100
for item in user_list:
uid = item.get('user', '0')
search_list.append(uid) # uid list
search_result = es_portrait.mget(index=portrait_index_name,
doc_type=portrait_index_type,
body={"ids": search_list},
_source=True)["docs"]
profile_result = es_profile.mget(index=profile_index_name,
doc_type=profile_index_type,
body={"ids": search_list},
_source=True)["docs"]
for i in range(len(search_result)):
if search_result[i]['found']:
info = ['', '', '', '', '', '', '1']
info[0] = rank
info[2] = search_result[i].get('_id', '')
if profile_result[i]['found']:
info[1] = profile_result[i]['_source'].get('photo_url', '')
info[3] = profile_result[i]['_source'].get('nick_name', '')
if 'retweeted' in field:
temp_mid = user_list[i]['origin_weibo_top_retweeted_id']
info[5] = weiboinfo2url(info[2], temp_mid)
info[4] = user_list[i]['origin_weibo_retweeted_top_number']
else:
temp_mid = user_list[i]['origin_weibo_top_comment_id']
info[5] = weiboinfo2url(info[2], temp_mid)
info[4] = user_list[i]['origin_weibo_comment_top_number']
rank += 1
return_list.append(info)
if rank >= int(top_k) + 1:
return return_list
def search_top_index(index_name,
top_k=1,
index_type="bci",
top=False,
sort_order="user_index"):
query_body = {
"query": {
"match_all": {}
},
"size": top_k,
"sort": [{
sort_order: {
"order": "desc"
}
}]
}
if top:
result = es.search(
index=index_name, doc_type=index_type,
body=query_body)['hits']['hits'][0]['_source'][sort_order]
else:
search_result = es.search(index=index_name,
doc_type=index_type,
body=query_body)['hits']['hits']
uid_list = []
for item in search_result:
uid_list.append(item['_id'])
profile_result = es_profile.mget(index=profile_index_name,
doc_type=profile_index_type,
body={"ids": uid_list},
_source=True)['docs']
portrait_result = es_portrait.mget(index=portrait_index_name,
doc_type=portrait_index_type,
body={"ids": uid_list},
_source=True)['docs']
result = []
rank = 1
for i in range(len(search_result)):
info = ['', '', '', '']
info[0] = rank
if profile_result[i]['found']:
info[1] = profile_result[i]['_source'].get('photo_url', '')
info[3] = profile_result[i]['_source'].get('nick_name', '')
info[2] = search_result[i].get('_id', '')
if sort_order in [
"user_index", "origin_weibo_retweeted_brust_average",
"origin_weibo_comment_brust_average"
]:
info.append(search_result[i]['_source'][sort_order])
if portrait_result[i]['found']:
info.append("1")
else:
info.append("0")
elif sort_order == "origin_weibo_retweeted_top_number":
info.append(search_result[i]['_source']
['origin_weibo_retweeted_top_number'])
mid = search_result[i]['_source'][
'origin_weibo_top_retweeted_id']
info.append(weiboinfo2url(info[2], mid))
if portrait_result[i]['found']:
info.append("1")
else:
info.append("0")
elif sort_order == "origin_weibo_comment_top_number":
info.append(search_result[i]['_source']
['origin_weibo_comment_top_number'])
mid = search_result[i]['_source'][
'origin_weibo_top_comment_id']
info.append(weiboinfo2url(info[2], mid))
if portrait_result[i]['found']:
info.append("1")
else:
info.append("0")
rank += 1
result.append(info)
return result
