def submit_identify_in_uname(input_data):
date = input_data['date']
submit_user = input_data['user']
upload_data = input_data['upload_data']
# get uname list from upload data
uname_list = upload_data.split('\n')
uid_list = []
#step1: get uid list from uname
profile_exist_result = es_user_profile.search(
index=profile_index_name,
doc_type=profile_index_type,
body={'query': {
'terms': {
'nick_name': uname_list
}
}},
_source=False)['hits']['hits']
for profile_item in profile_exist_result:
uid = profile_item['_id']
uid_list.append(uid)
if not uid_list:
return 'uname list valid'
#step2: filter user not in user_portrait and compute
#step2.1: identify in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name,
doc_type=portrait_index_type,
body={'ids':
uid_list})['docs']
new_uid_list = [
exist_item['_id'] for exist_item in exist_portrait_result
if exist_item['found'] == False
]
if not new_uid_list:
return 'uname list all in'
#step2.2: identify in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_list = list(new_uid_set - compute_set)
if not in_uid_list:
return 'uname list all in'
#step3: save submit
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(
r.hkeys(hashname_sensitive))
for in_item in in_uid_list:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system': '0', 'operation': submit_user}
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
return True
def new_identify_in(data, date, submit_user):
in_status = 1
compute_status = 0
hashname_submit = "submit_recomment_" + date
hashname_influence = "recomment_" + date + "_influence"
hashname_sensitive = "recomment_" + date + "_sensitive"
submit_user_recomment = "recomment_" + submit_user + "_" + str(
date) # 用户自推荐名单
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(
r.hkeys(hashname_sensitive)) # 系统自动推荐名单
for item in data:
date = item[0] # identify the date form '2013-09-01' with web
uid = item[1]
#status = item[2]
if uid in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, uid))
recommentor_list = (tmp['operation']).split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = "&".join(new_list)
else:
tmp = {"system": "0", "operation": submit_user}
r.hset(hashname_submit, uid, json.dumps(tmp))
r.hset(submit_user_recomment, uid, "0")
return True
def submit_identify_in_uname(input_data):
date = input_data['date']
submit_user = input_data['user']
operation_type = input_data['operation_type']
upload_data = input_data['upload_data']
# get uname list from upload data
uname_list_pre = upload_data.split('\n')
uname_list = [item.split('\r')[0] for item in uname_list_pre]
uid_list = []
have_in_user_list = []
invalid_user_list = []
valid_uname_list = []
#step1: get uid list from uname
profile_exist_result = es_user_profile.search(index=profile_index_name, doc_type=profile_index_type, body={'query':{'terms':{'nick_name': uname_list}}}, _source=False, fields=['nick_name'])['hits']['hits']
for profile_item in profile_exist_result:
uid = profile_item['_id']
uid_list.append(uid)
uname = profile_item['fields']['nick_name'][0]
valid_uname_list.append(uname)
invalid_user_list = list(set(uname_list) - set(valid_uname_list))
if len(invalid_user_list) != 0:
return False, 'invalid user info', invalid_user_list
#step2: filter user not in user_portrait and compute
#step2.1: identify in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids': uid_list})['docs']
new_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==False]
have_in_user_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==True]
if not new_uid_list:
return False, 'all user in'
#step2.2: identify in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_list = list(new_uid_set - compute_set)
if not in_uid_list:
return False, 'all user in'
#step3: save submit
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
#identify final submit user list
final_submit_user_list = []
for in_item in in_uid_list:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system':'0', 'operation': submit_user}
if operation_type == 'submit':
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
final_submit_user_list.append(in_item)
return True, invalid_user_list, have_in_user_list, final_submit_user_list
def submit_identify_in_url(input_data):
date = input_data['date']
submit_user = input_data['user']
operation_type = input_data['operation_type']
upload_data = input_data['upload_data']
#step1: get uid list from input_data url
url_list_pre = upload_data.split('\n')
url_list = [item.split('\r')[0] for item in url_list_pre]
uid_list = []
invalid_uid_list = []
have_in_uid_list = []
for url_item in url_list:
try:
#url_item = 'http://weibo.com/p/1002065727942146/album?.....'
url_list = url_item.split('/')
uid = url_list[4][-10:]
uid_list.append(uid)
except:
invalid_uid_list.append(url_item)
if len(invalid_uid_list)!=0:
return False, 'invalid user info', invalid_uid_list
#step2: identify uid list is not exist in user_portrait and compute
#step2.1: identify in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids':uid_list}, _source=True)['docs']
new_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==False]
have_in_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==True]
#step2.2: identify in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_list = list(new_uid_set - compute_set)
if len(in_uid_list)==0:
return False, 'all user in'
#step3: save
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
#identify the final submit user
final_submit_user_list = []
for in_item in in_uid_list:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system': '0', 'operation': submit_user}
if operation_type == 'submit':
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
final_submit_user_list.append(in_item)
return True, invalid_uid_list, have_in_uid_list, final_submit_user_list
def submit_identify_in_url(input_data):
date = input_data['date']
submit_user = input_data['user']
operation_type = input_data['operation_type']
upload_data = input_data['upload_data']
#step1: get uid list from input_data url
url_list_pre = upload_data.split('\n')
url_list = [item.split('\r')[0] for item in url_list_pre]
uid_list = []
invalid_uid_list = []
have_in_uid_list = []
for url_item in url_list:
try:
#url_item = 'http://weibo.com/p/1002065727942146/album?.....'
url_list = url_item.split('/')
uid = url_list[4][-10:]
uid_list.append(uid)
except:
invalid_uid_list.append(url_item)
if len(invalid_uid_list)!=0:
return False, 'invalid user info', invalid_uid_list
#step2: identify uid list is not exist in user_portrait and compute
#step2.1: identify in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids':uid_list}, _source=True)['docs']
new_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==False]
have_in_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==True]
#step2.2: identify in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_list = list(new_uid_set - compute_set)
if len(in_uid_list)==0:
return False, 'all user in'
#step3: save
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
#identify the final submit user
final_submit_user_list = []
for in_item in in_uid_list:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system': '0', 'operation': submit_user}
if operation_type == 'submit':
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
final_submit_user_list.append(in_item)
return True, invalid_uid_list, have_in_uid_list, final_submit_user_list
def identify_compute(data):
results = False
compute_status = 1
hash_name = 'compute'
uid2compute = r.hgetall(hash_name)
for item in data:
uid = item[1]
result = r.hget(hash_name, uid)
in_date = json.loads(result)[0]
r.hset(hash_name, uid, json.dumps([in_date, compute_status]))
return True
def identify_compute(data):
results = False
compute_status = 1
hash_name = 'compute'
uid2compute = r.hgetall(hash_name)
for item in data:
uid = item[1]
result = r.hget(hash_name, uid)
in_date = json.loads(result)[0]
r.hset(hash_name, uid, json.dumps([in_date, compute_status]))
return True
def submit_identify_in_uname(input_data):
date = input_data['date']
submit_user = input_data['user']
upload_data = input_data['upload_data']
# get uname list from upload data
uname_list = upload_data.split('\n')
uid_list = []
#step1: get uid list from uname
profile_exist_result = es_user_profile.search(index=profile_index_name, doc_type=profile_index_type, body={'query':{'terms':{'nick_name': uname_list}}}, _source=False)['hits']['hits']
for profile_item in profile_exist_result:
uid = profile_item['_id']
uid_list.append(uid)
if not uid_list:
return 'uname list valid'
#step2: filter user not in user_portrait and compute
#step2.1: identify in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids': uid_list})['docs']
new_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==False]
if not new_uid_list:
return 'uname list all in'
#step2.2: identify in compute
new_uid_set = set(new_uid_list)
compute_set = r.hkeys('compute')
in_uid_list = list(new_uid_set - compute_set)
if not in_uid_list:
return 'uname list all in'
#step3: save submit
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
for in_item in in_uid_list:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, uid))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system':'0', 'operation': submit_user}
r.hset(hashname_submit, uid, json.dumps(tmp))
r.hset(submit_user_recomment, uid, '0')
return True
def identify_in(data):
in_status = 1
compute_status = 0
compute_hash_name = 'compute'
for item in data:
date = item[0] # identify the date form '2013-09-01' with web
uid = item[1]
status = item[2]
value_string = []
identify_in_hashname = "identify_in_" + str(date)
r.hset(identify_in_hashname, uid, in_status)
if status == '1':
in_date = date
compute_status = '1'
elif status == '2':
in_date = date
compute_status = '2'
r.hset(compute_hash_name, uid, json.dumps([in_date, compute_status]))
return True
def identify_in(data):
in_status = 1
compute_status = 0
compute_hash_name = 'compute'
for item in data:
date = item[0] # identify the date form '2013-09-01' with web
uid = item[1]
status = item[2]
value_string = []
identify_in_hashname = "identify_in_" + str(date)
r.hset(identify_in_hashname, uid, in_status)
if status == '1':
in_date = date
compute_status = '1'
elif status == '2':
in_date = date
compute_status = '2'
r.hset(compute_hash_name, uid, json.dumps([in_date, compute_status]))
return True
def submit_identify_in_uid(input_data):
date = input_data['date']
submit_user = input_data['user']
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(
r.hkeys(hashname_sensitive))
upload_data = input_data['upload_data']
line_list = upload_data.split('\n')
uid_list = []
for line in line_list:
uid = line[:10]
if len(uid) == 10:
uid_list.append(uid)
#identify the uid is not exist in user_portrait and compute
#step1: filter in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name,
doc_type=portrait_index_type,
body={'ids': uid_list},
_source=False)['docs']
for exist_item in exist_portrait_result:
if exist_item['found'] == False:
new_uid_list.append(exist_item['_id'])
#step2: filter in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_set = list(new_uid_set - compute_set)
for in_item in in_uid_set:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashtname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system': '0', 'operation': submit_user}
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
return True
def identify_in(data):
#in_status = 1
compute_status = 0
in_hash_name = 'recomment_'
compute_hash_name = 'compute'
for item in data:
date = item[0] # identify the date form '2013-09-01' with web
in_hash_key = in_hash_name + str(date)
uid = item[1]
status = item[2]
value_string = []
r.hset(in_hash_key, uid, status)
if status == '1':
in_date = date
compute_status = '1'
elif status == '2':
in_date = date
compute_status = '2'
r.hset(compute_hash_name, uid, json.dumps([in_date, compute_status]))
return True
def new_identify_in(data, date, submit_user):
in_status = 1
compute_status = 0
hashname_submit = "submit_recomment_" + date
hashname_influence = "recomment_" + date + "_influence"
hashname_sensitive = "recomment_" + date + "_sensitive"
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive)) # 系统自动推荐名单
for item in data:
date = item[0] # identify the date form '2013-09-01' with web
uid = item[1]
#status = item[2]
if uid in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, uid))
recommentor_list = (tmp['operation']).split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = "&".join(new_list)
else:
tmp = {"system":"0", "operation":submit_user}
r.hset(hashname_submit, uid, json.dumps(tmp))
return True
def submit_identify_in_url(input_data):
date = input_data['date']
submit_user = input_data['user']
upload_data = input_data['upload_data']
#step1: get uid list from input_data url
url_list = upload_data.split('\n')
uid_list = []
for url_item in url_list:
#url_item = 'weibo.com/p/1002065727942146/album?.....'
url_list = url_item.split('/')
uid = url_list[2][-10:]
uid_list.append(uid)
#step2: identify uid list is not exist in user_portrait and compute
#step2.1: identify in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids':uid_list}, _source=True)['docs']
new_uid_list = [exist_item['_id'] for exist_item in exist_portrait_result if exist_item['found']==False]
#step2.2: identify in compute
new_uid_set = set(new_uid_list)
compute_set = r.hkeys('compute')
in_uid_list = list(new_uid_set - compute_set)
#step3: save
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
for in_item in in_uid_list:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, uid))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system': '0', 'operation': submit_user}
r.hset(hashname_submit, uid, json.dumps(tmp))
r.hset(submit_user_recomment, uid, '0')
return True
def submit_identify_in_uid(input_data):
date = input_data['date']
submit_user = input_data['user']
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
upload_data = input_data['upload_data']
line_list = upload_data.split('\n')
uid_list = []
for line in line_list:
uid = line[:10]
if len(uid)==10:
uid_list.append(uid)
#identify the uid is not exist in user_portrait and compute
#step1: filter in user_portrait
new_uid_list = []
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids':uid_list}, _source=False)['docs']
for exist_item in exist_portrait_result:
if exist_item['found'] == False:
new_uid_list.append(exist_item['_id'])
#step2: filter in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_set = list(new_uid_set - compute_set)
for in_item in in_uid_set:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashtname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system':'0', 'operation':submit_user}
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
return True
def submit_identify_in_uid(input_data):
date = input_data['date']
submit_user = input_data['user']
operation_type = input_data['operation_type']
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
upload_data = input_data['upload_data']
line_list = upload_data.split('\n')
uid_list = []
invalid_uid_list = []
for line in line_list:
uid = line.split('\r')[0]
#if len(uid)==10:
# uid_list.append(uid)
if uid != '':
uid_list.append(uid)
if len(invalid_uid_list)!=0:
return False, 'invalid user info', invalid_uid_list
#identify the uid is not exist in user_portrait and compute
#step1: filter in user_portrait
new_uid_list = []
have_in_uid_list = []
try:
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids':uid_list}, _source=False)['docs']
except:
exist_portrait_result = []
if exist_portrait_result:
for exist_item in exist_portrait_result:
if exist_item['found'] == False:
new_uid_list.append(exist_item['_id'])
else:
have_in_uid_list.append(exist_item['_id'])
else:
new_uid_list = uid_list
#step2: filter in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_set = list(new_uid_set - compute_set)
print 'new_uid_set:', new_uid_set
print 'in_uid_set:', in_uid_set
if len(in_uid_set)==0:
return False, 'all user in'
#identify the final add user
final_submit_user_list = []
for in_item in in_uid_set:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system':'0', 'operation':submit_user}
if operation_type == 'submit':
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
final_submit_user_list.append(in_item)
return True, invalid_uid_list, have_in_uid_list, final_submit_user_list
def submit_identify_in_uid(input_data):
date = input_data['date']
submit_user = input_data['user']
operation_type = input_data['operation_type']
hashname_submit = 'submit_recomment_' + date
hashname_influence = 'recomment_' + date + '_influence'
hashname_sensitive = 'recomment_' + date + '_sensitive'
submit_user_recomment = 'recomment_' + submit_user + '_' + str(date)
auto_recomment_set = set(r.hkeys(hashname_influence)) | set(r.hkeys(hashname_sensitive))
upload_data = input_data['upload_data']
line_list = upload_data.split('\n')
uid_list = []
invalid_uid_list = []
for line in line_list:
uid = line.split('\r')[0]
#if len(uid)==10:
# uid_list.append(uid)
if uid != '':
uid_list.append(uid)
if len(invalid_uid_list)!=0:
return False, 'invalid user info', invalid_uid_list
#identify the uid is not exist in user_portrait and compute
#step1: filter in user_portrait
new_uid_list = []
have_in_uid_list = []
try:
exist_portrait_result = es_user_portrait.mget(index=portrait_index_name, doc_type=portrait_index_type, body={'ids':uid_list}, _source=False)['docs']
except:
exist_portrait_result = []
if exist_portrait_result:
for exist_item in exist_portrait_result:
if exist_item['found'] == False:
new_uid_list.append(exist_item['_id'])
else:
have_in_uid_list.append(exist_item['_id'])
else:
new_uid_list = uid_list
#step2: filter in compute
new_uid_set = set(new_uid_list)
compute_set = set(r.hkeys('compute'))
in_uid_set = list(new_uid_set - compute_set)
print 'new_uid_set:', new_uid_set
print 'in_uid_set:', in_uid_set
if len(in_uid_set)==0:
return False, 'all user in'
#identify the final add user
final_submit_user_list = []
for in_item in in_uid_set:
if in_item in auto_recomment_set:
tmp = json.loads(r.hget(hashname_submit, in_item))
recommentor_list = tmp['operation'].split('&')
recommentor_list.append(str(submit_user))
new_list = list(set(recommentor_list))
tmp['operation'] = '&'.join(new_list)
else:
tmp = {'system':'0', 'operation':submit_user}
if operation_type == 'submit':
r.hset(hashname_submit, in_item, json.dumps(tmp))
r.hset(submit_user_recomment, in_item, '0')
final_submit_user_list.append(in_item)
return True, invalid_uid_list, have_in_uid_list, final_submit_user_list
