def acquire_user_by_id(uid):
XAPIAN_USER_DATA_PATH = "/home/xapian/xapian_user/"
user_search = XapianSearch(path=XAPIAN_USER_DATA_PATH, name="master_timeline_user", schema_version=1)
result = user_search.search_by_id(int(uid), fields=["name", "location", "followers_count", "friends_count"])
user = {}
if result:
user["name"] = result["name"]
user["location"] = result["location"]
user["count1"] = result["followers_count"]
user["count2"] = result["friends_count"]
return user
def acquire_user_by_id(uid):
user_search = XapianSearch(path=XAPIAN_USER_DATA_PATH, name='master_timeline_user', schema_version=1)
result = user_search.search_by_id(int(uid), fields=['name', 'location', 'followers_count', 'friends_count', 'profile_image_url'])
user = {}
if result:
user['name'] = result['name']
user['location'] = result['location']
user['followers_count'] = result['followers_count']
user['friends_count'] = result['friends_count']
user['profile_image_url'] = result['profile_image_url']
else:
return None
return user
def acquire_user_by_id(uid):
XAPIAN_USER_DATA_PATH = '/home/xapian/xapian_user/'
user_search = XapianSearch(path=XAPIAN_USER_DATA_PATH,
name='master_timeline_user',
schema_version=1)
result = user_search.search_by_id(
int(uid),
fields=['name', 'location', 'followers_count', 'friends_count'])
user = {}
if result:
user['name'] = result['name']
user['location'] = result['location']
user['count1'] = result['followers_count']
user['count2'] = result['friends_count']
return user
def getXapianWeiboByDate(datestr):
# datestr: 20130908
stub_file = path + datestr
if os.path.exists(stub_file):
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
return None
def getXapianWeiboByTopic(topic_id='545f4c22cf198b18c57b8014'):
stub_file = XAPIAN_WEIBO_TOPIC_DATA_PATH + 'stub/xapian_weibo_topic_stub_' + str(
topic_id)
if os.path.exists(stub_file):
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
return None
def getXapianWeiboByTopic(topic_id='54635178e74050a373a1b939'):
stub_file = XAPIAN_WEIBO_TOPIC_DATA_PATH + 'stub/xapian_weibo_topic_stub_' + str(
topic_id)
if os.path.exists(stub_file):
print 'stub exist'
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
print 'stub not exist'
return None
def getXapianWeiboByTopic(topic_id='54ccbfab5a220134d9f7fc1b37'):
stub_file = XAPIAN_WEIBO_TOPIC_DATA_PATH + 'stub/xapian_weibo_topic_stub_' + str(
topic_id)
if os.path.exists(stub_file):
print 'stub exist'
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
print 'stub not exist'
return None
def getXapianWeiboByTopic(topic):
stub_file = '/home/ubuntu4/ljh/csv/stub/master_timeline_weibo_topic'
print stub_file
if os.path.exists(stub_file):
print 'stub exist'
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
print 'stub not exist'
return None
def getXapianWeiboByDate(datestr):
# datestr: 20130908
stub_file = path + datestr
print stub_file
if os.path.exists(stub_file):
print 'step--stub exist'
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
print 'stub not exist'
return None
def getXapianWeiboByTopic(topic, start_ts, end_ts):
topic_id = topic2xapian(topic, start_ts, end_ts)
XAPIAN_WEIBO_TOPIC_DATA_PATH = '/home/xapian/xapian_weibo_topic/'
stub_file = XAPIAN_WEIBO_TOPIC_DATA_PATH + 'stub/xapian_weibo_topic_stub_' + str(topic_id)
if os.path.exists(stub_file):
print 'stub exist'
xapian_search_weibo = XapianSearch(stub=stub_file, schema_version='5')
return xapian_search_weibo
else:
print 'stub not exist'
return None
def acquire_user_by_id(uid):
user_search = XapianSearch(path=XAPIAN_USER_DATA_PATH,
name='master_timeline_user',
schema_version=1)
result = user_search.search_by_id(int(uid),
fields=[
'name', 'location',
'followers_count', 'friends_count',
'profile_image_url'
])
user = {}
if result:
user['name'] = result['name']
user['location'] = result['location']
user['followers_count'] = result['followers_count']
user['friends_count'] = result['friends_count']
user['profile_image_url'] = result['profile_image_url']
else:
return None
return user
def getXapianWeiboByDuration(datestr_list):
stub_file_list = []
for datestr in datestr_list:
stub_file = path + datestr
if os.path.exists(stub_file):
stub_file_list.append(stub_file)
if len(stub_file_list):
xapian_search_weibo = XapianSearch(stub=stub_file_list,
include_remote=True,
schema_version='5')
return xapian_search_weibo
else:
return None
'university', 'homeadmin', 'abroadadmin', 'homemedia', 'abroadmedia', 'folkorg', \
'lawyer', 'politician', 'mediaworker', 'activer', 'grassroot', 'other']
DOMAIN_ZH_LIST = [u'文化', u'教育', u'娱乐', u'时尚', u'财经', u'媒体', u'体育', u'科技', u'境外', \
u'高校微博', u'境内机构', u'境外机构', u'境内媒体', u'境外媒体', u'民间组织', u'律师', \
u'政府官员', u'媒体人士', u'活跃人士', u'草根', u'其它']
MYSQL_HOST = '219.224.135.47'
MYSQL_USER = '******'
MYSQL_DB = 'weibocase'
MONGODB_HOST = '219.224.135.47'
MONGODB_PORT = 27019
SSDB_PORT = 8888
SSDB_HOST = '219.224.135.47' # SSDB服务器在47
XAPIAN_USER_DATA_PATH = '/home/xapian/xapian_user/'
XAPIAN_WEIBO_TOPIC_DATA_PATH = '/home/xapian/xapian_weibo_topic/'
xapian_search_user = XapianSearch(path=XAPIAN_USER_DATA_PATH,
name='master_timeline_user',
schema_version=1)
API_HOST = '219.224.135.47'
API_PORT = 9115
MASTER_TIMELINE_54API_MONGOD_HOST = '219.224.135.47'
MASTER_TIMELINE_54API_MONGOD_PORT = 27019
MASTER_TIMELINE_54API_WEIBO_DB = '54api_weibo_v2'
MASTER_TIMELINE_54API_USER_COLLECTION = 'master_timeline_user'
MASTER_TIMELINE_54API_WEIBO_DAILY_COLLECTION_PREFIX = 'master_timeline_weibo_weekly_'
MASTER_TIMELINE_54API_WEIBO_TOPIC_COLLECTION_PREFIX = 'master_timeline_weibo_topic_'
MASTER_TIMELINE_54API_TOPIC_COLLECTION = 'master_timeline_topic'
MASTER_TIMELINE_54API_WEIBO_REPOST_COLLECTION = 'master_timeline_weibo_repost'
MINUTE = 60
FIFTEENMINUTES = 15 * MINUTE
HOUR = 3600
SIXHOURS = 6 * HOUR
DAY = 24 * HOUR
INTERVAL = TENSECONDS
REDIS_HOST = '219.224.135.48'
REDIS_PORT = 6379
USER_DOMAIN = 'user_domain' # user domain hash
BEGIN_TS = time.mktime(datetime.datetime(2013, 9, 1, 0, 0, 0).timetuple())
END_TS = time.mktime(datetime.datetime(2013, 9, 1, 0, 1, 0).timetuple())
s = XapianSearch(stub = PATH, schema_version = '5')
def _default_redis(host = REDIS_HOST, port = REDIS_PORT, db = 0):
return redis.StrictRedis(host, port, db)
r = _default_redis()
def cron_index_topic(topic, begin_ts = BEGIN_TS, end_ts = END_TS):
if topic and topic != '':
topic = topic.strip()
query_dict = {
'timestamp':{'$gt':begin_ts,'$lt':end_ts},
'topics':topic
}
count,results = s.search(query=query_dict, sort_by=[SORT_FIELD], fields=RESP_ITER_KEYS)
# -*- coding:utf-8 -*-
import sys
import time
import datetime
sys.path.append('../xapian_case')
from xapian_case.xapian_backend import XapianSearch
from xapian_case.utils import top_keywords, not_low_freq_keywords, gen_mset_iter
# 默认schema_version为2
s = XapianSearch(path='/home/ubuntu3/huxiaoqian/data/20140724/20140724/',
name='master_timeline_weibo',
schema_version='5')
# import和初始化, 请使用下面的用法
# from xapian_weibo.xapian_backend import XapianSearch
# s = XapianSearch(path='/opt/xapian_weibo/data/', name='master_timeline_weibo')
# 查询条件有user(id),text,topic,timestamp,reposts_count,comments_count,attitudes_count(从timestamp开始后面四个查询指标可以指定范围和排序)
# 返回字段基本和新浪api的返回字段相同，注意没有created_at，而是timestamp
# 值得注意的是新增返回字段terms，返回的是每条微博里的词和以及词频的dict（字典），所有不用自己取出来之后再分词
# 若fields参数不指定，或者为None,则返回所有字段，除terms之外
# 如果需要返回terms，请一一指定需要的字段，并包括terms
# 简单示例如下
'''
count, get_results = s.search(query={'text': [u'男士']}, sort_by=['-timestamp'], fields=['text', 'timestamp', 'user', 'terms', '_id'])
print 'query1:'
#根据text查询
if count!=0:
for r in get_results():
def save_weibos(excel_name, topic, child_topic_list, w_limit): # 这里需要根据文本内容查询相关微博id等
data = xlrd.open_workbook(excel_name)
weibos_dict = {}
for i in child_topic_list:
#if i == '0':
# continue
weibos_dict[i] = []
table_weibos = data.sheet_by_name(str(int(i)))
n_row_weibos = table_weibos.nrows
if n_row_weibos <= w_limit:
n_rows = n_row_weibo
else:
n_rows = w_limit # 考虑到数据已经根据权重从大到小排列
for j in range(n_rows):
line = table_weibos.row_values(j) # 缺少根据文本查询微博文本对应的其他微博内容
weibo_text = line[1]
weibo_weight = line[0]
try:
weibos_dict[i].append((weibo_text, weibo_weight)) # 实际上这里append的应该是weibo的完整内容，并且是将username等获取到的
except:
weibos_dict[i]=[(weibo_text, weibo_weight)]
#print 'weibos_dict:', weibos_dict
#获取微博具体数据，仅作测试用
s = XapianSearch(path='/home/ubuntu3/huxiaoqian/case/20140724/20140804/', name='master_timeline_weibo',schema_version='5')
begin_ts = 1378050300
end_ts = 1378051200
query_dict = {
'timestamp': {'$gt':begin_ts, '$lt': end_ts},
'message_type' : 2
}
weibos_dict_new = {}
scount, weibo_results =s.search(query=query_dict, fields=fields_list)
#print 'scount:', scount
i = 0
j = 0
for weibo in weibo_results():
if i==11:
break
weibo['text'] = weibos_dict[str(i)][j][0]
#获取username，profileimage,weibourl
username, profileimage = getuserinfo(weibo['user'])
weibo['username'] = username
weibo['profile_image_url'] = profileimage
weibo['timestamp'] = ts2date(weibo['timestamp'])
weibo['weibo_link'] = weiboinfo2url(weibo['user'],weibo['_id'])
#获取username， profileimage,weibourl结束
weight = weibos_dict[str(i)][j][1]
try:
weibos_dict_new[i].append((weibo, weight))
except:
weibos_dict_new[i] = [(weibo, weight)]
if j==4:
j = 0
i += 1
else:
j +=1
#分割线
for i in range(len(child_topic_list)):
item = OpinionTestWeibos(topic, i, json.dumps(weibos_dict_new[i]))
item_exist = db.session.query(OpinionTestWeibos).filter(OpinionTestWeibos.topic==topic, \
OpinionTestWeibos.child_topic==i).first()
if item_exist:
db.session.delete(item_exist)
db.session.add(item)
db.session.commit()
# -*- coding:utf-8 -*-
import sys
import time
import datetime
sys.path.append('../xapian_case')
from xapian_case.xapian_backend import XapianSearch
from xapian_case.utils import top_keywords, not_low_freq_keywords, gen_mset_iter
# 默认schema_version为2
s = XapianSearch(path='/home/ubuntu3/huxiaoqian/data/20140724/20140724/', name='master_timeline_weibo',schema_version='5')
# import和初始化, 请使用下面的用法
# from xapian_weibo.xapian_backend import XapianSearch
# s = XapianSearch(path='/opt/xapian_weibo/data/', name='master_timeline_weibo')
# 查询条件有user(id),text,topic,timestamp,reposts_count,comments_count,attitudes_count(从timestamp开始后面四个查询指标可以指定范围和排序)
# 返回字段基本和新浪api的返回字段相同，注意没有created_at，而是timestamp
# 值得注意的是新增返回字段terms，返回的是每条微博里的词和以及词频的dict（字典），所有不用自己取出来之后再分词
# 若fields参数不指定，或者为None,则返回所有字段，除terms之外
# 如果需要返回terms，请一一指定需要的字段，并包括terms
# 简单示例如下
'''
count, get_results = s.search(query={'text': [u'男士']}, sort_by=['-timestamp'], fields=['text', 'timestamp', 'user', 'terms', '_id'])
print 'query1:'
#根据text查询
if count!=0:
for r in get_results():
print "** " * 10
def save_weibos(excel_name, topic, child_topic_list,
w_limit): # 这里需要根据文本内容查询相关微博id等
data = xlrd.open_workbook(excel_name)
weibos_dict = {}
for i in child_topic_list:
#if i == '0':
# continue
weibos_dict[i] = []
table_weibos = data.sheet_by_name(str(int(i)))
n_row_weibos = table_weibos.nrows
if n_row_weibos <= w_limit:
n_rows = n_row_weibo
else:
n_rows = w_limit # 考虑到数据已经根据权重从大到小排列
for j in range(n_rows):
line = table_weibos.row_values(j) # 缺少根据文本查询微博文本对应的其他微博内容
weibo_text = line[1]
weibo_weight = line[0]
try:
weibos_dict[i].append(
(weibo_text, weibo_weight
)) # 实际上这里append的应该是weibo的完整内容，并且是将username等获取到的
except:
weibos_dict[i] = [(weibo_text, weibo_weight)]
#print 'weibos_dict:', weibos_dict
#获取微博具体数据，仅作测试用
s = XapianSearch(path='/home/ubuntu3/huxiaoqian/case/20140724/20140804/',
name='master_timeline_weibo',
schema_version='5')
begin_ts = 1378050300
end_ts = 1378051200
query_dict = {
'timestamp': {
'$gt': begin_ts,
'$lt': end_ts
},
'message_type': 2
}
weibos_dict_new = {}
scount, weibo_results = s.search(query=query_dict, fields=fields_list)
#print 'scount:', scount
i = 0
j = 0
for weibo in weibo_results():
if i == 11:
break
weibo['text'] = weibos_dict[str(i)][j][0]
#获取username，profileimage,weibourl
username, profileimage = getuserinfo(weibo['user'])
weibo['username'] = username
weibo['profile_image_url'] = profileimage
weibo['timestamp'] = ts2date(weibo['timestamp'])
weibo['weibo_link'] = weiboinfo2url(weibo['user'], weibo['_id'])
#获取username， profileimage,weibourl结束
weight = weibos_dict[str(i)][j][1]
try:
weibos_dict_new[i].append((weibo, weight))
except:
weibos_dict_new[i] = [(weibo, weight)]
if j == 4:
j = 0
i += 1
else:
j += 1
#分割线
for i in range(len(child_topic_list)):
item = OpinionTestWeibos(topic, i, json.dumps(weibos_dict_new[i]))
item_exist = db.session.query(OpinionTestWeibos).filter(OpinionTestWeibos.topic==topic, \
OpinionTestWeibos.child_topic==i).first()
if item_exist:
db.session.delete(item_exist)
db.session.add(item)
db.session.commit()
# -*- coding:utf-8 -*-
import sys
import time
import datetime
sys.path.append('../xapian_case')
from xapian_case.xapian_backend import XapianSearch
from xapian_case.utils import top_keywords, not_low_freq_keywords, gen_mset_iter
# 默认schema_version为2
s = XapianSearch(path='/home/ubuntu3/huxiaoqian/case/20140724/20140724/', name='master_timeline_weibo',schema_version='5')
#uesr
'''
count, get_results = s.search(query={'user': 1811093512}, fields=['text', 'timestamp', 'user', 'terms', '_id'])
print 'query1:'
if count!=0:
for r in get_results():
print "** " * 10
print r['_id']
print r['user']
print r['text']
print r['timestamp']
print r['terms']
print 'hits: %s' % count
else:
print 'no results'
'''
get_results = s.iter_all_docs(fields=['_id', 'user', 'retweeted_uid', 'retweeted_mid', 'text', 'timestamp', 'reposts_count', 'source', 'bmiddle_pic', 'geo', 'attitudes_count', 'comments_count', 'sentiment', 'topics', 'message_type', 'terms' ])
for r in get_results:
