def acquire_topic_id(name, start_ts, end_ts, module="identify"):
item = db.session.query(TopicStatus).filter_by(topic=name,
start=start_ts,
end=end_ts,
module=module).first()
if not item: # 若item不存在TopicStatus说明是新插入的，进行插入-----完成通过前端用户提交的要计算的topic数据
item = TopicStatus(module, -1, topic, start_ts, end_ts,
int(time.time()))
db.session.add(item)
db.session.commit()
return item.id
def _update_topic_status2Completed(topic, start, end, db_date, module='identify'): # 更新：正在计算>>已完成计算
item = TopicStatus(module, COMPLETED_STATUS, topic, start, end, db_date)
item_exist = db.session.query(TopicStatus).filter(TopicStatus.module==module, \
TopicStatus.status==IN_CALC_STATUS, \
TopicStatus.topic==topic, \
TopicStatus.start==start, \
TopicStatus.end==end, \
TopicStatus.db_date==db_date).first()
if item_exist:
db.session.delete(item_exist)
db.session.add(item)
db.session.commit()
start_ts = datetime2ts(NEWS_START_TS)
end_ts = datetime2ts(NEWS_END_TS)
# deal with the start_ts/end_ts is not the whole day
if start_ts - datetime2ts(ts2datetime(start_ts)) != 0:
start_ts = datetime2ts(ts2datetime(start_ts))
if end_ts - datetime2ts(ts2datetime(end_ts)) != 0:
end_ts = datetime2ts(ts2datetime(end_ts)) + 3600 * 24
print 'start_ts, end_ts:', start_ts, end_ts
db_date = int(time.time())
# 创建topics中得话题
'''
save_t = Topics(topic, start_ts, end_ts)
save_t_exist = db.session.query(Topics).filter(Topics.topic==topic ,\
Topics.start_ts==start_ts ,\
Topics.end_ts==end_ts).first()
if save_t_exist:
db.session.delete(save_t_exist)
db.session.add(save_t)
db.session.commit()
'''
save_t_s = TopicStatus(module, status, topic, start_ts, end_ts, db_date)
save_t_s_exist = db.session.query(TopicStatus).filter(TopicStatus.module==module, \
TopicStatus.start==start_ts, \
TopicStatus.end==end_ts).first()
if save_t_s_exist:
db.session.delete(save_t_s_exist)
db.session.add(save_t_s)
db.session.commit()
main(topic, start_ts, end_ts)
quota_coverage(topic, xapian_search_weibo, start_ts=start, end_ts=end) # 覆盖度计算
print 'save coverage success'
quota_person_sensitivity(topic, xapian_search_weibo, start_ts=start, end_ts=end) # 敏感人物参与度
print 'save person_sensitivity success'
# 考虑怎么把使用数据相似性很高的合并在一起，减少检索的次数
def worker(topic, start, end):
print 'topic: ', topic.encode('utf8'), 'start:', start, 'end:', end
cal_topic_quotasystem_count_by_date(topic, start, end)
if __name__=='__main__':
module = 'quota_sysytem'
status = -1
topic = u'东盟,博览会'
start = datetime2ts('2013-09-02')
end = datetime2ts('2013-09-05') + Day
db_date = int(time.time()) # 入库时间
save_item = TopicStatus(module, status, topic, start, end, db_date)
db.session.add(save_item)
db.session.commit()
attention_exp = {'folk':100, 'media':100, 'other':100, 'opinion_leader':100, 'oversea':100} # 此处仅对经验值进行初始化，需要管理员根据具体情况进行修改
duration_exp = 5 * Day
coverage_exp = 3000
save_exp(topic, start, end, attention_exp, duration_exp, coverage_exp) # 给关注度经验值和持续度经验值默认值
save_sensitivity(topic, start, end) # 给类型敏感词表、词汇敏感词表、地点敏感词表进行初始化----三张表中均为每个话题一条记录
print 'start_worker'
worker(topic, start, end)
ComputeIndex(topic, start, end)
if __name__ == '__main__':
#module_t_s = 'identify'
status = -1
#topic = u'高校思想宣传'
#start = datetime2ts('2015-01-23')
#end = datetime2ts('2015-01-31') + Day
module_t_s = MODULE_T_S
topic = TOPIC
start = datetime2ts(START)
end = datetime2ts(END)
save_topics = Topics(topic, start, end)
save_topics_exist = db.session.query(Topics).filter(Topics.topic==topic ,\
Topics.start_ts==start ,\
Topics.end_ts==end).first()
if save_topics_exist:
db.session.delete(save_topics_exist)
db.session.add(save_topics)
db.session.commit()
db_date = int(time.time())
save_t_s = TopicStatus(module_t_s, status, topic, start, end, db_date)
save_t_s_exist = db.session.query(TopicStatus).filter(TopicStatus.module==module_t_s, TopicStatus.topic==topic ,\
TopicStatus.start==start, TopicStatus.end==end).first()
if save_t_s_exist:
db.session.delete(save_t_s_exist)
db.session.add(save_t_s)
db.session.commit()
main(topic, start, end)