UserProfile.py

#!/usr/bin/python
#-*-coding:utf-8-*-
'''@author:duncan'''
import config
import time
from MySQLInteraction import TwitterWithMysql as mysql
from MongoDBInteraction import TweetsWithMongo as mongo
from DocumentClassify import TweetsClassify
from UserInterestExtract import ExtractTargetUserInterest
from UserInfluenceAnalysis import UserInfluNoPageRank
from SentimentModule import SentimentWithTime
from XMLInteraction import GenerateXML as xml
################################################################
'''
对外接口
'''
################################################################
# 统一从mongo中获取用户信息
def GetUserInfo(userid):
    '''

    :param userid: 用户的userid
    :return: 返回TwitterUser类对象
    '''
    if mongo.CheckUser(userid) == False:
        print "数据库中不存在该用户"
        return None
    user = mysql.getUserInfo(userid)
    return user


# 获取用户推文文本
def GetUserTweets(userid):
    '''

    :param userid: 用户的userid
    :return: 返回近期的推文文本,没有推文则为None
    '''
    tweets = mongo.getUserTweets(userid)
    if tweets == "":
        print "mongodb中没有该用户的推文"
        return None
    return tweets

# 推断用户的领域类别
def GetUserCategory(userid):
    '''

    :param userid: 用户的userid
    :return: 返回用户的分类类别
    '''
    tweets = GetUserTweets(userid)
    if tweets != None:
        category = TweetsClassify.Classify(tweets,config.mnb)
        return category
    else:
        return None

# 从推文和description中得到用户的兴趣标签
def GetUserInterestTags(userid):
    '''

    :param userid: 用户的userid
    :return: 返回用户的兴趣标签
    '''
    interests = ExtractTargetUserInterest.GenerateInterestsWithTF(userid)
    return interests

# 获取用户的活跃度,影响力度分数,影响力分数,影响力等级
def GetUserInfluence(userid):
    '''

    :param userid: 用户的userid
    :return: 返回四个结果,activity,influence,influenceScore,rank_influence(influence是计算influenceScore的中间结果)
    '''
    influence_score,active,influ,rank = UserInfluNoPageRank.CalucateUserInfluence(userid)
    rank = config.rank_influence[rank]
    return influence_score,active,influ,rank

# 获取用户的心理状态
def GetUserPsychology(userid):
    '''

    :param userid: 用户的userid
    :return: 返回三个结果:最新推文的起始时间,以设定的时间间隔的心理状态序列,近期的心理状态结果
    '''
    tweets = mongo.getTweets(userid)
    starttime,psychological,psy = SentimentWithTime.SentimentWithTime(tweets)
    psy = config.psychological[psy]
    return starttime,psychological,psy

# 根据用户的userid,从mysql和mongo数据库中获取信息构建人物画像
def UserProfileFromDB(userid):
    start_time = time.time()
    if mysql.checkUser(userid) == False:
        print "数据库中不存在该用户"
        return
    user = mysql.getUserInfo(userid)
    # 获取用户推文文本
    tweets = mongo.getUserTweets(userid)
    if tweets == "":
        print "mongodb中没有该用户的推文"
        return
    print "已获取推文"

    # 获取人物所属领域
    category = GetUserCategory(userid)
    user.category = category
    print "人物所属领域:%s" %  category

    # 获取人物兴趣爱好标签,两种方式
    # interests = ExtractTargetUserInterest.GenerateInterestsWithFollowers(userid)
    interests = GetUserInterestTags(userid)
    user.interest_tags = interests
    print "人物兴趣爱好标签:%s" % interests

    # 获取人物影响力分数及等级
    # rank为{1,2,3}集合中的某一元素
    influence_score,active,influ,rank = GetUserInfluence(userid)
    user.influenceScore = influence_score
    print "人物活跃度分数:%f,影响力度分数:%f,影响力分数:%f,影响力等级:%s" % (active,influ,influence_score,rank)

    # 获取人物心理状态,返回结果为最近一条推文起始时间,从起始时间向前一段时间内的心理状态序列以及近期心理状态结果,psy为{1,-1,0}
    # 后面后可以跟参数period,设置时间段的长度,单位为月
    starttime,psychological,psy = GetUserPsychology(userid)
    user.psy_tweets_starttime = starttime
    user.psy = psy
    user.psy_seq = psychological
    # psy从整形转为字符串型
    psy = config.psychological[psy]
    print "人物近期心理状态:%s" % psy

    # 生成XML文档
    xml.GenerateUserXml(user)

    end_time = time.time()
    print "用时:%f" % (end_time - start_time)

# 在抓取过程中对人物构建人物画像
def UserProfileFromDic(userinfo):
    '''

    :param userinfo: userinfo是一个字典形式的变量,包含用户基本信息和推文信息
    :return: 返回字典形式的用户基本信息和隐性属性信息
    '''
    # 得到分类
    tweets = userinfo['tweets']
    text = ""
    for tweet in tweets:
        text += tweet['text']
    category = TweetsClassify.Classify(tweets,config.mnb)
    userinfo['category'] = category

    #　得到兴趣爱好标签
    description = userinfo['description']
    interest_tags = ExtractTargetUserInterest.GenerateInterestsWithTFFromTweets(text,description)
    userinfo['interest_tags'] = interest_tags

    # 得到用户的社交总影响力,活跃度,推文影响力,影响力等级
    score,d_active,d_influ,rank = UserInfluNoPageRank.GetUserInfluence(userinfo['followers_count'],tweets)
    userinfo['influenceScore'] = score
    userinfo['activity'] = d_active
    rank = config.rank_influence[rank]
    userinfo['rank_influ'] = rank

    # 得到用户的心理状态,间隔默认为1个月
    starttime,psychologic,res = SentimentWithTime.SentimentWithTime(tweets,period=1)
    userinfo['psy_tweets_starttime'] = starttime
    userinfo['psy_seq'] = psychologic
    userinfo['psy'] = config.psychological[res]

    return userinfo
# print GetUserInfo("10047382")