robotIdentificationTopic/text_analysis/bak/views.py_0304

#coding:utf8
import os, sys
import io
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf8')
cur_dir = os.path.dirname(os.path.abspath(__file__)) or os.getcwd()
par_dir = os.path.abspath(os.path.join(cur_dir, os.path.pardir))
sys.path.append(cur_dir)
sys.path.append(par_dir)
import json
from django.http import HttpResponse
from text_analysis.tools import to_kafka,tool
from django.views.decorators.csrf import csrf_exempt
from log_util.set_logger import set_logger
logging=set_logger('logs/results.log')
import traceback
import queue
import requests
import time
from datetime import datetime, timedelta
from text_analysis.cusException import userFile_Exception,postFile_Exception,replyFile_Exception
from text_analysis.tools.tool import parse_data
import os
import joblib
from text_analysis.tools.db_pool import get_conn_pool
#任务队列
global task_queue
task_queue = queue.Queue()
global replyGraph
replyGraph={}

@csrf_exempt
def robotIdentificationTopic(request):
    if request.method == 'POST':
        try:
            raw_data = json.loads(request.body)
            task_queue.put(raw_data)
            return HttpResponse(json.dumps({"code": 1, "msg": "请求正常！"}, ensure_ascii=False))
        except:
            logging.error(traceback.format_exc())
            return HttpResponse(json.dumps({"code": 0, "msg": "请求json格式不正确！"}, ensure_ascii=False))
    else:
        return HttpResponse(json.dumps({"code": 0, "msg": "请求方式错误，改为post请求"}, ensure_ascii=False))
    
def predictTopic(user_file_result,post_file_result,task,dbConfig,taskId):
    try:
        # 识别结果返回值
        recognition_code = "0"
        # 用户数据
        res = {"successCode": "1", "errorLog": "", "results": {}}
        # 获取历史数据源
        all_result = task['data']
        user_data = []
        data={}
        #返回值需要的三个字段
        accountId=""
        nickName=""
        accountName=""
        # {"user_file": "9_获取用户信息", "post_file": "10_获取用户发帖信息"}
        if user_file_result:
            data['user_file'] = user_file_result
            logging.info('用户数据：{}'.format(data['user_file']))
            accountId = data["user_file"]["accountId"]
            nickName = data["user_file"]["nickName"]
            accountName = data["user_file"]["accountName"]
        else:
            data['user_file'] ={}
            raise userFile_Exception
        if post_file_result:
            data['post_file'] = post_file_result
            logging.info('帖子数据：{}'.format(data['post_file']))
        else:
            data['post_file'] = {}
            raise postFile_Exception
        try:
            user_data_otherInfo_1 = 0 if data["user_file"]["otherInfo"].strip() == "" else 1
        except:
            user_data_otherInfo_1 = 0
        try:
            user_data_nickName_2 = 0 if data["user_file"]["nickName"].strip() == "" else 1
        except:
            user_data_nickName_2 = 0
        try:
            user_data_likeCount_4 = int(data["user_file"]["likeCount"])
        except:
            user_data_likeCount_4 = 0
        try:
            user_data_postCount_5 = int(data["user_file"]["postCount"])
        except:
            user_data_postCount_5 = 0
        try:
            user_data_authentication_6 = int(data["user_file"]["authentication"])
        except:
            user_data_authentication_6 = 0
        user_data.extend(
            [user_data_otherInfo_1, user_data_nickName_2, user_data_likeCount_4,user_data_postCount_5, user_data_authentication_6])
        logging.info("用户数据处理完毕！-{}".format(user_data))
        # 帖子数据
        post_data = []
        if data["post_file"]=={}:
            post_data=[0,0,0,0,0,0,0,0]
        else:
            try:
                post_data_LikeCount_1 = int(data["post_file"]["LikeCount"])
            except:
                post_data_LikeCount_1 = 0
            try:
                post_data_ShareCount_2 = int(data["post_file"]["ShareCount"])
            except:
                post_data_ShareCount_2 = 0
            try:
                post_data_emotionCount_3 = int(data["post_file"]["emotionCount"])
            except:
                post_data_emotionCount_3 = 0
            try:
                post_data_CommentsCount_4 = int(data["post_file"]["CommentsCount"])
            except:
                post_data_CommentsCount_4 = 0
            try:
                post_data_length_5 = int(data["post_file"]["length"])
            except:
                post_data_length_5 = 0
            try:
                post_data_tags_6 = int(data["post_file"]["tags"])
            except:
                post_data_tags_6 = 0
            try:
                post_data_https_7 = int(data["post_file"]["https"])
            except:
                post_data_https_7 = 0
            try:
                post_data_diffdate_8 = int(data["post_file"]["diffdate"])
            except:
                post_data_diffdate_8 = 0
            post_data.extend(
                [post_data_LikeCount_1, post_data_ShareCount_2, post_data_emotionCount_3, post_data_CommentsCount_4,
                 post_data_length_5, post_data_tags_6, post_data_https_7, post_data_diffdate_8])
        logging.info("帖子数据处理完毕！-{}".format(post_data))
        #关系数据
        reply_data_1 = [0, 0, 0, 0, 0]
        reply_data_2 = [0, 0]
        try:
            #先判断内存中是否有该专题图信息
            topicID=taskId
            if topicID not in list(replyGraph.keys()):
                reply_file=tool.mysqlData(dbConfig,topicID,logging)
                if reply_file:
                    graph=tool.get_replyData(reply_file)
                    replyGraph[topicID]=graph
                else:
                    raise replyFile_Exception
            else:
                graph=replyGraph[topicID]
            userId=data["user_file"]["accountId"]
            if userId in list(graph.keys()):
                closeness_centrality=graph["userId"]["closeness_centrality"]
                pagerank=graph["userId"]["pagerank"]
                clustering=graph["userId"]["clustering"]
                in_degree=graph["userId"]["in_degree"]
                out_degree=graph["userId"]["out_degree"]
                reply_data_1=[closeness_centrality,pagerank,clustering,in_degree,out_degree]
                user_flag_infl=graph["userId"]["user_flag_infl"]
                user_flag_act=graph["userId"]["user_flag_act"]
                reply_data_2=[user_flag_infl,user_flag_act]
            replyGraph[topicID]["last_operation_time"]=datetime.now()
        except:
            logging.info("专题关系数据mysql获取失败！")
            logging.info(traceback.format_exc())
        logging.info("关系数据处理完毕！{}-{}".format(reply_data_1,reply_data_2))
        features = [user_data + reply_data_1 + post_data + reply_data_2]
        bot_user = joblib.load(cur_dir+"/model/bot_topic.pkl")  # 加载训练好的模型
        result = bot_user.predict(features)
        recognition_code = str(result[0])
        res["results"]=str(result[0])
        results = {}
        # 用户id
        results['authorId'] = accountId
        # 用户昵称
        results['nickName'] = nickName
        # 用户账号
        results['accountName'] = accountName
        # 结束标识
        res['isLast'] = True
        # 数据类型   --目前只提供给图谱使用
        results['pageType'] = 'userAuthenPage'
        if recognition_code == '0':
            results['recognitionResult'] = '非机器人'
            results['recognitionCode'] = recognition_code
        elif recognition_code == '1':
            results['recognitionResult'] = '机器人'
            results['recognitionCode'] = recognition_code
        else:
            results['recognitionResult'] = '未知识别结果'
            results['recognitionCode'] = recognition_code
        res['results'] = json.dumps(results)
        task["result"] = res
        logging.info("增加预测数据-{}".format(task))
        to_kafka.send_kafka(task, logging)
    except userFile_Exception:
        res = {"successCode": "0", "errorLog": "用户数据为空！", "results": {}}
        results={}
        results['authorId'] = ""
        results['nickName'] = ""
        results['accountName'] = ""
        results['recognitionResult'] = '用户数据为空'
        res['results'] = json.dumps(results)
        task["result"] = res
        logging.info("该条请求用户数据为空-{}".format(task))
        to_kafka.send_kafka(task, logging)
    except postFile_Exception:
        res = {"successCode": "0", "errorLog": "帖子数据为空！", "results": {}}
        results={}
        results['authorId'] = accountId
        results['nickName'] = nickName
        results['accountName'] = accountName
        results['recognitionResult'] = '帖子数据为空'
        res['results'] = json.dumps(results)
        task["result"] = res
        logging.info("该条请求帖子数据为空-{}".format(task))
        to_kafka.send_kafka(task, logging)
    except replyFile_Exception:
        res = {"successCode": "0", "errorLog": "发帖和评论关系数据为空！", "results": {}}
        results={}
        results['authorId'] = accountId
        results['nickName'] = nickName
        results['accountName'] = accountName
        results['recognitionResult'] = '发帖和评论关系数据为空'
        res['results'] = json.dumps(results)
        task["result"] = res
        logging.info("该条请求发帖和评论关系数据为空-{}".format(task))
        to_kafka.send_kafka(task, logging)

    except:
        res = {"successCode": "0", "errorLog": "", "results": {}}
        results = {}
        results['authorId'] = accountId
        results['nickName'] = nickName
        results['accountName'] = accountName
        results['recognitionResult'] = ""
        res['results'] = json.dumps(results)
        task["result"] = res
        task["result"]["error"] = traceback.format_exc()
        logging.info(traceback.format_exc())
        to_kafka.send_kafka(task, logging)
def data_structure(dbConfig):
    '''
    所需计算数据入库
    :param dbConfig: 数据库连接信息
    :return:
    '''
    # 获取数据库连接
    sqlhelper = get_conn_pool(dbConfig['host'], dbConfig['port'], dbConfig['username'], dbConfig['password'],dbConfig['db'])
    #用户任务结构体缓存
    user_tasks = {}
    while True:
        if task_queue.qsize() > 0:
            try:
                task = task_queue.get()
                input = task['input']
                account = input['account']
                post = input['post']
                reply = input['reply']

                #判断数据类型
                data = task['data']
                page_type = None
                taskId = None
                for data_str in data:
                    try:
                        app_data = json.loads(data[data_str])
                        taskId = app_data['taskId']
                        if "pageType" in app_data:
                            page_type = app_data['pageType']
                            break
                    except:
                        logging.error("正常判断，异常请忽略")
                if page_type == 'userInfoPage':
                    #用户添加到缓存
                    accountId = parse_data(task, account['accountId'])
                    user_tasks[accountId] = task
                    logging.info('成功添加用户缓存：{}'.format(accountId))
                    #用户类型数据写入
                    sql = "INSERT INTO `user_account`(`taskId`, `accountId`, `accountName`, `nickName`, `fansCount`, `likeCount`, `postCount`, `otherInfo`, `authentication`) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)"
                    # 构造参数元组
                    values = (
                        parse_data(task, account['taskId']),
                        parse_data(task, account['accountId']),
                        parse_data(task, account['accountName']),
                        parse_data(task, account['nickName']),
                        parse_data(task, account['fansCount']),
                        parse_data(task, account['likeCount']),
                        parse_data(task, account['postCount']),
                        parse_data(task, account['otherInfo']),
                        parse_data(task, account['authentication'])
                    )
                    sqlhelper.insert(sql,values)
                elif page_type == 'storyDetailPage':
                    #帖子类型数据写入
                    sql = "INSERT INTO `user_post`(`taskId`, `postId`, `accountId`, `accountName`, `likeCount`, `emotionCount`, `commentsCount`, `shareCount`, `content`, `pubTime`, `crawlTime`) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"
                    # 构造参数元组
                    values = (
                        parse_data(task, post['taskId']),
                        parse_data(task, post['postId']),
                        parse_data(task, post['accountId']),
                        parse_data(task, post['accountName']),
                        parse_data(task, post['likeCount']),
                        parse_data(task, post['emotionCount']),
                        parse_data(task, post['commentsCount']),
                        parse_data(task, post['shareCount']),
                        parse_data(task, post['content']),
                        parse_data(task, post['pubTime']),
                        parse_data(task, post['crawlTime'])
                    )
                    sqlhelper.insert(sql,values)
                elif page_type == 'socialComment':
                    #评论类型数据写入
                    sql = "INSERT INTO `reply`(`taskId`, `ReviewerAccountId`, `ReviewerAccountName`, `postId`, `ShareCount`, `LikeCount`, `CommentCount`, `CommentTime`) VALUES (%s, %s, %s, %s, %s, %s, %s, %s)"
                    # 构造参数元组
                    values = (
                        parse_data(task, reply['taskId']),
                        parse_data(task, reply['reviewerAccountId']),
                        parse_data(task, reply['reviewerAccountName']),
                        parse_data(task, reply['postId']),
                        parse_data(task, reply['shareCount']),
                        parse_data(task, reply['likeCount']),
                        parse_data(task, reply['commentsCount']),
                        parse_data(task, reply['commentTime'])
                    )
                    sqlhelper.insert(sql,values)
                #判断是否是此次数据流的最后一条，最后一条直接触发用户的水军识别算法
                if 'isLast'in data and data['isLast']:
                    #获取用户相关的数据
                    sql = "select accountId,accountName,nickName,fansCount,likeCount,postCount,otherInfo,authentication from user_account where taskId ='{}'".format(taskId)
                    user_file_result = sqlhelper.queryAll(sql)
                    if user_file_result:
                        for user in user_file_result:
                            try:
                                # 获取帖子相关的数据
                                sql = "SELECT CONVERT(COUNT(postId), CHAR(255)) AS count, CONVERT(AVG(likeCount), CHAR(255)) AS LikeCount, CONVERT(AVG(commentsCount), CHAR(255)) AS CommentsCount, CONVERT(AVG(shareCount), CHAR(255)) AS ShareCount, CONVERT(AVG(LENGTH(content)), CHAR(255)) AS length, CONVERT(AVG((LENGTH(content) - LENGTH(REPLACE(content, '#', ''))) / LENGTH('#')), CHAR(255)) AS tags, CONVERT(AVG((LENGTH(content) - LENGTH(REPLACE(content, 'https', ''))) / LENGTH('https')), CHAR(255)) AS https, CONVERT(AVG((LENGTH(content) - LENGTH(REPLACE(content, '@', ''))) / LENGTH('@')), CHAR(255)) AS at, CONVERT(MIN(TIMESTAMPDIFF(SECOND, pubTime, GREATEST(pubTime, crawlTime))), CHAR(255)) AS diffdate FROM user_post WHERE taskId = '{taskId}' and accountId = '{accountId}'".format(taskId=taskId,accountId=user['accountId'])
                                post_file_result = sqlhelper.queryOne(sql)
                                send_task = user_tasks[user['accountId']]
                                predictTopic(user,post_file_result,send_task,dbConfig,taskId)
                            except Exception as e:
                                traceback.print_exc()
                                logging.error("用户id：{}".format(user['accountId']))
                                logging.error("用户缓存加载失败：{}".format(send_task))
                        else:
                            #清空用户任务缓存
                            user_tasks.clear()
            except Exception as e:
                traceback.print_exc()
        else:
            # 暂无任务，进入休眠
            time.sleep(10)
def replyGraphThread():
    '''
    判断话题是否结束，如果2个小时未访问话题，则删除该话题的图信息。
    :return:
    '''
    while True:
        try:
            if replyGraph!={}:
                # 获取当前时间
                current_time = datetime.now()
                for topicID in list(replyGraph.keys()):
                    # 计算最后一次操作的时间与当前时间的差值
                    time_difference = current_time - replyGraph[topicID]['last_operation_time']
                    # 如果差值大于等于120分钟，则删除该话题图信息
                    if time_difference >= timedelta(minutes=120):
                        del replyGraph[topicID]
        except:
            logging.info(traceback.format_exc())
        finally:
            time.sleep(1800)