robotIdentification/text_analysis/bak/views.py_0226

# 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
from django.views.decorators.csrf import csrf_exempt
from log_util.set_logger import set_logger
from text_analysis.tools.tool import parse_data
logging = set_logger('logs/results.log')
import traceback
import queue
import requests
import time
from datetime import datetime
import os
import joblib
from text_analysis.cusException import userFile_Exception, postFile_Exception

# 任务队列
global task_queue
task_queue = queue.Queue()

#mysql连接池
from text_analysis.tools.db_pool import get_conn_pool

@csrf_exempt
def robotIdentification(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 predict(user_file_result,post_file_result,task):
    try:
        # raw_data = {"user_file": {"accountId": "39234393", "accountName": "hello", "nickName": "Johnson Leung",
        #                           "fansCount": 308, "likeCount": 92707, "postCount": 14237,
        #                           "otherInfo": "{\"\"otherInfo\"\":\"\"{\"\"bio\"\": \"\"Huge}",
        #                           "authentication": 0},
        #             "post_file": {"count": 1, "LikeCount": 12, "CommentsCount": 1, "ShareCount": 1,
        #                           "length": 150, "tags": 0, "https": 0, "at": 0, "diffdate": 1}}
        # 用户数据
        res = {"successCode": "1", "errorLog": "", "results": {}}
        user_data = []
        # 返回值需要的三个字段
        accountId = ""
        nickName = ""
        accountName = ""
        data = {}
        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
        # 识别结果返回值
        recognition_code = "0"
        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_fansCount_3 = int(data["user_file"]["fansCount"])
        except:
            user_data_fansCount_3 = 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_fansCount_3, user_data_likeCount_4,
             user_data_postCount_5, user_data_authentication_6])
        # 帖子数据
        if data["post_file"] == {}:
            recognition_code = "-1"
        else:
            post_data = []
            try:
                post_data_count_1 = int(data["post_file"]["count"])
            except:
                post_data_count_1 = 0
            try:
                post_data_LikeCount_2 = int(data["post_file"]["LikeCount"])
            except:
                post_data_LikeCount_2 = 0
            try:
                post_data_CommentsCount_3 = int(data["post_file"]["CommentsCount"])
            except:
                post_data_CommentsCount_3 = 0
            try:
                post_data_ShareCount_4 = int(data["post_file"]["ShareCount"])
            except:
                post_data_ShareCount_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_at_8 = int(data["post_file"]["at"])
            except:
                post_data_at_8 = 0
            try:
                post_data_diffdate_9 = int(data["post_file"]["diffdate"])
            except:
                post_data_diffdate_9 = 0
            post_data.extend(
                [post_data_count_1, post_data_LikeCount_2, post_data_CommentsCount_3, post_data_ShareCount_4,
                 post_data_length_5, post_data_tags_6, post_data_https_7, post_data_at_8, post_data_diffdate_9])
            features = [user_data + post_data]
            bot_user = joblib.load(cur_dir + "/model/bot_user.pkl")  # 加载训练好的模型
            result = bot_user.predict(features)
            recognition_code = str(result[0])
        # logging.info("预测模型结果为{}".format(result))
        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:
        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):
    '''
    水军识别数据构造
    主要是写入用户表、主贴表
    '''
    #获取数据库连接
    sqlhelper = get_conn_pool(dbConfig['host'],dbConfig['port'],dbConfig['username'],dbConfig['password'],dbConfig['db'])
    #用户任务作为响应体
    send_task = None
    while True:
        if task_queue.qsize() > 0:
            try:
                logging.info("队列长度：{}".format(task_queue.qsize()))
                task = task_queue.get()
                input = task['input']
                account = input['account']
                post = input['post']
                #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")
                logging.info("数据类型：{}".format(page_type))
                if page_type == 'userInfoPage':
                    # 用户任务作为响应体
                    send_task = task
                    #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
                    # 定义 SQL 语句
                    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)
                #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.queryOne(sql)
                    # 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 ='{}'".format(taskId)
                    post_file_result = sqlhelper.queryOne(sql)
                    if send_task == None:
                        send_task = task
                    predict(user_file_result,post_file_result,send_task)
                    #结束置空
                    send_task = None
            except Exception as e:
                traceback.print_exc()
        else:
            # 暂无任务，进入休眠
            time.sleep(10)
if __name__ == '__main__':
    all_result = {
        "9_获取用户发帖信息": "{\"resultList\": [{\"count\": \"10\", \"LikeCount\": \"1\", \"CommentsCount\": \"0.1\", \"ShareCount\": \"0.4\", \"length\": \"241.8000\", \"tags\": \"5.80000000\", \"https\": \"1.20000000\", \"at\": \"0.40000000\", \"diffdate\": \"170269\"}]}",
        "8_获取用户信息": "{\"resultList\": [{\"accountId\": \"1368232444323799043\", \"accountName\": \"Ujjal best Tech@UjjalKumarGho19\", \"nickName\": \"UjjalKumarGho19\", \"fansCount\": \"660\", \"likeCount\": \"2096\", \"postCount\": \"579\", \"otherInfo\": \"\", \"authentication\": 1}]}"}
    data = {}
    # {"user_file": "9_获取用户信息", "post_file": "10_获取用户发帖信息"}
    user_file_result = json.loads(all_result[data['user_file']])
    post_file_result = json.loads(all_result[data['post_file']])
    if user_file_result['resultList']:
        resultList = user_file_result['resultList']
        data['user_file'] = resultList[0]
    else:
        data['user_file'] = {}
    if post_file_result['resultList']:
        data['post_file'] = post_file_result['resultList'][0]
    else:
        data['post_file'] = {}

    print(data)