data_analyze_platform/LIB/FRONTEND/SaftyCenter/diagfault/deploy.py

__author__ = 'lmstack'
#coding=utf-8
import os
import datetime
import pandas as pd
from LIB.BACKEND import DBManager, Log
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
import time, datetime
import dateutil.relativedelta
import traceback
from LIB.MIDDLE.CellStateEstimation.Common import log
from pandas.core.frame import DataFrame
from LIB.MIDDLE.SaftyCenter.Common import QX_BatteryParam
from LIB.MIDDLE.SaftyCenter.diagfault.SC_SamplingSafty import SamplingSafty

from LIB.MIDDLE.CellStateEstimation.Common.V1_0_1 import DBDownload
from urllib import parse
import pymysql
import pdb
from apscheduler.schedulers.blocking import BlockingScheduler
import datacompy
from LIB.MIDDLE.SaftyCenter.Common import FeiShuData
from LIB.MIDDLE.SaftyCenter.Common import QX_BatteryParam
from LIB.MIDDLE.SaftyCenter.diagfault import  CBMSBatDiag
from LIB.MIDDLE.SaftyCenter.diagfault.SC_SamplingSafty import SamplingSafty

def fun():
    global df_sn
    global db_res_engine
    global logger
    global df_Diag_Ram
    # 读取结果数据库
    host2='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
    port2=3306
    db2='safety_platform'
    user2='qx_read'
    password2='Qx@123456'
    start=time.time()
    end_time=datetime.datetime.now()
    start_time=end_time-datetime.timedelta(seconds=120)
    start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
    end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
    logger.info("cycle start !!!!!!!!!!!!!!!!!!!!")
    
    start=time.time()
    end_time=datetime.datetime.now()
    start_time=end_time-datetime.timedelta(seconds=130)
    start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
    end_time=end_time.strftime('%Y-%m-%d %H:%M:%S')
    df_read_Yunw = FeiShuData.getFeiShuDATA()#运维表格数据
    df_read_Yunw.rename(columns={'电池编码':'product_id'},inplace=True)
    df_read_Yunw.rename(columns={'内容描述':'info'},inplace=True)
    df_read_Yunw.rename(columns={'发生时间':'start_time'},inplace=True)
    df_read_Yunw.rename(columns={'维修信息':'advice'},inplace=True)

    for i in range(0, len(df_sn)):
        try:
            if df_sn.loc[i, 'imei'][5:9] == 'N640':
                celltype=1 #6040三元电芯
            elif df_sn.loc[i, 'imei'][5:9] == 'N440':
                celltype=2 #4840三元电芯
            elif df_sn.loc[i, 'imei'][5:9] == 'L660':
                celltype=99 # 6060锂电芯
            elif df_sn.loc[i, 'imei'][3:5] == 'LX' and df_sn.loc[i, 'imei'][5:9] == 'N750':    
                celltype=3 #力信 50ah三元电芯
            elif df_sn.loc[i, 'imei'][3:5] == 'CL' and df_sn.loc[i, 'imei'][5:9] == 'N750': 
                celltype=4 #CATL 50ah三元电芯
            elif df_sn.loc[i, 'imei'][5:9] == 'L420':
                celltype=101    #20ah磷酸铁锂电芯
            elif df_sn.loc[i, 'imei'][5:9] == 'L264':
                celltype=102    #120ah磷酸铁锂电芯
            else:
                logger.info("pid-{} celltype-{} SN: {} SKIP!".format(os.getpid(), "未知", sn))
                continue
            sn = df_sn.loc[i, 'sn']
            
            logger.info("pid-{} celltype-{} SN: {} START!".format(os.getpid(), celltype, sn))
                
                
            param=QX_BatteryParam.BatteryInfo(celltype)   
            #读取原始数据库数据........................................................................................................................................................
            dbManager = DBManager.DBManager()
            df_data = dbManager.get_data(sn=sn, start_time=start_time, end_time=end_time, data_groups=['bms'])
            df_bms = df_data['bms']

            #读取结果数据库数据........................................................................................................................................................
            host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
            port=3306
            db='qx_cas'
            user='qx_read'
            password='Qx@123456'
            mode=1
            tablename1='cellstateestimation_soh'
            tablename2='cellstateestimation_uniform_socvoltdiff'       
            #电池诊断................................................................................................................................................................
            DBRead=DBDownload.DBDownload(host, port, db, user, password,mode)
            with DBRead as DBRead:
                df_soh=DBRead.getdata('time_st,sn,soh,cellsoh', tablename=tablename1, sn=sn, timename='time_sp', st=start_time, sp=end_time)
                df_uniform=DBRead.getdata('time,sn,cellsoc_diff,cellmin_num,cellmax_num', tablename=tablename2, sn=sn, timename='time', st=start_time, sp=end_time)

            #电池诊断................................................................................................................................................................
            CellFltInfo=DataFrame(columns=['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice'])
            df_Diag_Ram = df_Diag_Ram.drop_duplicates(subset=['product_id','code','start_time','Batpos','info'],keep='first')#sn之外的故障
            df_Diag_Ram_sn = df_Diag_Ram.loc[df_Diag_Ram['product_id']==sn]#历史故障
            df_Diag_Ram_sn_else = pd.concat([df_Diag_Ram,df_Diag_Ram_sn,df_Diag_Ram_sn]).drop_duplicates(subset=['product_id','code','start_time','Batpos','info'],keep=False)#sn之外的故障
            CellFltInfo = df_Diag_Ram_sn.drop('Batpos',axis=1)
            df_Diag_Ram_add = pd.DataFrame()
            df_Diag_Ram_Update_change = pd.DataFrame()
            if not df_bms.empty:
                df_Diag_Batdiag_update_xq=SamplingSafty.main(sn,param,df_bms,CellFltInfo)#学琦计算故障   
                BatDiag=CBMSBatDiag.BatDiag(sn,celltype,df_bms, df_soh, df_uniform, CellFltInfo)#鹏飞计算
                df_Diag_Batdiag_update=BatDiag.diag() 
                df_Diag_Cal_Update_add = pd.concat([df_Diag_Batdiag_update_xq,df_Diag_Batdiag_update])#重新计算的该SN下的故障
                df_Diag_Cal_Update_temp = df_Diag_Cal_Update_add.drop_duplicates(subset=['product_id','start_time','end_time','code','info'], keep='first', inplace=False, ignore_index=False)#去除相同故障
                df_Diag_cal_early_unfix = pd.DataFrame()
                df_Diag_Cal_finish = pd.DataFrame()
                df_Diag_cal_early_fix = pd.DataFrame()
                if not df_Diag_Cal_Update_temp.empty:
                    #------------------------------合并两者故障，并将同一sn号下的车辆故障放一起----------------------------------------------
                    df_Diag_Cal_Update = df_Diag_Cal_Update_temp#替换上一行
                    df_Diag_Cal_finish = df_Diag_Cal_Update.loc[df_Diag_Cal_Update['end_time'] != '0000-00-00 00:00:00']
                    df_Diag_Cal_new = df_Diag_Cal_Update.loc[df_Diag_Cal_Update['end_time'] == '0000-00-00 00:00:00']
                    df_Diag_Cal_finish['Batpos'] = 1
                    df_Diag_Cal_new['Batpos'] = 0
                    df_feishu_sta = df_read_Yunw.loc[(df_read_Yunw['product_id'] == sn)]#飞书中该sn车辆状态
                    if df_feishu_sta.empty:#飞书中没有该sn记录故障的新增
                        df_Diag_cal_early_unfix = df_Diag_Cal_new#如果为新出故障，则直接记录在df_diag_frame中
                    else:
                        df_Diag_cal_later = df_Diag_Cal_new.loc[pd.to_datetime(df_Diag_Cal_new['start_time']) > max(pd.to_datetime(df_feishu_sta['start_time']))]#故障表中故障时间晚于飞书记录时间的新增
                        df_Diag_cal_early = pd.concat([df_Diag_Cal_new,df_Diag_cal_later,df_Diag_cal_later]).drop_duplicates(subset=['product_id','code','start_time'],keep=False)#故障表中故障时间早于飞书记录时间
                        df_feishu_sta_latest = df_feishu_sta.loc[pd.to_datetime(df_feishu_sta['start_time']) == max(pd.to_datetime(df_feishu_sta['start_time']))]#飞书中该SN下的最新故障
                        df_feishu_diag_unfix = (df_feishu_sta_latest['advice'] == '需正常返仓') | (df_feishu_sta_latest['advice'] == '需紧急返仓')
                        if any(df_feishu_diag_unfix):
                            df_Diag_cal_early_unfix = df_Diag_Cal_new
                        else:
                            df_Diag_cal_early_fix = df_Diag_cal_early
                            df_Diag_cal_early_unfix = df_Diag_cal_later
                    if not df_Diag_cal_early_fix.empty:
                        df_Diag_cal_early_fix['Batpos'] = 1
                df_Diag_Ram_Update = pd.concat([df_Diag_cal_early_unfix,df_Diag_cal_early_fix,df_Diag_Cal_finish])
                df_Diag_Ram_Update['start_time'] = pd.to_datetime(df_Diag_Ram_Update['start_time'])
                df_Diag_Ram_Update.sort_values(by = ['start_time'], axis = 0, ascending=True,inplace=True)#该sn下当次诊断的故障状态
                df_Diag_Ram_add = pd.concat([df_Diag_Ram_Update,df_Diag_Ram_sn,df_Diag_Ram_sn]).drop_duplicates(subset=['start_time','code'],keep=False)#此次判断中新增故障
                df_Diag_Ram_Update_old = pd.concat([df_Diag_Ram_Update,df_Diag_Ram_add,df_Diag_Ram_add]).drop_duplicates(subset=['start_time','code'],keep=False)#此次判断中新增故障
                df_Diag_Ram_Update_change = pd.concat([df_Diag_Ram_Update_old,df_Diag_Ram_sn,df_Diag_Ram_sn]).drop_duplicates(subset=['start_time','code','Batpos'],keep=False)#此次判断中新增故障
                df_Diag_Ram_sav = df_Diag_Ram_Update.loc[df_Diag_Ram_Update['Batpos'] == 0]
                df_Diag_Ram = pd.concat([df_Diag_Ram_sn_else,df_Diag_Ram_sav])

            # if (len(df_Diag_Ram_add) > 0) | (len(df_Diag_Ram_Update_change) > 0):#历史及现有故障
            #     df_Diag_Ram.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\01Screen_Problem\result.csv',index=False,encoding='GB18030')
            if len(df_Diag_Ram_add) > 0:#新增故障
                
                df_Diag_Ram_add.columns = ['start_time', 'end_time', 'product_id', 'code', 'level', 'info','advice', 'Batpos']
                df_Diag_Ram_add['factory'] = '骑享'
                df_Diag_Ram_add.to_sql("all_fault_info",con=db_res_engine, if_exists="append",index=False)
                # df_Diag_Ram_add.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\01Screen_Problem\result_add.csv',index=False,encoding='GB18030')
            if len(df_Diag_Ram_Update_change) > 0:#更改故障
                df_Diag_Ram_Update_change = df_Diag_Ram_Update_change.reset_index(drop=True)
                try:
                    conn = pymysql.connect(host=host2, port=port2, user=user2, password=password2, database=db2)
                    cursor = conn.cursor()
                    logger.info(df_Diag_Ram_Update_change)
                    for i in range(0,len(df_Diag_Ram_Update_change)):
                        sql = '''
                                    update all_fault_info set end_time='{}', Batpos={} where product_id='{}' and code={} and start_time='{}'
                                    '''.format(df_Diag_Ram_Update_change.loc[i,'end_time'], df_Diag_Ram_Update_change.loc[i, 'Batpos'],
                                               df_Diag_Ram_Update_change.loc[i,'product_id'], df_Diag_Ram_Update_change.loc[i,'code'], 
                                               df_Diag_Ram_Update_change.loc[i,'start_time'])
                        logger.info(sql)
                        cursor.execute(sql)
                        conn.commit()
                    conn.close();
                except:
                    logger.error(traceback.format_exc)
                    logger.error(u"{} ：{},{} 任务运行错误\n".format(sn,start_time,end_time), exc_info=True)
                    conn.close();
                # df_Diag_Ram_Update_change.to_csv(r'D:\Work\Code_write\data_analyze_platform\USER\01Screen_Problemm\result_change.csv',index=False,encoding='GB18030')
            end=time.time()
            logger.info("pid-{} celltype-{} SN: {} DONE!".format(os.getpid(), celltype, sn))
        except:
            logger.error(traceback.format_exc)
            logger.error(u"{} ：{},{} 任务运行错误\n".format(sn,start_time,end_time), exc_info=True)
    logger.info("cycle DONE !!!!!!!!!!!!!!!!!!!!")

if __name__ == "__main__":
    
    # 时间设置
    # now_time = datetime.datetime.now()
    # pre_time = now_time + dateutil.relativedelta.relativedelta(days=-1)# 前一日
    # end_time=datetime.datetime.strftime(now_time,"%Y-%m-%d 00:00:00")
    # start_time=datetime.datetime.strftime(pre_time,"%Y-%m-%d 00:00:00")
    
    history_run_flag = False # 历史数据运行标志
    

    # 更新sn列表
    host='rm-bp10j10qy42bzy0q7.mysql.rds.aliyuncs.com'
    port=3306
    db='qixiang_oss'
    user='qixiang_oss'
    password='Qixiang2021'
    conn = pymysql.connect(host=host, port=port, user=user, password=password, database=db)
    cursor = conn.cursor()
    cursor.execute("select sn, imei, add_time from app_device")
    res = cursor.fetchall()
    df_sn = pd.DataFrame(res, columns=['sn', 'imei', 'add_time'])
    df_sn = df_sn.reset_index(drop=True)
    conn.close();
    
    # 数据库配置
    host = 'rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
    port = 3306
    user = 'qx_cas'
    password = parse.quote_plus('Qx@123456')
    database = 'qx_cas'

    db_engine = create_engine(
        "mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8".format(
            user, password, host, port, database
        ))
    DbSession = sessionmaker(bind=db_engine)
    
    # 运行历史数据配置
    
    df_first_data_time = pd.read_sql("select * from bat_first_data_time", db_engine)

    
    # 日志配置
    now_str = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()).replace(":","_")
    log_path = 'log/' + now_str
    if not os.path.exists(log_path):
        os.makedirs(log_path)
    log = Log.Mylog(log_name='saftyCenter_diagfault', log_level = 'info')
    log.set_file_hl(file_name='{}/info.log'.format(log_path), log_level='info', size=1024* 1024 * 100)
    log.set_file_hl(file_name='{}/error.log'.format(log_path), log_level='error', size=1024* 1024 * 100)
    logger = log.get_logger()

    logger.info("pid is {}".format(os.getpid()))
    
    # 算法参数
    host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
    port=3306
    db='safety_platform'
    user='qx_read'
    password=parse.quote_plus('Qx@123456')
    tablename='all_fault_info'
    db_res_engine = create_engine(
        "mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8".format(
            user, password, host, port, db
        ))

        
    #............................模块运行前，先读取数据库中所有结束时间为0的数据，需要从数据库中读取................``
    # print("select start_time, end_time, product_id, code, level, info, advice, factory from {}".format(tablename))
    df_Diag_Ram=pd.read_sql("select start_time, end_time, product_id, code, level, info, advice, Batpos from all_fault_info where factory = '{}'".format('骑享'), db_res_engine)
    # result = result[['start_time', 'end_time', 'product_id', 'code', 'level', 'info', 'advice']]
    # df_Diag_Ram=result[result['end_time']=='0000-00-00 00:00:00']


    #定时任务.......................................................................................................................................................................
    fun()
    scheduler = BlockingScheduler()

    scheduler.add_job(fun, 'interval', seconds=600, id='diag_job')
    try:  
        scheduler.start()
    except Exception as e:
        scheduler.shutdown()
        logger.error(str(e))