data_analyze_platform/LIB/FRONTEND/CellStateEstimation/BatSafetyWarning/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 traceback
from LIB.MIDDLE.CellStateEstimation.Common import log
from LIB.MIDDLE.CellStateEstimation.BatSafetyWarning.V1_0_1 import CBMSSafetyWarning
from LIB.MIDDLE.CellStateEstimation.BatSafetyWarning.V1_0_1 import CBMSBatInterShort
from LIB.MIDDLE.CellStateEstimation.BatSafetyWarning.V1_0_1 import CBMSBatUniform
from LIB.MIDDLE.CellStateEstimation.BatSafetyWarning.V1_0_1 import VoltStray
from urllib import parse
import pymysql

from apscheduler.schedulers.blocking import BlockingScheduler

#...................................电池包电芯安全诊断函数......................................................................................................................
def saftywarning_cal():
    global df_sn
    global df_warning_ram
    global df_warning_ram1
    global df_warning_ram2
    global df_warning_ram3
    global df_lfp_ram
    global df_lfp_ram1

    
    
    # 读取结果数据库
    host2='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
    port2=3306
    db2='safety_platform'
    user2='qx_algo_rw'
    password2='qx@123456'
    
    db_safety_platform_engine = create_engine(
        "mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8".format(
            user2, parse.quote_plus(password2), host2, port2, db2
        ))
    conn_platform = pymysql.connect(host=host2, port=port2, user=user2, password=password2, database=db2)
    cursor_platform = conn_platform.cursor()

    
    host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com'
    port=3306
    db='qx_cas'
    user='qx_algo_rw'
    password='qx@123456'
    
    db_qxcas_engine = create_engine(
        "mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8".format(
            user, parse.quote_plus(password), host, port, db
        ))
    
    conn_cas = pymysql.connect(host=host, port=port, user=user, password=password, database=db)
    cursor_cas = conn_cas.cursor()
    
    result=pd.read_sql("select start_time, end_time, product_id, code, level, info, advice from all_fault_info", db_safety_platform_engine)
    result = result[['start_time', 'end_time', 'product_id', 'code', 'level', 'info', 'advice']]
    df_fault_ram=result[(result['end_time']=='0000-00-00 00:00:00') & (result['code']==110)]
    
    now_time=datetime.datetime.now()
    start_time=now_time-datetime.timedelta(hours=6)
    start_time1=now_time-datetime.timedelta(days=7)
    start_time2=now_time-datetime.timedelta(days=3)
    start_time3=now_time-datetime.timedelta(days=1)

    start_time=start_time.strftime('%Y-%m-%d %H:%M:%S')
    start_time1=start_time1.strftime('%Y-%m-%d %H:%M:%S')
    start_time2=start_time2.strftime('%Y-%m-%d %H:%M:%S')
    start_time3=start_time3.strftime('%Y-%m-%d %H:%M:%S')
    end_time=now_time.strftime('%Y-%m-%d %H:%M:%S')

    for i in range(0, len(df_sn)):
        factory = "骑享"
        try:
            sn = df_sn.loc[i, 'sn']
            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'][3:9] == 'CLL128':    
                celltype=100 # 重卡
                factory = "金茂换电"
            else:
                logger.info("pid-{} celltype-{} SN: {} SKIP!".format(os.getpid(), "未知", sn))
                continue
            
            
            logger.info("pid-{} celltype-{} SN: {} START!".format(os.getpid(), celltype, sn))

            # 读取soh数据
            df_soh = pd.read_sql("select time_st,sn,soh,cellsoh from cellstateestimation_soh where sn = '{}' order by id desc limit 1".format(sn), db_qxcas_engine)
            df_uniform = pd.read_sql("select time,sn,cellsoc_diff,cellvolt_diff,cellmin_num,cellmax_num,cellvolt_rank from cellstateestimation_uniform_socvoltdiff where sn = '{}' order by id desc limit 1".format(sn), db_qxcas_engine)
            df_uniform.loc[0,'cellvolt_rank']=str([1]*20)
            df_voltsigma=pd.DataFrame()
            #读取原始数据库数据................................................................................id........................................................................
            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']
            # print(df_bms)

            #电池诊断................................................................................................................................................................
            if not df_bms.empty:
                 #电池内短路计算................................................................................................................................................................
                df_warning_ram_sn=df_warning_ram[df_warning_ram['sn']==sn]
                df_warning_ram_sn1=df_warning_ram1[df_warning_ram1['sn']==sn]
                df_warning_ram_sn2=df_warning_ram2[df_warning_ram2['sn']==sn]
                df_warning_ram_sn3=df_warning_ram3[df_warning_ram3['sn']==sn]
                df_warning_ram_sn.reset_index(inplace=True,drop=True)     #重置索引
                df_warning_ram_sn1.reset_index(inplace=True,drop=True)     #重置索引
                df_warning_ram_sn2.reset_index(inplace=True,drop=True)     #重置索引
                df_warning_ram_sn3.reset_index(inplace=True,drop=True)     #重置索引
                if celltype>50 and (not df_lfp_ram.empty):
                    df_lfp_ram_sn=df_lfp_ram[df_lfp_ram['sn']==sn]
                    df_lfp_ram_sn.reset_index(inplace=True,drop=True)     #重置索引
                else:
                    df_lfp_ram_sn=pd.DataFrame()
                    df_lfp_ram=pd.DataFrame(columns=df_bms.columns.tolist()+['sn'])
                    
                if celltype>50 and (not df_lfp_ram1.empty):
                    df_lfp_ram_sn1=df_lfp_ram1[df_lfp_ram1['sn']==sn]
                    df_lfp_ram_sn1.reset_index(inplace=True,drop=True)     #重置索引
                else:
                    df_lfp_ram_sn1=pd.DataFrame()
                    df_lfp_ram1=pd.DataFrame(columns=df_bms.columns.tolist()+['sn'])
                
                #内短路计算..................................................................................................................................................
                BatShort=CBMSBatInterShort.BatInterShort(sn,celltype,df_bms,df_soh,df_warning_ram_sn,df_warning_ram_sn1,df_warning_ram_sn2,df_warning_ram_sn3,df_lfp_ram_sn)
                df_short_res, df_ram_res, df_ram_res1, df_ram_res2, df_ram_res3, df_ram_res4=BatShort.intershort() 

                if not df_short_res.empty:
                    df_short_res.columns = ['time_st', 'time_sp', 'sn', 'method', 'short_current', 'baltime']
                    df_short_res.to_sql("cellStateEstimation_interShort",con=db_qxcas_engine, if_exists="append",index=False)
                    
                #静置电压排名..................................................................................................................................................
                BatUniform=CBMSBatUniform.BatUniform(sn,celltype,df_bms,df_uniform,df_ram_res3,df_lfp_ram_sn1)
                df_rank_res, df_ram_res3, df_ram_res5=BatUniform.batuniform()
                if not df_rank_res.empty:
                    df_uniform=df_rank_res
                    df_rank_res.to_sql("cellstateestimation_uniform_socvoltdiff",con=db_qxcas_engine, if_exists="append",index=False)
                
                #电压离群.....................................................................................................................................................
                df_voltsigma=VoltStray.main(sn,df_bms,celltype)
                if not df_voltsigma.empty:
                    df_voltsigma.to_sql("outlier_voltchangeratio",con=db_qxcas_engine, if_exists="append",index=False)


                #内短路ram处理.........................................................
                df_warning_ram=df_warning_ram.drop(df_warning_ram[df_warning_ram.sn==sn].index)
                df_warning_ram1=df_warning_ram1.drop(df_warning_ram1[df_warning_ram1.sn==sn].index)
                df_warning_ram2=df_warning_ram2.drop(df_warning_ram2[df_warning_ram2.sn==sn].index)
                df_warning_ram3=df_warning_ram3.drop(df_warning_ram3[df_warning_ram3.sn==sn].index)

                df_warning_ram=pd.concat([df_warning_ram,df_ram_res],ignore_index=True)
                df_warning_ram1=pd.concat([df_warning_ram1,df_ram_res1],ignore_index=True)
                df_warning_ram2=pd.concat([df_warning_ram2,df_ram_res2],ignore_index=True)
                df_warning_ram3=pd.concat([df_warning_ram3,df_ram_res3],ignore_index=True)
                
                if celltype>50:
                    df_lfp_ram=df_lfp_ram.drop(df_lfp_ram[df_lfp_ram.sn==sn].index)
                    df_lfp_ram=pd.concat([df_lfp_ram,df_ram_res4],ignore_index=True)
                    df_lfp_ram1=df_lfp_ram1.drop(df_lfp_ram1[df_lfp_ram1.sn==sn].index)
                    df_lfp_ram1=pd.concat([df_lfp_ram1,df_ram_res5],ignore_index=True)
                    
            #电池热安全预警..............................................................................................................................................................
            #读取内短路、析锂和一致性结果数据库数据
            df_short = pd.read_sql("select time_sp,sn,short_current from cellstateestimation_intershort where sn = '{}' and time_sp between '{}' and '{}'".format(sn,start_time1,end_time), db_qxcas_engine)
            # df_liplated = pd.read_sql("select time,sn,liplated,liplated_amount from mechanism_liplated where sn = '{}' and time between '{}' and '{}'".format(sn,start_time2,end_time), db_qxcas_engine)
            df_uniform = pd.read_sql("select time,sn,cellsoc_diff,cellvolt_diff,cellmin_num,cellmax_num,cellvolt_rank from cellstateestimation_uniform_socvoltdiff where sn = '{}' and time between '{}' and '{}'".format(sn,start_time2,end_time), db_qxcas_engine)
            df_voltsigma = pd.read_sql("select time,sn,VolOl_Uni,VolChng_Uni from outlier_voltchangeratio where sn = '{}' and time between '{}' and '{}'".format(sn,start_time3,end_time), db_qxcas_engine)

            #获取sn的故障RAM
            df_fault_ram_sn=df_fault_ram[df_fault_ram['product_id']==sn]
            
            #热安全预警
            if df_fault_ram_sn.empty:
                BatWarning=CBMSSafetyWarning.SafetyWarning(sn,celltype,df_short,df_uniform,df_voltsigma,df_soh)
                df_warning_res=BatWarning.diag()
                #当前热失控故障写入数据库
                if not df_warning_res.empty:
                    df_warning_res['add_time'] = datetime.datetime.now()
                    df_warning_res['factory'] = factory
                    df_warning_res.to_sql("all_fault_info",con=db_safety_platform_engine, if_exists="append",index=False)
                    conn_platform.commit()
            else:
                fault_time=datetime.datetime.strptime(df_fault_ram_sn.iloc[-1]['start_time'], '%Y-%m-%d %H:%M:%S')
                if (now_time-fault_time).total_seconds()>3*24*3600:   #df_warning_end历史故障筛选并更改数据库故障结束时间
                    df_fault_ram_sn['end_time']=end_time
                    df_fault_ram_sn['Batpos']=1
                    try:
                        cursor_platform.execute('''
                                update all_fault_info set update_time='{}',end_time='{}', Batpos={} where product_id='{}' and code={} and end_time='0000-00-00 00:00:00'
                                '''.format(datetime.datetime.now(), df_fault_ram_sn.iloc[-1]['end_time'], df_fault_ram_sn.iloc[-1]['Batpos'],sn, 110))
                        conn_platform.commit()
                    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)
        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)
    cursor_platform.close()
    conn_platform.close()
    cursor_cas.close()
    conn_cas.close()
    db_qxcas_engine.dispose()
    db_safety_platform_engine.dispose()
    logger.info("pid-{} Done!".format(os.getpid()))

#...................................................主进程...........................................................................................................
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 where status in (1,2,3)")
    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='batsafetyWarning', 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................
    df_warning_ram=pd.DataFrame(columns=['sn','time','deltsoc','cellsoc'])
    df_warning_ram1=pd.DataFrame(columns=['sn','time1','deltsoc1'])
    df_warning_ram2=pd.DataFrame(columns=['sn','time2','deltAs2'])
    df_warning_ram3=pd.DataFrame(columns=['sn','time3','standingtime','standingtime1','standingtime2'])
    df_lfp_ram=pd.DataFrame()
    df_lfp_ram1=pd.DataFrame()

    # now_time='2021-10-15 00:00:00'
    # now_time=datetime.datetime.strptime(now_time,'%Y-%m-%d %H:%M:%S')
    saftywarning_cal()
    #定时任务.......................................................................................................................................................................
    scheduler = BlockingScheduler()
    scheduler.add_job(saftywarning_cal, 'interval', hours=6, id='saftywarning_cal')

    try:  
        scheduler.start()
    except Exception as e:
        scheduler.shutdown()
        logger.error(str(e))