zlwl-algos-new/USER/cez/socdiag/main.py

from datetime import datetime
from multiprocessing import Pool
import json
import os
import time
import traceback
import warnings

from sqlalchemy import text, delete, and_, or_, update
import pandas as pd

from ZlwlAlgosCommon.utils.ProUtils import *
from ZlwlAlgosCommon.service.iotp.IotpAlgoService import IotpAlgoService
from ZlwlAlgosCommon.service.iotp.Beans import DataField
from ZlwlAlgosCommon.orm.models import *

from socdiag.V_1_0_0.SOCBatDiag import SocDiag
# from LowSocAlarm.V1_0_0.low_soc_alarm import Low_soc_alarm                               

def main(process_num): 
    # 程序不能停止
    for i in range(1):
        warnings.filterwarnings("ignore")
        try:   
            # 调用算法前的准备工作
            kafka_topic_key = 'topic_test_cez'
            kafka_groupid_key = 'group_id_test_cez'
            algo_list = ['socdiag'] # 本调度所包含的算法名列表。
            
            loggers = sysUtils.get_loggers(algo_list, log_base_path, process_num) # 为每个算法分配一个logger
            logger_main.info(f"process-{process_num}: 配置中间件")
            
            # mysql
            mysql_algo_params = sysUtils.get_cf_param('mysql-algo')
            mysqlUtils = MysqlUtils()
            mysql_algo_engine, mysql_algo_Session= mysqlUtils.get_mysql_engine(mysql_algo_params)
            mysql_algo_conn = mysql_algo_engine.connect()
            
            
            mysql_iotp_data = sysUtils.get_cf_param('mysql-iotp')
            mysqlUtils = MysqlUtils()
            mysql_iotp_engine, mysql_iopt_Session= mysqlUtils.get_mysql_engine(mysql_iotp_data)
            mysql_iotp_conn = mysql_iotp_engine.connect()            
            
            

            # kafka
            kafka_params = sysUtils.get_cf_param('kafka')
            kafkaUtils = KafkaUtils()
            kafka_consumer = kafkaUtils.get_kafka_consumer(kafka_params, kafka_topic_key, kafka_groupid_key, client_id=kafka_topic_key)

            #Hbase
            hbase_params = sysUtils.get_cf_param('hbase-datafactory')
            iotp_service = IotpAlgoService(hbase_params=hbase_params)

            #redis
            redis_params = sysUtils.get_cf_param('redis')
            reidsUtils = RedisUtils()
            rc = reidsUtils.get_redis_conncect(redis_params)

        except Exception as e:
            logger_main.error(f'process-{process_num}: {e}')
            logger_main.error(f'process-{process_num}: {traceback.format_exc()}')
        
        # 开始准备调度
        logger_main.info(f"process-{process_num}: 监听topic {kafka_params[kafka_topic_key]}等待kafka 调度")
        for message in kafka_consumer:
            try:
                logger_main.info(f'收到调度')
                # kafka_consumer.commit()
                # continue
                if mysql_algo_conn.close:
                    mysql_algo_conn = mysql_algo_engine.connect() # 从连接池中获取一个myslq连接
                    
                schedule_params = json.loads(message.value)                    
                if (schedule_params is None) or (schedule_params ==''):
                    logger_main.info('{} kafka数据异常，跳过本次运算'.format(str(message.value)))
                    continue
                # kafka 调度参数解析
                df_snlist = pd.DataFrame(schedule_params['snlist'])
                # df_algo_adjustable_param = pd.DataFrame([(d['algo_id'], d['param'],d['param_ai']) for d in schedule_params['adjustable_param']], columns=['algo_id', 'param','param_ai'])
                df_algo_pack_param = json.loads(schedule_params['pack_param'][0]['param'])
                df_algo_pack_param = {k: eval(v) if isinstance(v, str) else v for k, v in df_algo_pack_param.items()}
                df_algo_param = pd.DataFrame(schedule_params['algo_list'])
                # start_time = schedule_params['start_time']
                # end_time = schedule_params['end_time']
                start_time = schedule_params['start_time'].replace(' ', '-').replace(':', '-')
                end_time = schedule_params['end_time'].replace(' ', '-').replace(':', '-')
                pack_code = schedule_params['pack_code']
                cell_type = schedule_params['cell_type']  
                sn_list=df_snlist['sn'].tolist()
                
                # 取数
                time_st = time.time()
                logger_main.info(f"process-{process_num}: 开始取数{sn_list}")
                columns = [ DataField.time, DataField.sn, DataField.pack_crnt, DataField.pack_volt, DataField.pack_soc,  
                            DataField.cell_voltage_count, DataField.cell_temp_count, DataField.cell_voltage, DataField.cell_temp, 
                            DataField.other_temp_value, DataField.bms_sta]
                # df_data = iotp_service.get_data(sn_list=sn_list, columns=columns, start_time=start_time, end_time=end_time)
                df_data = pd.read_pickle(f'/data/common/benchi/data/{sn}/{start_time}_{end_time}.zippkl', compression='zip')
                logger_main.info(f'process-{process_num},从{start_time}到{end_time}获取到{len(df_data)}条数据,取数耗时:{time.time()-time_st}')
            except Exception as e:
                kafka_consumer.commit()
                logger_main.error(f"process-{process_num}:{pack_code}获取原始数据出错")
                logger_main.error(f"process-{process_num}:{e}")
                logger_main.error(f"process-{process_num}:{traceback.format_exc()}")
                continue
            
            # 数据清洗
            try:
                time_st = time.time()
                logger_main.info(f'process-{process_num}数据清洗')                        
                df_data, df_table, cellvolt_name, celltemp_name = iotp_service.datacleaning(df_algo_pack_param,df_data)#进行数据清洗
                if len(df_data) == 0:
                    logger_main.info(f"process-{process_num}: 数据清洗耗时{time.time()-time_st}, 无有效数据，跳过本次运算")      
                    continue
                else:
                    logger_main.info(f"process-{process_num}: {pack_code}, time_type:{df_data.loc[0, 'time']} ~ {df_data.iloc[-1]['time']}, 数据清洗完成耗时{time.time()-time_st}")
            except Exception as e:
                logger_main.error(f"process-{process_num}:{pack_code}数据清洗出错")
                logger_main.error(f"process-{process_num}:{e}")
                logger_main.error(f"process-{process_num}:{traceback.format_exc()}")
                continue
            
            # mysql数据读取
            try:
                time_st = time.time()
                logger_main.info(f'process-{process_num}开始读取mysql故障数据')
                if len(sn_list) == 1:
                    sql = "select * from algo_all_fault_info_ing where  sn = '{}'".format(sn_list[0])
                else:
                    sql = "select * from algo_all_fault_info_ing where  sn in {}".format(tuple(sn_list)) #fault_code='{}' or fault_code='{}') and 'C599','C590', 
                df_diag_ram = pd.read_sql(sql, mysql_algo_conn)
                logger_main.info(f'process-{process_num}读取mysql耗时{time.time()-time_st}')

            except Exception as e:
                logger_main.error(f"process-{process_num}:{pack_code}读取redis出错")
                logger_main.error(f"process-{process_num}:{e}")
                logger_main.error(f"process-{process_num}:{traceback.format_exc()}")
                continue

            # 算法调用   
            try:
                time_st = time.time()
                loggers['socdiag'].info(f'开始执行算法{pack_code}, time:{start_time}~{end_time},\n sn_list:{sn_list}')
                period = 24*60 #算法周期min
                soc_diag = SocDiag(cell_type, df_algo_pack_param, df_algo_param, end_time, period, pack_code, df_snlist, df_data)
                df_res_end_C107= soc_diag.soc_jump()
                df_res_new_C109, df_res_end_C109 = soc_diag.soc_block(df_diag_ram)

                df_res_new_soc = df_res_new_C109
                df_res_end_soc = pd.concat([df_res_end_C107, df_res_end_C109])

                loggers['socdiag'].info(f'算法运行完成{pack_code}，算法耗时{time.time()-time_st}')
            except Exception as e:
                loggers['socdiag'].error('{}算法运行出错'.format(pack_code))
                loggers['socdiag'].error(str(e))
                loggers['socdiag'].error(traceback.format_exc())
                continue
            # 算法调用   
            # try:
            #     time_st = time.time()
            #     # loggers['low_soc_diag'].info(f'开始执行算法{pack_code}, time:{start_time}~{end_time},\n sn_list:{sn_list}')
            #     # low_soc_warning = Low_soc_alarm(df_data,cellvolt_name)
            #     # df_res_new_lw_soc, df_res_update_lw_soc,df_res_end_lw_soc= low_soc_warning.diag(df_algo_pack_param,df_algo_param,df_algo_adjustable_param,df_data,df_table,df_diag_ram,df_snlist)

            #     loggers['low_soc_diag'].info(f'算法运行完成{pack_code}，算法耗时{time.time()-time_st}')
            # except Exception as e:
            #     loggers['low_soc_diag'].error('{}算法运行出错'.format(pack_code))
            #     loggers['low_soc_diag'].error(str(e))
            #     loggers['low_soc_diag'].error(traceback.format_exc())
            #     continue            
            df_res_new = df_res_new_soc #, res1
            # df_res_update=df_res_update_lw_soc#pd.concat([df_res_update_lw_soc,df_res_update_crnt, df_res_update_temp]) #, res1
            df_res_end = df_res_end_soc #, res2
            df_res_new.reset_index(drop=True, inplace=True)
            # df_res_update.reset_index(drop=True, inplace=True)
            df_res_end.reset_index(drop=True, inplace=True)
            #结果写入mysql
            try:
                time_st = time.time()
                session = mysql_algo_Session()
                if not df_res_new.empty:
                    df_res_new['date_info'] = df_res_new['start_time']
                    df_res_new['create_time'] = datetime.now()
                    df_res_new['create_by'] = 'algo'
                    df_res_new['is_delete'] = 0
                    df_res_new.to_sql("algo_all_fault_info_ing", con=mysql_algo_conn, if_exists="append", index=False)
                    logger_main.info(f'process-{process_num}新增未结束故障入库{pack_code}完成')
                
                if not df_res_end.empty:
                    df_res_end=df_res_end.where(pd.notnull(df_res_end),None)
                    df_res_end=df_res_end.fillna(0)
                    for index in df_res_end.index:
                        df_t = df_res_end.loc[index:index]
                        sql = 'delete from algo_all_fault_info_ing where start_time=:start_time and fault_code=:fault_code and sn=:sn'
                        params = {'start_time': df_t['start_time'].values[0],
                                    'fault_code': df_t['fault_code'].values[0], 'sn': df_t['sn'].values[0]}
                        session.execute(sql, params=params)

                        sql = 'insert into algo_all_fault_info_done (date_info, start_time, end_time, sn, imei, model, fault_level, fault_code, fault_info,\
                        fault_reason, fault_advice, fault_location, device_status,odo, create_time, create_by,update_time, update_by, is_delete,comment) values \
                            (:date_info, :start_time, :end_time, :sn, :imei, :model,:fault_level, :fault_code, :fault_info,\
                        :fault_reason, :fault_advice, :fault_location, :device_status, :odo, :create_time, :create_by, :update_time,:update_by, :is_delete , :comment)'
                        params = {'date_info': datetime.now(),
                                    'start_time': df_t['start_time'].values[0],
                                    'end_time': df_t['end_time'].values[0],
                                    'sn': df_t['sn'].values[0],
                                    'imei': df_t['imei'].values[0],
                                    'model' :pack_code,
                                    'fault_level': df_t['fault_level'].values[0],
                                    'fault_code': df_t['fault_code'].values[0],
                                    'fault_info': df_t['fault_info'].values[0],
                                    'fault_reason': df_t['fault_reason'].values[0],
                                    'fault_advice': df_t['fault_advice'].values[0],
                                    'fault_location': df_t['fault_location'].values[0],
                                    'device_status': df_t['device_status'].values[0],
                                    'odo': df_t['odo'].values[0], 
                                    'create_time': datetime.now(),
                                    'create_by': 'algo',
                                    'update_time': datetime.now(),
                                    'update_by': None,
                                    'is_delete': 0,
                                    'comment': None}
                        session.execute(sql, params=params)
                        session.commit()
                    logger_main.info(f'process-{process_num}结束故障入库{pack_code}完成')
                # if not df_res_update.empty:
                #     df_res_update=df_res_update.where(pd.notnull(df_res_update),None)
                #     df_res_update=df_res_update.fillna(0)                    
                #     for index in df_res_update.index:
                #         df_t = df_res_update.loc[index:index]
                #         try:
                #             # 更新数据
                #             with mysql_algo_Session() as session:
                #                 session.execute(update(AlgoAllFaultInfoIng).where(
                #                     and_((AlgoAllFaultInfoIng.start_time == df_t['start_time'].values[0]), 
                #                             (AlgoAllFaultInfoIng.fault_code == df_t['fault_code'].values[0]),
                #                             (AlgoAllFaultInfoIng.sn == df_t['sn'].values[0]))).
                #                                 values(fault_level=df_t['fault_level'].values[0],
                #                                         comment=df_t['comment'].values[0]))
                #                 session.commit()
                #         except Exception as e:
                #             logger_main.error(f"process-{process_num}:{pack_code}结果入库出错")
                #             logger_main.error(f"process-{process_num}:{e}")
                #             logger_main.error(f"process-{process_num}:{traceback.format_exc()}")
                #         finally:
                #             session.close()
                #     logger_main.info(f"process-{process_num}: 更新入库完成")
                # else:
                #     logger_main.info(f"process-{process_num}: 无更新故障")                                            
                
                logger_main.info(f"process-{process_num}: 结果入库耗时：{time.time()-time_st}")

            except Exception as e:
                logger_main.error(f"process-{process_num}:{pack_code}结果入库出错")
                logger_main.error(f"process-{process_num}:{e}")
                logger_main.error(f"process-{process_num}:{traceback.format_exc()}")
            finally:
                pass

if __name__ == '__main__':
   while(True):
        try:
            # 配置量
            
            cur_env = 'dev' # 设置运行环境
            app_path = "/home/chenenze/zlwl-algos/" # 设置app绝对路径
            log_base_path = f"{os.path.dirname(os.path.abspath(__file__))}/log" # 设置日志路径

            app_name = "task_day_1_test" # 应用名
            
            sysUtils = SysUtils(cur_env, app_path)
            logger_main = sysUtils.get_logger(app_name, log_base_path)
            logger_main.info(f"本次主进程号: {os.getpid()}")
            # 读取配置文件 (该部分请不要修改)
            processes = int(sysUtils.env_params.get("PROCESS_NUM_PER_NODE", '1')) # 默认为1个进程
            pool = Pool(processes = int(processes))
            logger_main.info("开始分配子进程")
            for i in range(int(processes)):
                pool.apply_async(main, (i, ))
            pool.close()
            logger_main.info("进程分配结束，堵塞主进程")
            pool.join()
        except Exception as e:
            print(str(e))
            print(traceback.format_exc())
            logger_main.error(str(e))
            logger_main.error(traceback.format_exc())
        finally:
            handlers = logger_main.handlers.copy()
            for h in handlers:
                logger_main.removeHandler(h)
            pool.terminate()