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@@ -1,353 +1,3 @@
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-<<<<<<< HEAD
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-'''
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-暂时采用http方式获取历史数据。
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-
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-预留：后期若改用通过访问数据库的形式进行数据的获取，则本文件负责数据库的连接，sql指令的执行，数据获取等功能。
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-'''
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-__author__ = 'lmstack'
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-
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-
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-from re import S
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-import time
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-import datetime
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-import os
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-import urllib.request
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-import time
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-import pandas as pd
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-import numpy as np
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-import json
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-import requests
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-import pdb
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-
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-
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-# import http.client
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-# http.client.HTTPConnection._http_vsn = 10
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-# http.client.HTTPConnection._http_vsn_str = 'HTTP/1.1'
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-class DBManager():
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-
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- def __init__(self, host='', port='', auth='', db='', username='', password=''):
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- pass
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-
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- def __enter__(self):
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- self.connect()
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- return self
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-
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- def __exit__(self):
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- self.close()
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-
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- def connect(self):
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- conn_success_flag = 0
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- while not conn_success_flag:
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- try:
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- pass # 连接数据库
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- except Exception as e:
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- conn_success_flag = 0
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- time.sleep(5)
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- else:
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- conn_success_flag = 1
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- pass # 连接成功， 获取cursor
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- def close(self):
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- try:
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- pass # 断开数据库
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- except Exception as e:
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- print(e)
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- else:
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- print('数据库已断开连接')
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-
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- # 以下各个函数实现 通过http方式获取数据
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- @staticmethod
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- def _get_var_name(cellnum,Tempnum,Othernum):
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- temp = []
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- for i in range(cellnum):
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- temp.append('单体电压'+str(i+1))
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- for i in range(Tempnum):
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- temp.append('单体温度'+str(i+1))
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- for i in range(Othernum):
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- temp.append('其他温度'+str(i+1))
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- return temp
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-
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- @staticmethod
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- def _download_json_data(url):
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- '''
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- 返回json数据的生成器，一次一行
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- '''
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-
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- i = 0
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- while 1:
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- try:
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- r = requests.get(url, stream=True, timeout=100, headers={'Connection':'close'})
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- break
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- except requests.exceptions.RequestException as e:
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- if (i == 0):
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- print()
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- print('\r' + 'Server Error, retry {}......'.format(str(i)), end=" ")
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- time.sleep(5)
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- i+=1
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- # print(r.content)
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- # pdb.set_trace()
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- for line in r.iter_lines():
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- if line:
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- yield json.loads(line)
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-
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- @staticmethod
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- def _convert_to_dataframe_bms(data, mode=0):
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- CellU = []
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- CellT = []
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- OtherT = []
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- CellU_Num = 0
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- CellT_Num = 0
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- OtherT_Num = 0
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- CellU_Num = len(data['ffBatteryStatus']['cellVoltageList'])
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- CellT_Num = len(data['ffBatteryStatus']['cellTempList'])
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- try:
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- OtherT_Num = len(data['ffBatteryStatus']['otherTempList'])
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- except:
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- OtherT_Num = 0
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- for i in range(CellU_Num):
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- CellU.append(data['ffBatteryStatus']['cellVoltageList'][i]*1000)
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- for i in range(CellT_Num):
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- CellU.append(data['ffBatteryStatus']['cellTempList'][i])
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- for i in range(OtherT_Num):
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- CellU.append(data['ffBatteryStatus']['otherTempList'][i])
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- if mode == 0:
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- data_len = 15
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-
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- data_block = np.array([data['info']['obdTime'],data['ffBatteryStatus']['rssi'],data['ffBatteryStatus']['errorLevel'],data['ffBatteryStatus']['errorCode']
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- ,data['ffBatteryStatus']['current'],data['ffBatteryStatus']['voltageInner'],data['ffBatteryStatus']['voltageOutter'],
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- data['ffBatteryStatus']['totalOutputState'],data['ffBatteryStatus']['lockedState'],
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- data['ffBatteryStatus']['chargeState'],data['ffBatteryStatus']['heatState'],data['ffBatteryStatus']['cellVoltageDiff']
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- ,data['ffBatteryStatus']['soc'],data['ffBatteryStatus']['soh'],data['ffBatteryStatus']['cellVolBalance']]).reshape(1,data_len)
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- elif mode == 1:
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- data_len = 11
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-
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- data_block = np.array([data['info']['obdTime'],data['ffBatteryStatus']['rssi']
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- ,data['ffBatteryStatus'].get('errorLevel'),data['ffBatteryStatus'].get('errorCode'),data['ffBatteryStatus']['switchState']
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- ,data['ffBatteryStatus']['current'],data['ffBatteryStatus']['voltageInner'],data['ffBatteryStatus']['chargeState'],
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- data['ffBatteryStatus']['cellVoltageDiff'],data['ffBatteryStatus']['soc'],data['ffBatteryStatus']['soh']]).reshape(1,data_len)
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- data_block = np.append(data_block,CellU)
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- data_block = np.append(data_block,CellT)
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- data_block = np.append(data_block,OtherT)
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- data_block = data_block.reshape(1,len(data_block))
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- return data_block,CellU_Num,CellT_Num,OtherT_Num
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-
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- @staticmethod
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- def _convert_to_dataframe_gps(data, mode=0):
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- if mode == 0:
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- if data['info']['subType'] == 1:
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- data_block = np.array([data['info']['obdTime'],data['ffGps']['locationType'], data['ffGps']['satellites'],
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- data['ffGps']['latitude'],data['ffGps']['longitude'],data['ffGps']['speed'],
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- data['ffGps']['altitude'], data['ffGps']['direction']]).reshape(1,8)
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- df = pd.DataFrame(
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- columns=['时间戳','定位类型', '卫星数','纬度','经度','速度[km/h]','海拔','航向'],data=data_block)
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- elif data['info']['subType'] == 2:
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- df = pd.DataFrame(
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- columns=['时间戳','定位类型', '卫星数','纬度','经度','速度[km/h]','海拔','航向'])
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- if mode == 1:
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- data_block = np.array([data['info']['obdTime'],data['ffGps']['locationType'],data['ffGps']['latitude'],data['ffGps']['longitude']
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- ,data['ffGps']['speed'], data['ffGps']['isValid']]).reshape(1,6)
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- df = pd.DataFrame(
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- columns=['时间戳','定位类型', '纬度','经度','速度[km/h]','有效位'],data=data_block)
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- return df
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-
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-
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- @staticmethod
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- def _convert_to_dataframe_system(data, mode=0):
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- if mode == 0:
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-
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- data_block = np.array([data['info']['obdTime'],data['ffSystemInfo']['heatTargetTemp'], data['ffSystemInfo']['heatTimeout'],
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- time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(int(data['ffSystemInfo']['rentalStartTime'])/1000)),
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- data['ffSystemInfo']['rentalPeriodDays'],data['ffSystemInfo']['bmsInterval'],
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- data['ffSystemInfo']['gpsInterval']]).reshape(1,7)
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- df = pd.DataFrame(
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- columns=['时间戳','加热目标温度', '加热超时','租赁开始时间','租赁天数','bms上传周期','gps上传周期'],data=data_block)
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- if mode == 1:
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- df = pd.DataFrame()
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-
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- return df
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-
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- @staticmethod
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- def _convert_to_dataframe_accum(data, mode=0):
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- if mode == 0:
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-
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- data_block = np.array([data['info']['obdTime'],data['ffBatteryAccum']['SOH_AlgUnexTime'], data['ffBatteryAccum']['CHG_AHaccum'],
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- data['ffBatteryAccum']['CHG_PHaccum'], data['ffBatteryAccum']['DSG_AHaccum'],
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- data['ffBatteryAccum']['DSG_PHaccum'],data['ffBatteryAccum']['OverTemp_CHG_AHaccum'],
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- data['ffBatteryAccum']['OverTemp_CHG_PHaccum']]).reshape(1,8)
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- df = pd.DataFrame(
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- columns=['时间戳','SOH未标定时间', '累计充电电量','累计充电能量','累计放电电量','累计放电能量',
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- '累计高温充电电量', '累计高温充电能量'],data=data_block)
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-
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- if mode == 1:
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- data_block = np.array([data['info']['obdTime'], data['ffBatteryAccum']['CHG_AHaccum'],
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- data['ffBatteryAccum']['CHG_PHaccum'], data['ffBatteryAccum']['DSG_AHaccum'],
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- data['ffBatteryAccum']['DSG_PHaccum'],data['ffBatteryAccum']['totalMileage']]).reshape(1,6)
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- df = pd.DataFrame(
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- columns=['时间戳','累计充电电量','累计充电能量','累计放电电量','累计放电能量', '累积里程'],data=data_block)
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- return df
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-
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- @staticmethod
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- def _get_data(urls,type_name,mode=0):
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- if type_name == 'bms':
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- if mode == 0:
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- name_const = ['时间戳','GSM信号','故障等级','故障代码','总电流[A]','总电压[V]', '外电压', '总输出状态', '上锁状态', '充电状态','加热状态',
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- '单体压差', 'SOC[%]','SOH[%]','单体均衡状态']
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- elif mode == 1:
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- name_const = ['时间戳','GSM信号','故障等级', '故障代码','开关状态', '总电流[A]','总电压[V]','充电状态', '单体压差', 'SOC[%]','SOH[%]']
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- i=0
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- CellUNum = 0
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- CellTNum = 0
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- OtherTNumm = 0
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- st = time.time()
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- for line in DBManager._download_json_data(urls):
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- et = time.time()
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- if i==0:
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- data_blocks,CellUNum,CellTNum,OtherTNumm = DBManager._convert_to_dataframe_bms(line, mode)
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- i+=1
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- continue
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- try:
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- data_block,CellUNum,CellTNum,OtherTNumm = DBManager._convert_to_dataframe_bms(line, mode)
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- except:
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- continue
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- data_blocks = np.concatenate((data_blocks,data_block),axis=0)
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- # print('\r'+str(i),end=" ")
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- # print(data_block)
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- # print(urls)
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- # print(time.time()-et)
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- i+=1
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- name_var = DBManager._get_var_name(CellUNum,CellTNum,OtherTNumm)
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- name_const.extend(name_var)
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- columns_name = name_const
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- if i==0:
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- data_blocks = []
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- df_all = pd.DataFrame(columns=columns_name,data=data_blocks)
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- if not df_all.empty:
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- df_all.loc[:,'时间戳'] = df_all.loc[:,'时间戳'].apply(lambda x:time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(int(x)/1000)))
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- return df_all
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- elif type_name =='gps':
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- if mode == 0:
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- df_all = pd.DataFrame(columns=['时间戳','定位类型', '卫星数','纬度','经度','速度[km/h]','海拔','航向'])
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- elif mode == 1:
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- df_all = pd.DataFrame(columns=['时间戳','定位类型', '纬度','经度','速度[km/h]','有效位'])
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-
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- for line in DBManager._download_json_data(urls):
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- df_add = DBManager._convert_to_dataframe_gps(line, mode)
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- df_all = df_all.append(df_add,ignore_index=True)
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- if not df_all.empty:
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- df_all.loc[:,'时间戳'] = df_all.loc[:,'时间戳'].apply(lambda x:time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(int(x)/1000)))
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- return df_all
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- elif type_name =='system':
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- if mode == 0:
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- df_all = pd.DataFrame(columns=['时间戳','加热目标温度', '加热超时','租赁开始时间','租赁天数','bms上传周期','gps上传周期'])
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- elif mode == 1:
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- df_all = pd.DataFrame()
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- for line in DBManager._download_json_data(urls):
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- df_add = DBManager._convert_to_dataframe_system(line, mode)
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- df_all = df_all.append(df_add,ignore_index=True)
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- if not df_all.empty:
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- df_all.loc[:,'时间戳'] = df_all.loc[:,'时间戳'].apply(lambda x:time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(int(x)/1000)))
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- return df_all
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-
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- elif type_name =='accum':
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- if mode == 0:
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- df_all = pd.DataFrame(columns=['时间戳','SOH未标定时间', '累计充电电量','累计充电能量','累计放电电量','累计放电能量',
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- '累计高温充电电量', '累计高温充电能量'])
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- elif mode == 1:
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- df_all = pd.DataFrame(columns=['时间戳','累计充电电量','累计充电能量','累计放电电量','累计放电能量', '累积里程'])
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- for line in DBManager._download_json_data(urls):
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- df_add = DBManager._convert_to_dataframe_accum(line, mode)
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- df_all = df_all.append(df_add,ignore_index=True)
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- if not df_all.empty:
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- df_all.loc[:,'时间戳'] = df_all.loc[:,'时间戳'].apply(lambda x:time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(int(x)/1000)))
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- return df_all
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- def get_data(self, url='http://172.16.126.13/store/load?dataType={}&limit=0&sn={}', sn='', start_time='', end_time='',
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- data_groups=['bms', 'gps']):
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- '''
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- 获取指定 sn 和起止日期的bms和gps数据.
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- 添加了重试机制。
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-
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- --------------输入参数------------
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- url：数据获取url， 可采用默认值
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- sn: str, 电池sn号
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- start_time: str, 开始时间
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- end_time: str, 结束时间
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- data_groups: 选择需要获取的数据组，可填入多个字符串（默认只获取bms和gps数据）
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- bms: bms数据
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- gps：gps数据
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- system：system数据
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- accum：accum数据
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-
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-
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- --------------输出参数------------
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- df_data: {'bms':dataframe, 'gps':dataframe, 'system':dataframe, ;accum':dataframe}
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- '''
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-
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- if len(set(data_groups) - (set(data_groups) and set(['bms', 'gps', 'system', 'accum']))) > 0:
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- raise Exception("data_groups 参数错误")
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-
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-
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- # mode: 0：正常取数； 1：7255 取数
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- if sn[0:2] == 'UD' or sn[0:2] == 'MG':
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- mode = 1
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- else:
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- mode = 0
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- bms_all_data = pd.DataFrame()
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- gps_all_data = pd.DataFrame()
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- system_all_data = pd.DataFrame()
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- accum_all_data = pd.DataFrame()
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- maxnum = (datetime.datetime.strptime(end_time, "%Y-%m-%d %H:%M:%S") - datetime.datetime.strptime(start_time, "%Y-%m-%d %H:%M:%S")).days +1
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- print("### start to get data {} from {} to {}".format(sn, start_time, end_time))
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- # 为避免chunkEncodingError错误，数据每天获取一次，然后将每天的数据合并，得到最终的数据
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- for j in range(int(maxnum)):
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- timefrom = datetime.datetime.strptime(start_time, "%Y-%m-%d %H:%M:%S")+ datetime.timedelta(days=j)
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- timeto = datetime.datetime.strptime(start_time, "%Y-%m-%d %H:%M:%S")+ datetime.timedelta(days=j+1)
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- #滴滴的数据sub=0
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- if timefrom.strftime('%Y-%m-%d %H:%M:%S') >= end_time:
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- break
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- elif timeto.strftime('%Y-%m-%d %H:%M:%S') > end_time:
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- timeto = datetime.datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S')
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- #print('{}_{}_----getting data----'.format(sn, timefrom))
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- bms_data = pd.DataFrame()
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- gps_data = pd.DataFrame()
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- system_data = pd.DataFrame()
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- accum_data = pd.DataFrame()
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- while True:
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- try:
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- print('\r' + "# get data from {} to {}.........".format(str(timefrom), str(timeto)), end=" ")
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- for data_group in data_groups:
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- if data_group == 'bms':
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- file_url = url.format(12, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
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- bms_data = DBManager._get_data(file_url,'bms',mode)
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- if data_group == 'gps':
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- file_url = url.format(16, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
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- gps_data = DBManager._get_data(file_url,'gps',mode)
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- if data_group == 'system':
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- file_url = url.format(13, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
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- system_data = DBManager._get_data(file_url,'system',mode)
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- if data_group == 'accum':
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- file_url = url.format(23, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
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- accum_data = DBManager._get_data(file_url,'accum',mode)
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- except Exception as e:
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|
- if 'Connection broken' in str(e):
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- continue
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- else:
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- raise Exception
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- else:
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- bms_all_data = pd.concat([bms_all_data, bms_data], ignore_index=True)
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- gps_all_data = pd.concat([gps_all_data, gps_data], ignore_index=True)
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- system_all_data = pd.concat([system_all_data, system_data], ignore_index=True)
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- accum_all_data = pd.concat([accum_all_data, accum_data], ignore_index=True)
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-
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- break
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|
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-
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|
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- bms_all_data = bms_all_data.reset_index(drop=True)
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- gps_all_data = gps_all_data.reset_index(drop=True)
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- system_all_data = system_all_data.reset_index(drop=True)
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|
|
- accum_all_data = accum_all_data.reset_index(drop=True)
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|
|
- print('\nall data-getting done, bms_count is {}, gps_count is {}, system_count is {}, accum_count is {} \n'.format(
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|
|
- str(len(bms_all_data)), str(len(gps_all_data)), str(len(system_all_data)), str(len(accum_all_data))))
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|
- return {'bms':bms_all_data, 'gps':gps_all_data, 'system':system_all_data, 'accum':accum_all_data}
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-
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-=======
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'''
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暂时采用http方式获取历史数据。
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@@ -718,4 +368,3 @@ class DBManager():
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str(len(bms_all_data)), str(len(gps_all_data)), str(len(system_all_data)), str(len(accum_all_data))))
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return {'bms':bms_all_data, 'gps':gps_all_data, 'system':system_all_data, 'accum':accum_all_data}
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->>>>>>> 65a87ae16013552e359df047df19f46fc4e6eb08
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