DBManager.py 13 KB

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  1. '''
  2. 暂时采用http方式获取历史数据。
  3. 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。
  4. '''
  5. __author__ = 'wlm'
  6. from re import S
  7. import time
  8. import datetime
  9. import os
  10. import urllib.request
  11. import time
  12. import pandas as pd
  13. import numpy as np
  14. import json
  15. import requests
  16. import pdb
  17. # import http.client
  18. # http.client.HTTPConnection._http_vsn = 10
  19. # http.client.HTTPConnection._http_vsn_str = 'HTTP/1.1'
  20. class DBManager():
  21. def __init__(self, host='', port='', auth='', db='', username='', password=''):
  22. pass
  23. def __enter__(self):
  24. self.connect()
  25. return self
  26. def __exit__(self):
  27. self.close()
  28. def connect(self):
  29. conn_success_flag = 0
  30. while not conn_success_flag:
  31. try:
  32. pass # 连接数据库
  33. except Exception as e:
  34. conn_success_flag = 0
  35. time.sleep(5)
  36. else:
  37. conn_success_flag = 1
  38. pass # 连接成功, 获取cursor
  39. def close(self):
  40. try:
  41. pass # 断开数据库
  42. except Exception as e:
  43. print(e)
  44. else:
  45. print('数据库已断开连接')
  46. # 以下各个函数实现 通过http方式获取数据
  47. @staticmethod
  48. def _get_var_name(cellnum,Tempnum,Othernum):
  49. temp = []
  50. for i in range(cellnum):
  51. temp.append('单体电压'+str(i+1))
  52. for i in range(Tempnum):
  53. temp.append('单体温度'+str(i+1))
  54. for i in range(Othernum):
  55. temp.append('其他温度'+str(i+1))
  56. return temp
  57. @staticmethod
  58. def _download_json_data(url):
  59. '''
  60. 返回json数据的生成器,一次一行
  61. '''
  62. i = 0
  63. while 1:
  64. try:
  65. r = requests.get(url, stream=True, timeout=100, headers={'Connection':'close'})
  66. break
  67. except requests.exceptions.RequestException as e:
  68. if (i == 0):
  69. print()
  70. print('\r' + 'Server Error, retry {}......'.format(str(i)), end=" ")
  71. time.sleep(5)
  72. i+=1
  73. # print(r.content)
  74. # pdb.set_trace()
  75. for line in r.iter_lines():
  76. if line:
  77. yield json.loads(line)
  78. @staticmethod
  79. def _convert_to_bms(data, mode=0):
  80. CellU = []
  81. CellT = []
  82. OtherT = []
  83. CellU_Num = 0
  84. CellT_Num = 0
  85. OtherT_Num = 0
  86. CellU_Num = len(data['ffBatteryStatus']['cellVoltageList'])
  87. CellT_Num = len(data['ffBatteryStatus']['cellTempList'])
  88. try:
  89. OtherT_Num = len(data['ffBatteryStatus']['otherTempList'])
  90. except:
  91. OtherT_Num = 0
  92. for i in range(CellU_Num):
  93. CellU.append(data['ffBatteryStatus']['cellVoltageList'][i]*1000)
  94. for i in range(CellT_Num):
  95. CellU.append(data['ffBatteryStatus']['cellTempList'][i])
  96. for i in range(OtherT_Num):
  97. CellU.append(data['ffBatteryStatus']['otherTempList'][i])
  98. if mode == 0:
  99. data_len = 15
  100. data_block = np.array([data['info']['obdTime'],data['ffBatteryStatus']['rssi'],data['ffBatteryStatus']['errorLevel'],data['ffBatteryStatus']['errorCode']
  101. ,data['ffBatteryStatus']['current'],data['ffBatteryStatus']['voltageInner'],data['ffBatteryStatus']['voltageOutter'],
  102. data['ffBatteryStatus']['totalOutputState'],data['ffBatteryStatus']['lockedState'],
  103. data['ffBatteryStatus']['chargeState'],data['ffBatteryStatus']['heatState'],data['ffBatteryStatus']['cellVoltageDiff']
  104. ,data['ffBatteryStatus']['soc'],data['ffBatteryStatus']['soh'],data['ffBatteryStatus']['cellVolBalance']]).reshape(1,data_len)
  105. elif mode == 1:
  106. data_len = 7
  107. data_block = np.array([data['info']['obdTime'],data['ffBatteryStatus']['rssi']
  108. ,data['ffBatteryStatus']['current'],data['ffBatteryStatus']['voltageInner'],data['ffBatteryStatus']['chargeState']
  109. ,data['ffBatteryStatus']['soc'],data['ffBatteryStatus']['soh']]).reshape(1,data_len)
  110. data_block = np.append(data_block,CellU)
  111. data_block = np.append(data_block,CellT)
  112. data_block = np.append(data_block,OtherT)
  113. data_block = data_block.reshape(1,len(data_block))
  114. return data_block,CellU_Num,CellT_Num,OtherT_Num
  115. @staticmethod
  116. def _convert_to_dataframe_Gps(data, mode=0):
  117. if mode == 0:
  118. if data['info']['subType'] == 1:
  119. data_block = np.array([data['info']['obdTime'],data['ffGps']['locationType'], data['ffGps']['satellites'],
  120. data['ffGps']['latitude'],data['ffGps']['longitude'],data['ffGps']['speed'],
  121. data['ffGps']['altitude'], data['ffGps']['direction']]).reshape(1,8)
  122. df = pd.DataFrame(
  123. 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)
  124. elif data['info']['subType'] == 2:
  125. df = pd.DataFrame(
  126. columns=['时间戳','定位类型', '卫星数','纬度','经度','速度[km/h]','海拔','航向'])
  127. if mode == 1:
  128. data_block = np.array([data['info']['obdTime'],data['ffGps']['latitude'],data['ffGps']['longitude']
  129. ,data['ffGps']['speed'], data['ffGps']['isValid']]).reshape(1,5)
  130. df = pd.DataFrame(
  131. columns=['时间戳','纬度','经度','速度[km/h]','有效位'],data=data_block)
  132. return df
  133. @staticmethod
  134. def _get_data(urls,type_name,mode=0):
  135. if type_name == 'bms':
  136. if mode == 0:
  137. 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',
  138. '单体压差', 'SOC[%]','SOH[%]','单体均衡状态']
  139. elif mode == 1:
  140. name_const = ['时间戳','GSM信号','总电流[A]','总电压[V]','充电状态','SOC[%]','SOH[%]']
  141. i=0
  142. CellUNum = 0
  143. CellTNum = 0
  144. OtherTNumm = 0
  145. st = time.time()
  146. for line in DBManager._download_json_data(urls):
  147. et = time.time()
  148. if i==0:
  149. data_blocks,CellUNum,CellTNum,OtherTNumm = DBManager._convert_to_bms(line, mode)
  150. i+=1
  151. continue
  152. try:
  153. data_block,CellUNum,CellTNum,OtherTNumm = DBManager._convert_to_bms(line, mode)
  154. except:
  155. continue
  156. data_blocks = np.concatenate((data_blocks,data_block),axis=0)
  157. # print('\r'+str(i),end=" ")
  158. # print(data_block)
  159. # print(urls)
  160. # print(time.time()-et)
  161. i+=1
  162. name_var = DBManager._get_var_name(CellUNum,CellTNum,OtherTNumm)
  163. name_const.extend(name_var)
  164. columns_name = name_const
  165. if i==0:
  166. data_blocks = []
  167. df_all = pd.DataFrame(columns=columns_name,data=data_blocks)
  168. 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)))
  169. return df_all
  170. elif type_name =='gps':
  171. if mode == 0:
  172. 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'])
  173. elif mode == 1:
  174. df_all = pd.DataFrame(columns=['时间戳','纬度','经度','速度[km/h]','有效位'])
  175. for line in DBManager._download_json_data(urls):
  176. df_add = DBManager._convert_to_dataframe_Gps(line, mode)
  177. df_all = df_all.append(df_add,ignore_index=True)
  178. 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)))
  179. return df_all
  180. def get_data(self, url='http://172.16.126.13/store/load?dataType={}&limit=0&sn={}', sn='', start_time='', end_time='',
  181. data_groups=['bms', 'gps']):
  182. '''
  183. 获取指定 sn 和起止日期的bms和gps数据.
  184. 添加了重试机制。
  185. --------------输入参数------------
  186. url:数据获取url, 可采用默认值
  187. sn: str, 电池sn号
  188. start_time: str, 开始时间
  189. end_time: str, 结束时间
  190. 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)
  191. bms: bms数据
  192. gps:gps数据
  193. system:system数据
  194. accum:accum数据
  195. --------------输出参数------------
  196. df_data: {'bms':dataframe, 'gps':dataframe, 'system':dataframe, ;accum':dataframe}
  197. '''
  198. if len(set(data_groups) - (set(data_groups) and set(['bms', 'gps', 'system', 'accum']))) > 0:
  199. raise Exception("data_groups 参数错误")
  200. # mode: 0:正常取数; 1:7255 取数
  201. if sn[0:2] == 'MG' or sn[0:2] == 'UD':
  202. mode = 1
  203. else:
  204. mode = 0
  205. bms_all_data = pd.DataFrame()
  206. gps_all_data = pd.DataFrame()
  207. system_all_data = pd.DataFrame()
  208. accum_all_data = pd.DataFrame()
  209. 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
  210. print("### start to get data {} from {} to {}".format(sn, start_time, end_time))
  211. # 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
  212. for j in range(int(maxnum)):
  213. timefrom = datetime.datetime.strptime(start_time, "%Y-%m-%d %H:%M:%S")+ datetime.timedelta(days=j)
  214. timeto = datetime.datetime.strptime(start_time, "%Y-%m-%d %H:%M:%S")+ datetime.timedelta(days=j+1)
  215. #滴滴的数据sub=0
  216. if timefrom.strftime('%Y-%m-%d %H:%M:%S') > end_time:
  217. break
  218. elif timeto.strftime('%Y-%m-%d %H:%M:%S') > end_time:
  219. timeto = datetime.datetime.strptime(end_time, '%Y-%m-%d %H:%M:%S')
  220. #print('{}_{}_----getting data----'.format(sn, timefrom))
  221. bms_data = pd.DataFrame()
  222. gps_data = pd.DataFrame()
  223. system_data = pd.DataFrame()
  224. accum_data = pd.DataFrame()
  225. while True:
  226. try:
  227. print('\r' + "# get data from {} to {}.........".format(str(timefrom), str(timeto)), end=" ")
  228. for data_group in data_groups:
  229. if data_group == 'bms':
  230. file_url = url.format(12, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
  231. bms_data = DBManager._get_data(file_url,'bms',mode)
  232. if data_group == 'gps':
  233. file_url = url.format(16, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
  234. gps_data = DBManager._get_data(file_url,'gps',mode)
  235. if data_group == 'system':
  236. file_url = url.format(13, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
  237. system_data = DBManager._get_data(file_url,'system',mode)
  238. if data_group == 'accum':
  239. file_url = url.format(23, sn) + "&from="+timefrom.strftime('%Y-%m-%d %H:%M:%S')+"&to="+timeto.strftime('%Y-%m-%d %H:%M:%S')
  240. accum_data = DBManager._get_data(file_url,'accum',mode)
  241. except Exception as e:
  242. if 'Connection broken' in str(e):
  243. continue
  244. else:
  245. raise Exception
  246. else:
  247. bms_all_data = pd.concat([bms_all_data, bms_data], ignore_index=True)
  248. gps_all_data = pd.concat([gps_all_data, gps_data], ignore_index=True)
  249. system_all_data = pd.concat([system_all_data, system_data], ignore_index=True)
  250. accum_all_data = pd.concat([accum_all_data, accum_data], ignore_index=True)
  251. break
  252. bms_all_data = bms_all_data.reset_index(drop=True)
  253. gps_all_data = gps_all_data.reset_index(drop=True)
  254. system_all_data = system_all_data.reset_index(drop=True)
  255. accum_all_data = accum_all_data.reset_index(drop=True)
  256. print('\nall data-getting done, bms_count is {}, gps_count is {}, system_count is {}, accum_count is {} \n'.format(
  257. str(len(bms_all_data)), str(len(gps_all_data)), str(len(system_all_data)), str(len(accum_all_data))))
  258. return {'bms':bms_all_data, 'gps':gps_all_data, 'system':system_all_data, 'accum':accum_all_data}