def _Get_QueryParam(self, cmds):
nLen = len(cmds)
if (nLen > 1):
tradeParty = self._Get_Param(cmds, nLen, 2, self.billTradeParty)
tradeTarget = self._Get_Param(cmds, nLen, 3, self.billTradeTarget)
typeBill = self._Get_Param(cmds, nLen, 4, self.billType)
tradeType = self._Get_Param(cmds, nLen, 5, self.billTradeType)
tradeTargetType = self._Get_Param(cmds, nLen, 6,
self.billTradeTargetType)
startTime = self._Get_Param(cmds, nLen, 7, "")
endTime = self._Get_Param(cmds, nLen, 8, "")
if (startTime != ""):
startTime = myData_Trans.Tran_ToDatetime(startTime, "%Y-%m-%d")
if (endTime != ""):
endTime = myData_Trans.Tran_ToDatetime(endTime, "%Y-%m-%d")
#时间修正, 区分年月
nMonth = 0
nYear = 0
if (cmds[1].count("年") == 1):
if (type(startTime) != datetime.datetime):
nYear = int(cmds[1].replace("年", "").strip())
startTime = self.bills._Trans_Time_year("", nYear)
else:
nMonth = int(cmds[1].replace("月", "").strip())
return tradeParty, typeBill, tradeTarget, tradeType, tradeTargetType, startTime, endTime, nMonth
def _Init(self):
#提取字段信息
#dtUser = myIO_xlsx.loadDataTable(self.Path_SetUser, 0, 1) #用户信息
dtUser = myIO_xlsx.DtTable()
dtUser.Load_csv(self.Path_SetUser, 1, 0, isUtf=True)
if (len(dtUser.dataMat) < 1 or len(dtUser.dataField) < 1): return
lstFields_ind = dtUser.Get_Index_Fields(self.lstFields)
#转换为功能权限对象集
for dtRow in dtUser.dataMat:
pUser = myRoot_Usr("", dtRow[lstFields_ind["用户名"]])
pUser.usrID_sys = dtRow[lstFields_ind["ID"]]
pUser.usrRelationID_sys = dtRow[
lstFields_ind["RelationIDs"]].split('、')
pUser.usrName_Nick = dtRow[lstFields_ind["用户昵称"]]
pUser.usrID = dtRow[lstFields_ind["用户ID"]]
pUser.usrName_Full = dtRow[lstFields_ind["用户姓名"]]
if (pUser.usrName_Full != ""):
pUser.usrRelations.append(pUser.usrName_Full)
pUser.usrPlat = dtRow[lstFields_ind["来源平台"]]
pUser.usrPhones = dtRow[lstFields_ind["电话"]].split('、')
pUser.usrTags = dtRow[lstFields_ind["标签"]].split('、')
pUser.usrAddresss = dtRow[lstFields_ind["地址"]].split('、')
pUser.usrRamak = dtRow[lstFields_ind["备注"]]
pUser.usrNotes = dtRow[lstFields_ind["描述"]]
pUser.usrTime_Regist = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["注册时间"]])
pUser.usrTime_Logined_Last = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["最后登录时间"]])
pUser.usrLoaded = True
self._Index(pUser) #索引用户信息
def _Init_DB(self, path):
#提取字段信息
dtDB = myIO_xlsx.DtTable()
dtDB.Load_csv(path, 1, 0, True, 0, ',', isUtf=True)
lstFields = [
"编号", "用户名", "操作类型", "标的代码", "标的名称", "标的所属市场", "标的所属市场板块", "标的价格",
"标的价格-期望", "标的仓位", "标的所属行业", "标的所属概念", "交易类型", "交易子类型", "交易数量",
"交易金额", "交易量仓位占比", "交易收益", "交易收益-总计", "交易时间", "是否删除", "记录人",
"记录时间", "备注"
]
if (dtDB.sheet == None): dtDB.dataField = lstFields
lstFields_ind = dtDB.Get_Index_Fields(lstFields)
self.lstFields = lstFields
self.pathData = path
#装载账单记录
self.usrDB = {}
self.indLst = []
for dtRow in dtDB.dataMat:
trade = myObj_Trade()
if (dtRow[lstFields_ind["记录时间"]] == ""): continue
trade.recordTime = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["记录时间"]])
trade.recorder = dtRow[lstFields_ind["记录人"]]
trade.usrID = dtRow[lstFields_ind["用户名"]]
trade.usrOrderType = dtRow[lstFields_ind["操作类型"]]
trade.targetID = dtRow[lstFields_ind["标的代码"]]
trade.targetName = dtRow[lstFields_ind["标的名称"]]
trade.targetMarket = dtRow[lstFields_ind["标的所属市场"]]
trade.targetMarketBoard = dtRow[lstFields_ind["标的所属市场板块"]]
trade.targetIndustries = dtRow[lstFields_ind["标的所属行业"]].split("、")
trade.targetConcepts = dtRow[lstFields_ind["标的所属概念"]].split("、")
trade.targetPrice = float(dtRow[lstFields_ind["标的价格"]])
trade.targetPrice_Ex = float(dtRow[lstFields_ind["标的价格-期望"]])
trade.targetPosition = float(dtRow[lstFields_ind["标的仓位"]])
trade.infoID = int(dtRow[lstFields_ind["编号"]])
trade.tradeType = dtRow[lstFields_ind["交易类型"]]
trade.tradeType_sub = dtRow[lstFields_ind["交易子类型"]]
trade.tradeNum = float(dtRow[lstFields_ind["交易数量"]])
trade.tradeMoney = float(dtRow[lstFields_ind["交易金额"]])
trade.tradePosition = float(dtRow[lstFields_ind["交易量仓位占比"]])
trade.tradeProfit = float(dtRow[lstFields_ind["交易收益"]])
trade.tradeProfit_total = float(dtRow[lstFields_ind["交易收益-总计"]])
trade.tradeTime = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["交易时间"]])
trade.isDel = myData.iif(dtRow[lstFields_ind["是否删除"]] == "TRUE",
True, False)
trade.remark = dtRow[lstFields_ind["备注"]]
self.usrDB[trade.infoID] = trade
self.indLst.append(trade.infoID) # 顺序记录索引
self.dtDB = dtDB
def getTime(self, bMinute = False):
if(not bMinute):
if(self.datetime == None):
self.datetime = myData_Trans.Tran_ToDatetime(self.date + " " + self.time)
#print(self.datetime)
return self.datetime
else:
times = self.time.split(":")
datetime = myData_Trans.Tran_ToDatetime(self.date + " " + times[0] + ":" + times[1], "%Y-%m-%d %H:%M")
myDebug.Debug(datetime , "-- New Minutes")
return datetime
def _Init_DB(self, path):
#提取字段信息
dtDB = myIO_xlsx.DtTable()
dtDB.Load_csv(path, 1, 0, True, 0, ',', isUtf=True)
lstFields = [
"编号", "账单类型", "交易方", "交易类型", "交易子类", "交易内容", "交易单价", "交易数量",
"剩余数量", "交易金额", "手续费", "交易收益", "交易时间", "关联编号", "是否删除", "记录人",
"记录时间", "备注"
]
if (dtDB.sheet == None): dtDB.dataField = lstFields
lstFields_ind = dtDB.Get_Index_Fields(lstFields)
self.lstFields = lstFields
self.pathData = path
#装载账单记录
self.usrDB = {}
self.indLst = []
for dtRow in dtDB.dataMat:
bill = myObj_Bill()
bill.usrID = self.usrID
if (dtRow[lstFields_ind["记录时间"]] == ""): continue
bill.recordTime = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["记录时间"]])
bill.recorder = dtRow[lstFields_ind["记录人"]]
bill.usrBillType = dtRow[lstFields_ind["账单类型"]]
bill.tradeID = int(dtRow[lstFields_ind["编号"]])
bill.tradeParty = dtRow[lstFields_ind["交易方"]]
bill.tradeType = dtRow[lstFields_ind["交易类型"]]
bill.tradeTypeTarget = dtRow[lstFields_ind["交易子类"]]
bill.tradeTarget = dtRow[lstFields_ind["交易内容"]]
bill.tradePrice = float(dtRow[lstFields_ind["交易单价"]])
bill.tradeNum = float(dtRow[lstFields_ind["交易数量"]])
bill.tradeNum_Stock = float(dtRow[lstFields_ind["剩余数量"]])
bill.tradeMoney = float(dtRow[lstFields_ind["交易金额"]])
bill.tradePoundage = float(dtRow[lstFields_ind["手续费"]])
bill.tradeProfit = float(dtRow[lstFields_ind["交易收益"]])
bill.tradeTime = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["交易时间"]])
bill.tradeID_Relation = dtRow[lstFields_ind["关联编号"]]
if (bill.tradeID_Relation == "0"):
bill.tradeID_Relation = ""
bill.isDel = myData.iif(dtRow[lstFields_ind["是否删除"]] == "TRUE",
True, False)
bill.remark = dtRow[lstFields_ind["备注"]]
self.usrDB[bill.tradeID] = bill
self.indLst.append(bill.tradeID) # 顺序记录索引
self.dtDB = dtDB
def setTime(self):
self.dtDay = myData_Trans.Tran_ToTime_str(None, "%Y-%m-%d") #当前天
self.startTime = myData_Trans.Tran_ToDatetime(self.dtDay +
" 9:26:30") #起始时间
self.endTime = myData_Trans.Tran_ToDatetime(self.dtDay +
" 11:30:30") #结束时间
self.endTime2 = myData_Trans.Tran_ToDatetime(self.dtDay +
" 15:16:00") #结束时间--收盘
self.timeIntervals = 0
#时间段监测
tNow = datetime.datetime.now()
if (tNow.hour > 15):
self.timeIntervals = 1
return (self.startTime < tNow and tNow < self.endTime2)
def OnHandleMsg_ByThread(self):
try:
#线程循环
while self.isRuning:
try:
#循环所有缓存进行处理
for x in self.usrMsgs_Buffer:
bNeedSend = False
time = x.get("timeLimit", "")
if (time == "" and myData_Trans.Is_Numberic(time)):
bNeedSend = True
else:
if (type(time) != datetime.datetime):
time = myData_Trans.Tran_ToDatetime(time)
time_N = datetime.datetime.now()
if (time_N >= time):
bNeedSend = True
#消息发送
if (bNeedSend == False): continue
x['timeLimit'] = ""
self.OnHandleMsg(x, "")
self.usrMsgs_Buffer.remove(x)
# 延时
self.OnHandleMsg_ByThread_sleep(0.5)
except:
myDebug.Error("Err:: Run_OnHandleMsg_ByThread... ")
except:
myDebug.Error("Err:: Run_OnHandleMsg_ByThread... Restart...")
myDebug.Print('Thread Run_OnHandleMsg_ByThread is exiting...')
def getOptInfo(self, optPrice=2500, dateTime="", month_Delta=0):
# 同步参数
if (dateTime == ""):
dateTime = myData_Trans.Tran_ToDatetime_str(None, "%Y-%m-%d")
dtFliter = myData_Trans.Tran_ToDatetime(dateTime, "%Y-%m-%d")
strFliter = "50ETF" + myData.iif(
optPrice > 0, "购",
"沽") + str(dtFliter.month + month_Delta) + "月" + str(abs(optPrice))
# 查询
optInfos = opt.run_query(
query(opt.OPT_DAILY_PREOPEN).filter(
opt.OPT_DAILY_PREOPEN.date == dateTime,
opt.OPT_DAILY_PREOPEN.name == strFliter).limit(10))
if (optInfos.shape[0] != 1): return None
# 查询最新的期权基本资料数据
code = optInfos['code'][0]
optInfo = query(
opt.OPT_CONTRACT_INFO).filter(opt.OPT_CONTRACT_INFO.code == code)
value = opt.run_query(optInfo)
if (len(value) != 1): return None
return {
'id': value['id'][0],
'code': value['code'][0],
'trading_code': value['trading_code'][0],
'name': value['name'][0]
}
def __init__(self):
self.wind_Speed = 0
self.wind_Direction = 0
self.wind_Direction2 = 0
self.wind_Direction_Alias = ""
self.wind_Height = 0
self.wind_Tiem_start = myData_Trans.Tran_ToDatetime("")
self.wind_Tiem_duration = 0
def _Trans_Time_moth(self, dtTime = '', nMonth = 1):
if(type(dtTime) != datetime.datetime): dtTime = datetime.datetime.now()
dtTime = dtTime - datetime.timedelta(days=(dtTime.day - 1))
while(nMonth > 1):
dtTime = self._Trans_Time_moth(dtTime - datetime.timedelta(days=1))
nMonth -= 1
strTime = myData_Trans.Tran_ToDatetime_str(dtTime, "%Y-%m-%d")
return myData_Trans.Tran_ToDatetime(strTime, "%Y-%m-%d")
def initWind(self, direction, speed, higth=0, startTime="", duration=-1):
self.wind_Speed = myData_Trans.To_Float(str(speed))
self.wind_Direction = self.initWind_Direction(direction)
self.wind_Direction2 = 90 - self.wind_Direction
if (self.wind_Direction2 < 0): self.wind_Direction2 += 360
self.wind_Height = myData_Trans.To_Float(str(higth))
self.wind_Tiem_start = startTime
if (type(self.wind_Tiem_start) == str):
self.wind_Tiem_start = myData_Trans.Tran_ToDatetime(startTime)
self.wind_Tiem_duration = duration
def checkTime(self, data=None):
if (data == None):
tNow = datetime.datetime.now()
if (self.startTime < tNow and tNow < self.endTime):
return True
else:
if (tNow > self.endTime):
self.startTime = myData_Trans.Tran_ToDatetime(
self.dtDay + " 13:00:00") #起始时间
self.endTime = self.endTime2 #结束时间
if (self.startTime < tNow and tNow < self.endTime):
return True
return False
#时间判断
tNow = data.datetime_queryed
if (self.startTime < tNow and tNow < self.endTime):
if (self.timeIntervals > 0):
self.timeIntervals += 1
return True
elif (self.timeIntervals == 0 and self.endTime < tNow):
self.startTime = myData_Trans.Tran_ToDatetime(
self.dtDay + " 13:00:00") #起始时间
self.endTime = self.endTime2 #结束时间
self.timeIntervals += 1
if (self.datasNow != None):
self.datasNow.saveData() #保存数据（第一时段结束）
return self.checkTime(data)
elif (self.endTime < tNow):
if (self.datas.get(data.name,
None) == None): #初始数据(当天结束时段后，只有一条数据)
self.timeIntervals += 1
return True
elif (self.timeIntervals > 1):
#设置数据监听停止
if (self.datasNow.name != data.name):
self.datasNow = self.datas.get(data.name, None)
if (self.datasNow.stoped == False):
self.datasNow.saveData() #保存数据（第二时段结束）
self.datasNow.stoped = True
myDebug.Print("... stoped data(" + data.name + ")...")
return False
def _Init(self):
#提取字段信息
#dtGroup = myIO_xlsx.loadDataTable(self.Path_SetUser, 0, 1) #用户信息
dtGroup = myIO_xlsx.DtTable()
dtGroup.Load_csv(self.Path_SetUser, 1, 0, isUtf=True)
if (len(dtGroup.dataMat) < 1 or len(dtGroup.dataField) < 1): return
lstFields_ind = dtGroup.Get_Index_Fields(self.lstFields)
#转换为功能权限对象集
for dtRow in dtGroup.dataMat:
pGroup = myRoot_GroupInfo("", dtRow[lstFields_ind["群组名"]])
pGroup.groupID = dtRow[lstFields_ind["ID"]]
pGroup.typeName = dtRow[lstFields_ind["来源平台"]].split('、')
pGroup.groupDesc = dtRow[lstFields_ind["描述"]]
pGroup.groupTime_Regist = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["注册时间"]])
pGroup.groupTime_Logined_Last = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["最后登录时间"]])
self._Index(pGroup) #索引用户信息
def Init_ByDict(self, tradeInfo={}):
self.usrID = tradeInfo.get("usrID", "")
self.usrOrderType = tradeInfo.get("usrOrderType", "")
self.recordTime = tradeInfo.get("recordTime", datetime.datetime.now())
if (self.recordTime == None): self.recordTime = datetime.datetime.now()
self.recorder = tradeInfo.get("recorder", "zxcRobot")
if (self.recorder == ''): self.recorder = 'zxcRobot'
self.targetID = tradeInfo.get("targetID", 0)
self.targetName = tradeInfo.get("targetName", "")
self.targetMarket = tradeInfo.get("targetMarket", "")
self.targetMarketBoard = tradeInfo.get("targetMarketBoard", "")
self.targetIndustries = tradeInfo.get("targetIndustries", [])
self.targetConcepts = tradeInfo.get("targetConcepts", [])
self.targetPrice = tradeInfo.get("targetPrice", 0)
self.targetPrice_Ex = tradeInfo.get("targetPrice_Ex", 0)
self.targetPosition = tradeInfo.get("targetPosition", 0)
self.infoID = tradeInfo.get("infoID", 0)
self.tradeType = tradeInfo.get("tradeType", "")
self.tradeType_sub = tradeInfo.get("tradeType_sub", "")
self.tradeNum = tradeInfo.get("tradeNum", 0)
self.tradeMoney = tradeInfo.get("tradeMoney", 0)
self.tradePosition = tradeInfo.get("tradePosition", 0)
self.tradeProfit = tradeInfo.get("tradeProfit", 0)
self.tradeProfit_total = tradeInfo.get("tradeProfit_total", 0)
dateTime = tradeInfo.get("tradeTime", "")
self.tradeTime = myData.iif(dateTime == "", datetime.datetime.now(),
dateTime)
if (type(self.tradeTime) == str):
if (self.tradeTime.count(":") == 2):
self.tradeTime = myData_Trans.Tran_ToDatetime(dateTime)
else:
self.tradeTime = myData_Trans.Tran_ToDatetime(
dateTime, "%Y-%m-%d")
self.isDel = tradeInfo.get("isDel", False)
self.remark = tradeInfo.get("remark", "")
return self.Init_CheckInfo(self.usrOrderType, self.tradeType,
self.tradeType_sub)
def SwapData_In(self, nStepSwaps=1):
nums = 0
lstDatas = []
nStepSwaps = myData.iif(nStepSwaps <= 0, sys.maxsize, nStepSwaps)
lstFiles = myIO.getFiles(self.dirSwap, wildcard=".json", iswalk=False)
if (len(lstFiles) < 1): return lstDatas
myDebug.Print("DataSwap IOFiles::")
myDebug.Print("\t" + self.dirSwap)
myDebug.Print("\tSwap IOFiles(" + str(len(lstFiles)) + ")")
for file in lstFiles:
fileName = myIO.getFileName(file, True)
if (fileName[0:len(self.tagName)] != self.tagName): continue
if (self.checkNeedAck(fileName)): continue
# 超时校检
if (self.delayedTime > 0): #解析时间并校检
timeTag = fileName[len(self.tagName) + 1:]
timeData = myData_Trans.Tran_ToDatetime(
timeTag, "%Y-%m-%d-%H-%M-%S")
dtNow = datetime.datetime.now()
if ((dtNow - timeData).seconds > self.delayedTime):
self.SwapData_BackUp(file)
continue
#读取文件内容
myDebug.Print("\tnew file swap:: " + myIO.getFileName(file, False))
strJson = myIO.getContent(file, noBOM=True)
pJson = myData_Json.Json_Object()
pJson.Trans_FromStr(strJson)
#组装交换信息
data = {"path": file, "fileInfo": pJson._dict_}
lstDatas.append({"tagAck": fileName, "data": data})
#记录Ackinfo
if (self.useAck):
ackInfo = {
"isAcked": False,
"time": datetime.datetime.now(),
"retrys": 0,
"path": file
}
self.ackDict[fileName] = ackInfo
else:
self.SwapData_BackUp(file)
nums += 1
if (nums >= nStepSwaps): break
myDebug.Print("DataSwap IOFiles End." + "\tMargin Swap IOFiles(" +
str(len(lstFiles) - len(lstDatas)) + ")\n")
return lstDatas
def loadDt_Row(self, ind_row, col_start=0, isField=False, csvLines=None):
pTypes = self.dataFieldType
nFields = len(pTypes)
pValues = []
if (csvLines == None):
rows = self.sheet.row_values(
ind_row) # 获取整行内容,列内容: pSheet.col_values(i)
cols = self.sheet.ncols
else:
rows = csvLines # csv行数据
cols = len(self.dataField)
# 转换数据类型
cols_row = len(rows)
for j in range(col_start, cols):
if (nFields > j and cols_row > j and isField == False):
if (pTypes[j] == myFiledype.float):
pValues.append(float(rows[j]))
continue
elif (pTypes[j] == myFiledype.int):
pValues.append(int(rows[j]))
continue
elif (pTypes[j] == myFiledype.datetime):
nCount = rows[j].count(":")
if (nCount == 0):
pValues.append(
myData_Trans.Tran_ToDatetime(rows[j], "%Y-%m-%d"))
elif (nCount == 1):
pValues.append(
myData_Trans.Tran_ToDatetime(
rows[j], "%Y-%m-%d %H:%M"))
else:
pValues.append(myData_Trans.Tran_ToDatetime(rows[j]))
continue
elif (pTypes[j] == myFiledype.bool):
pValues.append(myData_Trans.To_Bool(rows[j]))
continue
#其他全部为默认类型
pValues.append(rows[j])
return pValues
def Init_ByDict(self, tradeInfo={}):
self.usrID = tradeInfo.get("usrID", "")
usrBillType = tradeInfo.get("usrBillType", "")
self.recordTime = tradeInfo.get("recordTime", datetime.datetime.now())
if (self.recordTime == None): self.recordTime = datetime.datetime.now()
self.recorder = tradeInfo.get("recorder", "zxcRobot")
if (self.recorder == ''): self.recorder = 'zxcRobot'
self.tradeID = tradeInfo.get("tradeID", 0)
self.tradeID_Relation = tradeInfo.get("tradeID_Relation", "")
self.tradeParty = tradeInfo.get("tradeParty", "")
tradeType = tradeInfo.get("tradeType", "")
tradeTypeTarget = tradeInfo.get("tradeTypeTarget", "")
tradeTarget = tradeInfo.get("tradeTarget", "")
self.tradePrice = tradeInfo.get("tradePrice", 0)
self.tradeNum = tradeInfo.get("tradeNum", 0)
self.tradeNum_Stock = tradeInfo.get("tradeNum_Stock", 0)
if (usrBillType == '买入'):
self.tradeNum_Stock = self.tradeNum
self.tradeMoney = tradeInfo.get("tradeMoney", 0)
self.tradePoundage = tradeInfo.get("tradePoundage", 0)
self.tradeProfit = tradeInfo.get("tradeProfit", 0)
dateTime = tradeInfo.get("tradeTime", "")
self.tradeTime = myData.iif(dateTime == "", datetime.datetime.now(),
dateTime)
if (type(self.tradeTime) == str):
if (self.tradeTime.count(":") == 2):
self.tradeTime = myData_Trans.Tran_ToDatetime(dateTime)
else:
self.tradeTime = myData_Trans.Tran_ToDatetime(
dateTime, "%Y-%m-%d")
self.isDel = tradeInfo.get("isDel", False)
self.remark = tradeInfo.get("remark", "")
self.Init_TypeInfo(usrBillType, tradeTarget, tradeType,
tradeTypeTarget)
def fromValueList(self, lstValue):
self.dtTime = lstValue[0]
if(type(self.dtTime) != datetime.datetime):
self.dtTime = myData_Trans.Tran_ToDatetime(str(self.dtTime))
self.seconds = lstValue[1]
self.base = lstValue[2]
self.start = lstValue[3]
self.last = lstValue[4]
self.high = lstValue[5]
self.low = lstValue[6]
self.average = lstValue[7]
self.tradeVolume = lstValue[8]
self.tradeTurnover = lstValue[9]
self.tradeVolume_Start = lstValue[10]
self.tradeVolume_End = lstValue[11]
self.tradeTurnover_Start = lstValue[12]
self.tradeTurnover_End = lstValue[13]
def __init__(self):
super().__init__()
self.modelName = "Atmospheric_Diffusion"
self.modelName_Alias = "大气扩散模型"
self.modelType = "webAPI"
self.modelResult = ""
self.modeRunning = False
self.wind = myModel_Object.myObj_Wind()
self.air = myModel_Object.myObj_Air()
self.sun = myModel_Object.myObj_Sun()
self.longitude_Leak = 0
self.latitude_Leak = 0
self.height_Leak = 0
self.massrate_Leak = 0
self.infoTargets = []
self.dtLeak = myData_Trans.Tran_ToDatetime("")
self.hasChimney = False
def fromValueList(self, lstValue):
self.dataList = lstValue
dtNow = lstValue[0]
if(type(dtNow) == str): dtNow = myData_Trans.Tran_ToDatetime(dtNow)
self.date = str(dtNow.year) + "-" + str(dtNow.month) + "-" + str(dtNow.day)
self.time = str(dtNow.hour) + ":" + str(dtNow.minute) + ":" + str(dtNow.second)
self.lastPrice = str(lstValue[1])
self.highPrice = str(lstValue[2])
self.lowPrice = str(lstValue[3])
self.buyPrice = str(lstValue[4])
self.sellPrice = str(lstValue[5])
self.tradeValume = str(lstValue[6])
self.tradeTurnover = str(lstValue[7])
self.buy1Volume = str(lstValue[8]) #买1-5量
self.buy2Volume = str(lstValue[9])
self.buy3Volume = str(lstValue[10])
self.buy4Volume = str(lstValue[11])
self.buy5Volume = str(lstValue[12])
self.buy1Price = str(lstValue[13]) #买1-5价格
self.buy2Price = str(lstValue[14])
self.buy3Price = str(lstValue[15])
self.buy4Price = str(lstValue[16])
self.buy5Price = str(lstValue[17])
self.sell1Volume = str(lstValue[18]) #卖1-5量
self.sell2Volume = str(lstValue[19])
self.sell3Volume = str(lstValue[20])
self.sell4Volume = str(lstValue[21])
self.sell5Volume = str(lstValue[22])
self.sell1Price = str(lstValue[23])
self.sell2Price = str(lstValue[24])
self.sell3Price = str(lstValue[25])
self.sell4Price = str(lstValue[26])
self.sell5Price = str(lstValue[27])
self.priceOpen = myData_Trans.To_Float(self.openPrice) #开盘价格
self.priceBase = myData_Trans.To_Float(self.preClose) #前一收盘价格
return True
# 期权交易测试-实时模拟
if(1 == 2):
#初始风险对象
pRisk_300033 = pRisk.getRiskSet('茶叶一主号', '300033', "", True)
pRisk_3000 = pRisk.getRiskSet('茶叶一主号', '10001965.XSHG', "", True)
pRisk_3100 = pRisk.getRiskSet('茶叶一主号', '10001966.XSHG', "", True)
#消息初始
pMMsg = gol._Get_Setting('manageMsgs')
msg = pMMsg.OnCreatMsg()
msg["usrName"] = "@*股票风控监测群"
msg["msgType"] = "TEXT"
msg["usrPlat"] = "wx"
#循环
dtTime = myData_Trans.Tran_ToDatetime("2019-10-23 09:30:00", "%Y-%m-%d %H:%M:%S")
num = 1
while(True):
#时间参数
dtTime += datetime.timedelta(minutes=1)
dtNow = myData_Trans.Tran_ToDatetime_str(dtTime, "%Y-%m-%d %H:%M")
dtStart = myData_Trans.Tran_ToDatetime(dtNow + ":00", "%Y-%m-%d %H:%M:%S")
dtNext = myData_Trans.Tran_ToDatetime(dtNow + ":59", "%Y-%m-%d %H:%M:%S")
#提取当前期权价格
sources_300033 = pSource.getPrice(security='300033.XSHE',frequency='1m',start_date=dtStart,end_date=dtNext)
sources_3000 = pSource.getPrice(security='10001965.XSHG',frequency='1m',start_date=dtStart,end_date=dtNext)
sources_3100 = pSource.getPrice(security='10001966.XSHG',frequency='1m',start_date=dtStart,end_date=dtNext)
if(len(sources_3100) < 1): continue
priceAvg_300033 = sources_300033['money'][0] / sources_300033['volume'][0]
def Trans_FromDict(self, dictSets, canLog=True):
#验证股票信息
#pStocks = gol._Get_Value('setsStock', None)
#lstStock = pStocks._Find(dictSets.get('标的编号',""), dictSets.get('标的名称',""), exType="")
#if(len(lstStock) != 1): return{}
#pStock = lstStock[0]
#self.stockID = pStock.code_id
#self.stockName = pStock.code_name
#交易信息必须存在
if (dictSets == None): return False
bExsit = False
index = -1
strTime = dictSets.get('操作时间', "")
if (type(strTime) != str):
strTime = myData_Trans.Tran_ToDatetime_str(dictSets['操作时间'],
"%Y-%m-%d %H:%M:%S")
for x in self.logOperates:
index += 1
if (x['时间'] == strTime):
bExsit = True
break
#解析信息
self.ID = dictSets.get('ID', self.ID)
self.usrID = dictSets.get('用户名', self.usrID)
self.usrTag = dictSets.get('用户标签', self.usrTag)
self.stockID = dictSets.get('标的编号', self.stockID)
self.stockName = dictSets.get('标的名称', self.stockName)
self.stockType = dictSets.get('标的类型', self.stockType)
stockNum_temp = myData_Trans.To_Float(str(dictSets.get("标的数量", 0)))
stockAvg_temp = myData_Trans.To_Float(str(dictSets.get("标的均价", 0)))
stockPosition_temp = myData_Trans.To_Float(str(dictSets.get("标的仓位",
1)))
if (stockNum_temp == 0 or stockNum_temp == 0): return False
self.logDatetime = dictSets.get("操作时间", self.logDatetime)
if (type(self.logDatetime) == str):
self.logDatetime = myData_Trans.Tran_ToDatetime(
self.logDatetime, "%Y-%m-%d %H:%M:%S")
self.remark = dictSets.get("备注", self.remark)
self.isDel = dictSets.get('isDel', not self.valid)
if (canLog):
#提取时间
strTime = self.logDatetime
if (type(strTime) != str):
strTime = myData_Trans.Tran_ToDatetime_str(
strTime, "%Y-%m-%d %H:%M:%S")
#存在则更新
if (bExsit == False):
self.logOperates.append({
"股数": stockNum_temp,
"股价": stockAvg_temp,
"时间": strTime
}) #仓位变化记录
else:
self.logOperates[index] = {
"股数": stockNum_temp,
"股价": stockAvg_temp,
"时间": strTime
}
else:
self.logOperates = dictSets.get('操作日志', self.logOperates)
self.sumOperates = dictSets.get('操作统计数', 0)
#计算仓位变化
if (bExsit == False):
stockNum = self.stockNum
if (stockNum_temp > 0):
#买入时更新成本
stockNum += abs(stockNum_temp)
stockMoney = self.stockAvg * self.stockNum + stockNum_temp * stockAvg_temp
self.stockPosition = (
stockNum_temp * stockPosition_temp +
self.stockNum * self.stockPosition) / stockNum
self.stockAvg = stockMoney / stockNum
self.stockNum = int(stockNum)
else:
#卖出更新仓位
if (stockNum == 0):
stockNum = stockNum_temp
self.stockNum = int(stockNum)
self.stockAvg = stockAvg_temp
self.stockPosition = (
stockNum_temp * stockPosition_temp +
self.stockNum * self.stockPosition) / stockNum
if (self.stockPosition <= 0):
self.stockPosition = 0
self.valid = False
self.stockFee = dictSets.get("手续费率", self.stockFee)
self.limitHit = dictSets.get("边界限制", self.limitHit)
self.fixHit = dictSets.get("定量监测", self.fixHit)
self.deltaProfit = dictSets.get("监测间隔", self.deltaProfit)
self.stopProfit = dictSets.get("止盈线", self.stopProfit)
self.stopLoss = dictSets.get("止损线", self.stopLoss)
self.stopProfit_Dynamic = dictSets.get("动态止盈", self.stopProfit_Dynamic)
self.stopLoss_Dynamic = dictSets.get("动态止损", self.stopLoss_Dynamic)
self.stopProfit_Retreat = dictSets.get("止盈回撤", self.stopProfit_Retreat)
self.stopLoss_Retreat = dictSets.get("止损回撤", self.stopLoss_Retreat)
self.stopProfit_Trade = dictSets.get("止盈比例", self.stopProfit_Trade)
self.stopLoss_Trade = dictSets.get("止损比例", self.stopLoss_Trade)
self.priceMax = dictSets.get("最高价格", self.priceMax)
self.priceCost = dictSets.get("成本价格", self.stockAvg)
self.priceAvg_sell = dictSets.get("卖出均价", stockAvg_temp)
self.priceNow = dictSets.get("当前价格", stockAvg_temp)
self.profitMax_Stage = dictSets.get("阶段止盈", self.profitMax_Stage)
self.profitMin_Stage = dictSets.get("阶段止损", self.profitMin_Stage)
self.profitNow = dictSets.get("当前浮盈", self.profitNow)
self.stopProfit_goon = dictSets.get("止盈状态", self.stopProfit_goon)
self.stopLoss_goon = dictSets.get("止损状态", self.stopLoss_goon)
self.date = dictSets.get("建仓日期", self.date).replace("'", "")
if (self.date == ""):
self.date = myData_Trans.Tran_ToDatetime_str(
self.logDatetime, "%Y-%m-%d")
#操盘记录数不一致，更新统计判断
if (self.sumOperates != len(self.logOperates)):
self.Static_Profit(self.priceNow)
return True
def _Trans_Value_Datetime(self, value):
return myData_Trans.Tran_ToDatetime(value, "%Y-%m-%d %H:%M:%S")
def Static(self,
startTime='',
endTime='',
nMonth=1,
tradeParty='',
usrBillType="",
tradeTarget="",
tradeType="",
tradeTypeTarget=""):
if (tradeType != ""):
if (type(startTime) == str and startTime != ""):
startTime = myData_Trans.Tran_ToDatetime(startTime, "%Y-%m-%d")
if (type(endTime) == str and endTime != ""):
endTime = myData_Trans.Tran_ToDatetime(endTime, "%Y-%m-%d")
lstBill, startTime, endTime = self.Query(startTime, endTime,
nMonth, tradeParty,
usrBillType, tradeTarget,
tradeType,
tradeTypeTarget)
else:
#单独查询投资所有
startTime2 = startTime
if (len(self.indLst) > 0):
startTime2 = self._Trans_Time_year(
self._Find(self.indLst[0]).tradeTime)
lstBill2, startTime2, endTime2 = self.Query(
startTime2, endTime, nMonth, tradeParty, usrBillType,
tradeTarget, myTradeType.投资, tradeTypeTarget)
lstBill, startTime, endTime = self.Query(startTime, endTime,
nMonth, tradeParty,
usrBillType, tradeTarget,
tradeType,
tradeTypeTarget, False,
[], [myTradeType.投资])
lstBill = lstBill + lstBill2
#统计项目初始
lstCount = {}
for x in myBileType:
lstCount_Type = {}
lstCount[x] = lstCount_Type
for xx in myTradeType:
lstCount_Type[xx] = {}
#统计
dSum_收益 = 0
for x in lstBill:
lstCount_Bill = lstCount[x.usrBillType]
lstCount_Type = lstCount_Bill[x.tradeType]
lstCount_TypeTarget = lstCount_Type.get(x.tradeTypeTarget, None)
if (lstCount_TypeTarget == None):
lstCount_TypeTarget = {}
lstCount_Type[x.tradeTypeTarget] = lstCount_TypeTarget
dSum = lstCount_TypeTarget.get(x.tradeTarget,
0) + x.tradeMoney #按名称累加
lstCount_TypeTarget[x.tradeTarget] = dSum #子类累加
lstCount_Type["SUM"] = lstCount_Type.get("SUM",
0) + x.tradeMoney #金额累加
lstCount_Bill["SUM"] = lstCount_Bill.get(
"SUM", 0) + x.tradeMoney #金额累加-账单类型
lstCount_Type["SUM_Poundage"] = lstCount_Type.get(
"SUM_Poundage", 0) + x.tradePoundage #金额累加-手续费
lstCount_Bill["SUM_Poundage"] = lstCount_Bill.get(
"SUM_Poundage", 0) + x.tradePoundage #金额累加-手续费-账单类型
#投资卖出，需找到买入
if (x.usrBillType == myBileType.卖出
and x.tradeType == myTradeType.投资):
lstCount_Type["SUM_Profit"] = lstCount_Type.get(
"SUM_Profit", 0) + x.tradeProfit #收益累加
lstCount_Bill["SUM_Profit"] = lstCount_Bill.get(
"SUM_Profit", 0) + x.tradeProfit #收益累加-账单类型
#查询买入源
if (x.tradeID_Relation != ""):
bill = self._Find(int(x.tradeID_Relation))
if (bill != None):
#lstCount_Bill["SUM_投资回笼"] = lstCount_Bill.get("SUM_投资回笼", 0) + x.tradeNum * bill.tradePrice #收益原始投资-账单类型
bExist = False
for xx in lstBill:
if (xx.tradeID == bill.tradeID):
bExist = True
break
if (bExist == False):
lstBill.append(bill)
#转账
dSum_转入 = 0
dSum_转出 = 0
if (lstCount[myBileType.转账][myTradeType.投资].get("转入", None) != None):
dSum_转入 = lstCount[myBileType.转账][myTradeType.投资]["转入"].get(
"现金", 0)
if (lstCount[myBileType.转账][myTradeType.投资].get("转出", None) != None):
dSum_转出 = lstCount[myBileType.转账][myTradeType.投资]["转出"].get(
"现金", 0)
dSum_转帐 = dSum_转入 - dSum_转出
#累加（自下向上）
dSum_In_投资总计 = 0
dSum_In_投资 = lstCount[myBileType.买入][myTradeType.投资].get("SUM", 0)
dSum_Out_投资 = lstCount[myBileType.卖出][myTradeType.投资].get("SUM", 0)
dSum_手续费 = lstCount[myBileType.买入].get(
"SUM_Poundage", 0) + lstCount[myBileType.卖出].get(
"SUM_Poundage", 0)
dSum_分红 = lstCount[myBileType.分红].get("SUM", 0)
dSum_收益 = lstCount[myBileType.卖出].get("SUM_Profit", 0) #已去除手续费
dSum_红包 = lstCount[myBileType.受赠][myTradeType.人际].get("SUM", 0)
dSum_消费 = lstCount[myBileType.买入].get("SUM", 0) - dSum_In_投资
dSum_收入 = lstCount[myBileType.卖出].get("SUM", 0) - dSum_Out_投资
dSum_In = dSum_收入 + lstCount[myBileType.受赠].get("SUM", 0) + dSum_收益
dSum_Out = dSum_消费 + lstCount[myBileType.赠予].get("SUM", 0)
dSum_ALL = dSum_In - dSum_Out + dSum_转帐 + dSum_分红
#输出信息
strPerfix = "\n" + " " * 4
strOut = "账单统计(" + self.usrID + ")："
strOut += "\n" + "总资产：" + str(round(dSum_ALL, 2)) + "元"
if (dSum_红包 > 0):
strOut += strPerfix + "红包收入：" + str(round(dSum_红包, 2)) + "元"
if (dSum_Out_投资 > 0):
dSum_In_投资总计 = dSum_Out_投资 - dSum_In_投资 + dSum_收益 + dSum_分红 #加入分红的钱，收益股价未除权
strOut += strPerfix + "投资收益：" + str(round(dSum_收益, 2)) + "元"
strOut += strPerfix + " " + "手续费：" + str(round(dSum_手续费,
2)) + "元"
strOut += strPerfix + " " + "分红累计：" + str(round(dSum_分红,
2)) + "元"
strOut += strPerfix + " " + "投资累计：" + str(round(dSum_In_投资,
2)) + "元"
strOut += strPerfix + " " + "回笼累计：" + str(
round(dSum_Out_投资 - myData.iif(dSum_收益 < 0, 0, dSum_收益),
2)) + "元"
strOut += strPerfix + " " + "投资总计：" + str(round(
dSum_In_投资总计, 0)) + "元"
if (dSum_Out > 0):
strOut += strPerfix + "消费总计：" + str(round(dSum_Out, 2)) + "元"
#消费细分：
lst消费 = lstCount[myBileType.买入]
for x in lst消费.keys():
if (x == "投资" or x == "SUM"): continue
dSum = lst消费[x].get("SUM", 0)
if (dSum > 0):
strOut += strPerfix + " " + x + "：" + str(round(
dSum, 2)) + "元"
#子类型细分
lst消费类型 = lst消费[x]
for x in lst消费类型.keys():
if (x == "投资" or x == "SUM"): continue
dSum_C = lst消费类型[x].get("SUM", 0)
if (dSum_C > 0):
strOut += strPerfix + " " * 2 + x + "：" + str(
round(dSum_C, 2)) + "元"
#特殊指定类型处理
if (usrBillType != "" and tradeType != ""):
pLst = lstCount[usrBillType][tradeType]
strOut += strPerfix + "总计：" + str(round(pLst['SUM'], 2)) + "元"
strOut += strPerfix + " " + "手续费" + "：" + str(
round(pLst['SUM_Poundage'], 2)) + "元"
for x in pLst.keys():
if (x.count("SUM") == 1): continue
#循环组装所有
keys = pLst[x].keys()
for xx in keys:
strOut += strPerfix + " " + x + xx + "：" + str(
round(pLst[x][xx], 2)) + "元"
else:
if (dSum_转帐 > 0):
strOut += strPerfix + "转账累计：" + str(round(dSum_转帐, 2)) + "元"
strOut += strPerfix + " " + "手续费：" + str(
round(lstCount[myBileType.转账]["SUM_Poundage"], 2)) + "元"
strOut += strPerfix + " " + "转入累计：" + str(round(dSum_转入,
2)) + "元"
strOut += strPerfix + " " + "转出累计：" + str(round(dSum_转出,
2)) + "元"
strOut += strPerfix + " " + "净投资额：" + str(round(dSum_转帐,
2)) + "元"
#当前账目余额
strOut += strPerfix + "现金总计：" + str(
round(dSum_ALL - dSum_In_投资总计, 2)) + "元"
if (usrBillType != ""): strOut += "\n账单类型：" + usrBillType
if (tradeTarget != ""): strOut += "\n交易品名：" + tradeTarget
if (tradeParty != ""): strOut += "\n交易方：" + tradeParty
if (tradeType != ""): strOut += "\n交易品类：" + tradeType
if (tradeTypeTarget != ""): strOut += "\n交易品子类：" + tradeTypeTarget
strOut += "\n账单时间：" + strPerfix + myData_Trans.Tran_ToDatetime_str(
startTime, "%Y-%m-%d") + " 至 " + myData_Trans.Tran_ToDatetime_str(
endTime, "%Y-%m-%d")
return strOut
#消息初始
pMMsg = gol._Get_Setting('manageMsgs')
msg = pMMsg.OnCreatMsg()
msg["usrName"] = "@*股票风控监测群"
msg["msgType"] = "TEXT"
msg["usrPlat"] = "wx"
#循环
#dtTime = myData_Trans.Tran_ToDatetime("2019-10-23 09:30:00", "%Y-%m-%d %H:%M:%S")
num = 1
while(True):
#时间参数
#dtTime += datetime.timedelta(minutes=1)
dtNow = myData_Trans.Tran_ToDatetime_str(None, "%Y-%m-%d %H:%M")
dtStart = myData_Trans.Tran_ToDatetime(dtNow + ":00", "%Y-%m-%d %H:%M:%S")
dtNext = myData_Trans.Tran_ToDatetime(dtNow + ":59", "%Y-%m-%d %H:%M:%S")
#提取当前期权价格
sources_300033 = pSource.getPrice(security='300033.XSHE',frequency='1m',start_date=dtStart,end_date=dtNext)
sources_3000 = pSource.getPrice(security='10001832.XSHG',frequency='1m',start_date=dtStart,end_date=dtNext)
sources_3100 = pSource.getPrice(security='10002033.XSHG',frequency='1m',start_date=dtStart,end_date=dtNext)
if(len(sources_3100) < 1): continue
priceAvg_300033 = sources_300033['money'][0] / sources_300033['volume'][0]
priceAvg_3000 = sources_3000['money'][0] / sources_3000['volume'][0]
priceAvg_3100 = sources_3100['money'][0] / sources_3100['volume'][0]
print(priceAvg_300033, priceAvg_3000, priceAvg_3100, "---", dtStart)
#风险调用
bSave = myData.iif(num % 5 == 0, True, False)
def _Init_TradeDB(self, path):
#提取字段信息
dtDB = myIO_xlsx.DtTable()
dtDB.Load_csv(path, 5, 0, True, 4, ',', isUtf=False)
lstFields = [
"交收日期", "合同号", "资金账号", "股东代码", "证券代码", "证券名称", "交易类别", "成交价格",
"成交数量", "证券余额", "成交金额", "资金发生数", "资金余额", "费用合计", "净佣金", "规费",
"印花税", "过户费", "经手费", "清算费", "前台费用", "交易规费", "证管费", "币种", "交易市场"
]
if (dtDB.sheet == None): dtDB.dataField = lstFields
lstFields_ind = dtDB.Get_Index_Fields(lstFields)
#提取交易记录
pBills = self.billManager._Find("Stock_" + self.usrID, True)
#装载账单记录
nInd = 0
for nTimes in range(0, 1):
for dtRow in dtDB.dataMat:
#解析有效数据内容
bill = myManager_Bill.myObj_Bill()
bill.usrID = self.usrID
bill.recorder = self.usrID
bill.tradeParty = dtRow[lstFields_ind["交易市场"]]
bill.tradeType = "投资"
bill.tradeTypeTarget = "股票"
bill.tradeTarget = dtRow[lstFields_ind["证券名称"]]
bill.tradePrice = float(dtRow[lstFields_ind["成交价格"]])
bill.tradeNum = int(dtRow[lstFields_ind["成交数量"]])
bill.tradeMoney = float(dtRow[lstFields_ind["成交金额"]])
bill.tradePoundage = float(dtRow[lstFields_ind["费用合计"]])
bill.tradeTime = myData_Trans.Tran_ToDatetime(
dtRow[lstFields_ind["交收日期"]],
"%Y%m%d") + datetime.timedelta(seconds=nInd * 10)
nInd = nInd + 1
#区分类型，部分类型屏蔽
strType = dtRow[lstFields_ind["交易类别"]]
if (strType.count('买入') == 1 or strType.count('配售缴款')):
bill.usrBillType = '买入'
elif (strType.count('配股入帐') == 1):
bill.usrBillType = '买入'
bill.tradePrice = bill.tradeMoney / bill.tradeNum
bill.tradePoundage = 0
elif (strType.count('卖出') == 1):
bill.usrBillType = '卖出'
elif (strType.count('银行转证券') == 1):
bill.usrBillType = '转账'
bill.tradeTypeTarget = "转入"
bill.tradeTarget = "现金"
bill.tradeParty = "券商"
bill.tradeMoney = float(dtRow[lstFields_ind["资金发生数"]])
elif (strType.count('证券转银行') == 1):
bill.usrBillType = '转账'
bill.tradeTypeTarget = "转出"
bill.tradeTarget = "现金"
bill.tradeParty = "券商"
bill.tradeMoney = abs(float(dtRow[lstFields_ind["资金发生数"]]))
elif (strType.count('融券回购') == 1):
bill.usrBillType = '买入'
bill.tradeTypeTarget = "国债逆回购"
elif (strType.count('融券购回') == 1):
bill.usrBillType = '卖出'
bill.tradeTypeTarget = "国债逆回购"
bill.tradeMoney = float(dtRow[lstFields_ind["资金发生数"]])
elif (strType.count('利息归本') == 1
or strType.count('利息税代扣') == 1):
bill.usrBillType = '分红'
bill.tradeTypeTarget = "活期"
bill.tradeTarget = "利息"
bill.tradeParty = "券商"
bill.tradeMoney = float(dtRow[lstFields_ind["资金发生数"]])
elif (strType.count('红利入账') == 1):
bill.usrBillType = '分红'
if (bill.tradeNum != 0):
pass #价格变动。。
bill.tradeMoney = float(dtRow[lstFields_ind["资金发生数"]])
else:
continue
#部分特殊类型名称转换
if (bill.usrBillType == "卖出"):
if (bill.tradeTarget.count("转债") == 1):
bill.tradeTarget = bill.tradeTarget.replace("转债", "发债")
if (bill.tradeTarget.count("发债") == 1):
bill.tradeTypeTarget = "可转债"
if (bill.tradeTarget.count("发债") == 1):
bill.tradeTypeTarget = "可转债"
#@@Test
if (bill.usrBillType == "卖出"
and bill.tradeTarget.count("五粮") == 1):
aa = 1
#添加账单信息
strReturn = pBills._Add(bill)
myDebug.Print(strReturn)
def _Trans_Value_Datetime(self, value):
if (value.count(":") == 2):
return myData_Trans.Tran_ToDatetime(value)
return myData_Trans.Tran_ToDatetime(value, "%Y-%m-%d")
def initParam(self, param):
errLst = []
self.modeState = -1
if (True):
self.tag = param.get('tag', "")
dictInfo_Leak = param.get("infoLeak")
self.longitude_Leak = dictInfo_Leak.get('longitude', "")
self.latitude_Leak = dictInfo_Leak.get('latitude', "")
self.height_Leak = dictInfo_Leak.get('height_leak', "")
self.massrate_Leak = dictInfo_Leak.get('massrate_leak', "")
self.dtLeak = myData_Trans.Tran_ToDatetime(
dictInfo_Leak.get('timestart_leak', ""))
dictInfo_Chimney = dictInfo_Leak.get("chimney", '')
self.hasChimney = dictInfo_Chimney != ""
if (self.hasChimney):
self.chimney_diameter = dictInfo_Chimney.get('diameter', "")
self.chimney_temperature_outlet = dictInfo_Chimney.get(
'temperature_outlet', "")
self.chimney_smoke_speed_outlet = dictInfo_Chimney.get(
'smoke_speed_outlet', "")
self.chimney_wind_speed_outlet = dictInfo_Chimney.get(
'wind_speed_outlet', "")
if (self.chimney_diameter == ""): errLst.append('diameter')
if (self.chimney_temperature_outlet == ""):
errLst.append('temperature_outlet')
if (self.chimney_smoke_speed_outlet == ""):
errLst.append('smoke_speed_outlet')
if (self.longitude_Leak == ""): errLst.append('longitude')
if (self.latitude_Leak == ""): errLst.append('latitude')
if (self.height_Leak == ""): errLst.append('height_leak')
if (self.massrate_Leak == ""): errLst.append('massrate_leak')
self.infoTargets = []
dictInfo_Targets = param.get("infoTarget")
for x in dictInfo_Targets:
id_Target = x.get('id', "")
longitude_Target = x.get('longitude', "")
latitude_Target = x.get('latitude', "")
height_Target = x.get('height', "")
self.infoTargets.append([
id_Target, longitude_Target, latitude_Target, height_Target
])
if (id_Target == ""): errLst.append('id')
if (longitude_Target == ""): errLst.append('longitude')
if (latitude_Target == ""): errLst.append('latitude')
if (height_Target == ""): errLst.append('height')
dictInfo_Evn = param.get("infoEnvironment")
wind_speed = dictInfo_Evn.get('wind_speed', "")
wind_direction = dictInfo_Evn.get('wind_direction', "")
wind_height = dictInfo_Evn.get('wind_height', "")
air_Stability = dictInfo_Evn.get('air_stability', "")
temperature = dictInfo_Evn.get('temperature', "")
cloudy_is = dictInfo_Evn.get('cloudy_is', "")
if (wind_speed == ""): errLst.append('wind_speed')
if (wind_direction == ""): errLst.append('wind_direction')
if (wind_height == ""): errLst.append('wind_height')
if (temperature == ""): errLst.append('temperature')
if (cloudy_is == ""): errLst.append('cloudy_is')
#参数检查
if (len(errLst) > 0):
return False
#初始环境对象
self.wind.initWind(wind_direction, wind_speed, wind_height,
self.dtLeak, -1)
self.sun.initSun_Infos(self.longitude_Leak, self.latitude_Leak,
self.dtLeak, myData.iif(cloudy_is, "多云", ""))
self.air.initAir_Stability(air_Stability, self.wind.wind_Speed,
self.sun.level_Radiation, temperature)
#记录参数及标识状态
self.modelParam = param
self.modeState = 0
return True
def _Done_Image(self, Text, msgID="", usrInfo={}):
#图片判别，只处理手机截图（图片行列比）
#提取图片内容,ORC通用识别
#Text = "E:\\myCode\\zxcProj\\src\\Zxc.Python\\zxcPy.All.Base\\Temps\\Images\\Test.png"
txtInfo = myAI_Baidu.ORC(Text, "", out_debug=False)
myDebug.Debug(str(txtInfo))
#按文字内容组合定义图片类型
dictInfos = {'收益率': "", '日期': ""}
num = txtInfo['wordText'].count('资产分析')
if (num >= 1):
# 使用文字匹配方式解析
year = myData_Trans.Tran_ToTime_str(None, "%Y")
if (txtInfo['wordText'].count('同花顺-资产分析') == 1): #同花顺截图
#'u中国联通令\n下午3:10\n64%\n同花顺-资产分析\n2019-01-01~2019-08-27\n分享\n本月\n近三月\n近半年\n今年\n近两年\n30.0%\n10.0%\n0.0%\n-10.0%\n01-01\n04-01\n07-01\n我上证○深证○创业板○上证50\nC沪深30中证500收益走势\n今年跑嬴上证指数\n23.03%\n我\n3940%\n上证\n16.37%\n深证\n30.43%\n创业板\n30.19%'
ind = txtInfo['words'].index('我')
if (ind > 0):
txt = txtInfo['words'][ind + 1]
dictInfos['收益率'] = float(txt.replace('%', "")) / 100
if (txt.count('.') == 0):
dictInfos['收益率'] = dictInfos['收益率'] / 100 #小数点未正确识别修正
# 提取日期
lst = [n for n in txtInfo['words'] if n.count(year) == 2]
if (len(lst) == 1):
times = lst[0].split('~')
if (times[0][0:10] == year + "-01-01"): #日期校检，必须当年开始
dictInfos['日期'] = myData_Trans.Tran_ToDatetime(
times[1], '%Y-%m-%d')
pass
else: #君弘截图
#'10:09:1l\n(80\n资产分析\n20190101~20190828\n今年收益率17.48%\n今日本月近三个月近半年今年2018\n30%\n20%\n2019.01.31\n我:-0.11\n10%\n上证:3.64%\n10%\n01.31\n03.29\n05.31\n07.31\n●我○上证深证○创业\n1.46%\n跑赢上证\n1.46%\n跑输深证\n-12.56%\n跑输创业\n-12.47%\n资产分析\n证券分析\n月度分析\n账单'
# 提取今年收益率
lst = [n for n in txtInfo['words'] if n.count('今年收益率') == 1]
if (len(lst) == 1):
txt = lst[0]
dictInfos['收益率'] = float(
txt.replace('今年收益率', "").replace('%', "")) / 100
if (txt.count('.') == 0):
dictInfos['收益率'] = dictInfos['收益率'] / 100 #小数点未正确识别修正
# 提取日期
lst = [n for n in txtInfo['words'] if n.count(year) == 2]
if (len(lst) == 1):
times = lst[0].split('~')
if (times[0][0:8] == year + "0101"): #日期校检，必须当年开始
dictInfos['日期'] = myData_Trans.Tran_ToDatetime(
times[1], '%Y%m%d')
pass
if (dictInfos['收益率'] == 0): return ""
# 修正日期为字符串、收益率格式等
usrName = usrInfo.get('usrNameNick', "")
usrProfit = dictInfos['收益率']
if (dictInfos.get('日期', "") != ""):
dictInfos['日期-前'] = myData_Trans.Tran_ToDatetime_str(
dictInfos['日期'] + datetime.timedelta(days=1), '%Y-%m-%d')
dictInfos['日期'] = myData_Trans.Tran_ToDatetime_str(
dictInfos['日期'], '%Y-%m-%d')
if (dictInfos.get('收益率', "") != ""):
dictInfos['收益率'] = str(
Decimal((usrProfit * 100)).quantize(Decimal('0.00'))) + "%"
#记录信息
pDB = gol._Get_Setting('zxcdbStockReturns')
lstQuery = pDB.Query("isDel==False && 日期>=" + dictInfos['日期-前'],
"日期", True)
if (len(lstQuery) > 0): return "" #必须比已有日期大
myDebug.Debug(
pDB.Add_Row(
{
'用户名': usrName,
'收益': usrProfit,
'日期': dictInfos['日期']
}, True))
#组装返回
lstR = pDB.Get_Ranks(usrName, True)
if (len(lstR) < 1):
return "@" + usrName + " 收益信息记录失败！当前收益率：" + dictInfos[
'收益率'] + "."
dicRand = lstR[0]
strRank = " 您的收益排名：第 " + dicRand['ranking'] + ", 收益率：" + dicRand[
'profit'] + " "
return "@" + usrName + " " + strRank
return ""
# 循环剔除重复
dictDCC = {}
lstRows = []
rows = pTable._Rows()
for i in range(0, rows):
# 忽略已处理用户
row = pTable[i]
usrID = row[indFields['车架号']]
if (dictDCC.get(usrID, None) != None):
continue
# 处理（循环所有，统计呼叫成功数、失败数）
nTimes = 0
nSuccees = 0
dt_S = myData_Trans.Tran_ToDatetime("1999/9/9 00:00:00",
"%Y/%m/%d %H:%M:%S")
for j in range(i, rows):
x = pTable[j]
if (x[indFields['车架号']] != usrID):
continue
# 保留最近时间
dt = myData_Trans.Tran_ToDatetime(x[indFields['开单日期']],
"%Y/%m/%d %H:%M:%S")
if (dt_S < dt):
dt_S = dt
row = pTable[j]
lstRows.append(row)
dictDCC[usrID] = row
dictDCC2 = {}
