class ClassifiedData(object):
'''新浪行业分类指数的构造'''
def __init__(self):
self.initialize()
self.main()
def initialize(self):
# 初始化日志服务
self.initLogging()
# 数据库连接，连接配置可在tool文件中修改
self.con = Connection().getConnection()
self.cur = self.con.cursor()
def main(self):
classifiedDict = self.getClassifiedDict()
for key in classifiedDict:
self.createClassifiedData(key,classifiedDict[key])
#------------------------------------------------------------------------------
def initLogging(self):
'''初始化日志对象'''
logging.basicConfig(level=logging.INFO,
format='%(asctime)-15s %(lineno)-6d %(funcName)-30s %(message)s',
datefmt='%m-%d %H:%M:%S',
filename=r'D:\classifiedData.txt',
filemode='w')
def getClassifiedDict(self):
classifiedDict = collections.defaultdict(list)
sql = 'select symbol,industryname from industryclassified'
self.cur.execute(sql)
for record in self.cur.fetchall():
symbol = u'SH' + record[0] if record[0][0] in ['5','6'] else u'SZ' + record[0]
classifiedDict[record[1]].append(symbol)
return classifiedDict
def createClassifiedData(self,classifiedName,symbolList):
'''生成行业的指数，从2007-01-01开始'''
stockDataList = []
firstDataList = []
insertDataList = []
firstDay = datetime.date(2007,1,4)
sql = 'select date,openprice,highprice,lowprice,closeprice from stockdata_day_tdx where symbol = "%s" and date >= "2007-01-01" order by date'
for symbol in symbolList:
stockData = []
self.cur.execute(sql % symbol)
for record in self.cur.fetchall():
stockData.append(list(record))
if not stockData: continue
stockData = np.array(stockData)
stockDataDict = {'openprice':stockData[:,1],'highprice':stockData[:,2],'lowprice':stockData[:,3],
'closeprice':stockData[:,4]}
stockDataFrame = pd.DataFrame(stockDataDict,index=stockData[:,0],columns=['openprice','highprice','lowprice',
'closeprice'])
if firstDay in stockDataFrame.index:
firstDataList.append(stockDataFrame.ix[firstDay].values)
# 存放该行业的所有的股票数据
stockDataFrame = (stockDataFrame / stockDataFrame.shift(1) - 1).dropna()
stockDataList.append(stockDataFrame)
# 获取第一天的数据
firstDataList = np.array(firstDataList)
firstOpen = 1000
firstHigh = round(firstDataList[:,1].sum() / firstDataList[:,0].sum() * 1000,2)
firstLow = round(firstDataList[:,2].sum() / firstDataList[:,0].sum() * 1000,2)
firstClose = round(firstDataList[:,3].sum() / firstDataList[:,0].sum() * 1000,2)
insertDataList.append([classifiedName,firstDay,firstOpen,firstHigh,firstLow,firstClose])
# 获得其它日期的数据
dateList = [dataDate.to_datetime().date() for dataDate in pd.date_range('2007-01-04',datetime.date.today(),freq='B')]
dataDict = {dataDate:[stockDataFrame.ix[dataDate].values for stockDataFrame in stockDataList if dataDate in stockDataFrame.index] for dataDate in dateList}
for key in sorted(dataDict.keys()):
yesterdayData = insertDataList[-1]
if not dataDict[key]: continue
otherDayData = np.array(dataDict[key])
otherOpen = round(yesterdayData[2] * (1 + otherDayData[:,0].mean()),2)
otherHigh = round(yesterdayData[3] * (1 + otherDayData[:,1].mean()),2)
otherLow = round(yesterdayData[4] * (1 + otherDayData[:,2].mean()),2)
otherClose = round(yesterdayData[5] * (1 + otherDayData[:,3].mean()),2)
insertDataList.append([classifiedName,key,otherOpen,otherHigh,otherLow,otherClose])
sql = 'insert ignore into classifieddata value(' + '%s,' * 5 + '%s)'
self.cur.executemany(sql,tuple(insertDataList))
self.con.commit()
class StockData():
'''获得股票数据'''
def __init__(self):
self.initialize()
self.main()
def initialize(self):
w.start()
self.initLogging()
self.con = Connection().getConnection()
self.cur = self.con.cursor()
def main(self):
self.historyWindData() # 历史数据，日线和分钟线
self.updateWindCode() # 更新A股的代码
self.currentWindData() # 每日的更新
self.close()
#------------------------------------------------------------------------------ init
def initLogging(self):
'''初始化日志对象'''
logging.basicConfig(level=logging.INFO,
format='%(asctime)-15s %(lineno)-6d %(funcName)-30s %(message)s',
datefmt='%m-%d %H:%M:%S',
filename=r'D:\log_windData.txt',
filemode='w')
#------------------------------------------------------------------------------ historyData
def historyWindData(self):
'''得到历史数据'''
stockCodeList = self.getStockCode() # 股票代码
fields = {'d':['pre_close','open','high','low','close','volume','amt','pct_chg'],
'm':['open','high','low','close','volume','amt','pct_chg']}
startDate = {'d':'20050101','m':'2014-01-01 09:30:00'}
endDate = {'d':datetime.date.today().strftime('%Y%m%d'),'m':datetime.date.today().strftime('%Y-%m-%d')+' 15:00:00'}
# day
self.getDayData(stockCodeList,fields['d'],startDate['d'],endDate['d'],option='PriceAdj=F')
# min
for period in [5,15,30,60]:
self.getMinData(stockCodeList,fields['m'],startDate['m'],endDate['m'],period)
def getDayData(self,stockCodeList,fields,startDate,endDate,option):
'''日数据的具体的获取步骤'''
for stockCode in stockCodeList:
print '添加日数据,代碼%s' % stockCode
wsd_data = w.wsd(stockCode,fields,startDate,endDate,option)
if wsd_data.ErrorCode==0: # 返回成功
stockDate = wsd_data.Times
dateList = [date.strftime("%Y-%m-%d") for date in stockDate]
stockDataDict = {'stockCode':stockCode,'date':dateList}
for i in range(len(fields)):
stockDataDict[fields[i]] = wsd_data.Data[i]
stockData = pd.DataFrame(stockDataDict,columns=['stockCode','date']+fields,index=dateList).dropna() # 只要有缺失的数据就删掉这一行，保证数据最为干净
stockData['pct_chg'] = stockData['pct_chg'] / 100 # 让涨幅变为实际涨幅（查询出来的是百分比数据）
# 插入到數據庫中
sql = "insert ignore into stockdata_day values(" + "%s,"*(len(fields)+1)+"%s)"
self.cur.executemany(sql,tuple(stockData.values.tolist()))
self.con.commit()
else:
logging.info('ERROR-%s-day數據下載失敗，錯誤代碼為：%s' % (stockCode,wsd_data.ErrorCode))
def getMinData(self,stockCodeList,fields,startDate,endDate,period):
'''分钟线的具体的获取步骤'''
option = 'BarSize=%s;PriceAdj=F' % period
for stockCode in stockCodeList:
print '添加%s 分钟数据,代碼%s' % (period,stockCode)
wsi_data = w.wsi(stockCode,fields,startDate,endDate,option)
if wsi_data.ErrorCode==0: # 返回成功
stockDate = wsi_data.Times
timeList = [time.strftime("%Y-%m-%d %H-%M-%S") for time in stockDate]
stockDataDict = {'stockCode':stockCode,'time':timeList}
for i in range(len(fields)):
stockDataDict[fields[i]] = wsi_data.Data[i]
stockData = pd.DataFrame(stockDataDict,columns=['stockCode','time']+fields,index=timeList).dropna() # 只要有缺失的数据就删掉这一行，保证数据最为干净
stockData['pct_chg'] = stockData['pct_chg'] / 100 # 让涨幅变为实际涨幅（查询出来的是百分比数据）
# 插入到數據庫中
sql = "insert ignore into stockData_%smin" % period + " values("+"%s,"*(len(fields)+1)+"%s)"
self.cur.executemany(sql,tuple(stockData.values.tolist()))
self.con.commit()
else:
logging.info('ERROR-%s歷史分鐘%smin數據下載失敗' % (stockCode,period))
def updateWindCode(self):
'''更新股票代码'''
today = date.today().strftime('%Y%m%d')
field = 'wind_code,sec_name' # 字段名：股票代码和股票名称
sector = '全部A股'
option = 'date=%s;sector=%s;field=%s' % (today,sector,field)
wset_data = w.wset('SectorConstituent',option)
if wset_data.ErrorCode == 0:
stockCodeData = zip(wset_data.Data[0],wset_data.Data[1]) # 返回值data[0],data[1]分别为代码和名称
sql = "delete from stockCode"
self.cur.execute(sql)
self.con.commit()
print '删除代码完毕'
# 插入到数据库中
sql = "insert ignore into stockCode values(%s,%s)"
self.cur.executemany(sql,tuple(stockCodeData))
self.con.commit()
else:
logging.info('ERROR-股票代码更新错误')
print '更新代码完毕'
#------------------------------------------------------------------------------ currentData
def currentWindData(self):
'''更新数据'''
stockCodeList = self.getStockCode()
reRightCode = self.getUpdateCode(stockCodeList)
self.reRightData(reRightCode) # 复权数据
self.insertTodayData(stockCodeList) # 插入今天数据
def getUpdateCode(self,stockCodeList):
'''得到直接插入和复权的代码'''
reRightCode = [] # 需要復權的股票
# 得到数据库中最新一天的收盘价
closeList = []
for code in stockCodeList:
sql = "select close from stockData_day where stockCode = %s order by date desc limit 1"
self.cur.execute(sql,code)
result = self.cur.fetchone()
if not result:
closeList.append(0.0)
else:
closeList.append(result[0])
# 查找今天的數據
fields = ['pre_close']
today = datetime.date.today().strftime('%Y%m%d') #今天的日期
option = 'showblank=0.0;PriceAdj=F' # 要進行前復權處理
wsd_data = w.wsd(stockCodeList,fields,today,today,option)
if wsd_data.ErrorCode==0: # 返回成功
stockData = wsd_data.Data[0]
ifEqualList = (np.array(stockData) == np.array(closeList))
for i in range(len(ifEqualList)):
if not ifEqualList[i]:
rate = (stockData[i] - closeList[i]) / closeList[i]
reRightCode.append([stockCodeList[i],rate])
print '需要复权的数量为'
print len(reRightCode)
print '需要复权的股票代码为：'
print reRightCode
logging.info('需要复权的股票代码为：%s' % reRightCode)
return reRightCode
def reRightData(self,reRightCode):
'''复权数据'''
print '开始复权数据'
code = [record[0] for record in reRightCode]
rate = [record[1] for record in reRightCode]
paraList = []
for i in range(len(reRightCode)):
paraList.append((rate[i],)*6 + (code[i],))
sql = 'update stockData_day set '+\
'pre_close=pre_close*(1+%s),open=open*(1+%s),high=high*(1+%s),low=low*(1+%s),close=close*(1+%s),amt=amt*(1+%s)' +\
" where stockCode=%s"
self.cur.executemany(sql,paraList)
self.con.commit()
print '日线复权完毕'
paraList = []
for i in range(len(reRightCode)):
paraList.append((rate[i],)*5 + (code[i],))
for period in [5,15,30,60]:
sql = 'update stockData_%smin ' % period + \
'set open=open*(1+%s),high=high*(1+%s),low=low*(1+%s),close=close*(1+%s),amt=amt*(1+%s)' + \
" where stockCode=%s"
self.cur.executemany(sql,paraList)
self.con.commit()
print '分钟线复权完毕'
def insertTodayData(self,stockCodeList):
'''插入当天的数据'''
fields = {'d':['pre_close','open','high','low','close','volume','amt','pct_chg'],
'm':['open','high','low','close','volume','amt','pct_chg']}
startDate = {'d':datetime.date.today().strftime('%Y%m%d'),'m':datetime.date.today().strftime('%Y-%m-%d')+' 09:30:00'}
endDate = {'d':datetime.date.today().strftime('%Y%m%d'),'m':datetime.date.today().strftime('%Y-%m-%d')+' 15:00:00'}
# day
self.getDayData(stockCodeList,fields['d'],startDate['d'],endDate['d'],option='PriceAdj=F')
# min
for period in [5,15,30,60]:
self.getMinData(stockCodeList,fields['m'],startDate['m'],endDate['m'],period)
def getStockCode(self):
'''获得股票代码'''
sql = 'select distinct stockCode from stockCode'
self.cur.execute(sql)
stockCodeList = []
for code in self.cur.fetchall():
stockCodeList.append(code[0])
return stockCodeList
def close(self):
'''關閉數據庫'''
self.con.close()
self.cur.close()
class ClassifiedData(object):
'''新浪行业分类指数的构造'''
def __init__(self):
self.initialize()
self.main()
def initialize(self):
# 初始化日志服务
self.initLogging()
# 数据库连接，连接配置可在tool文件中修改
self.con = Connection().getConnection()
self.cur = self.con.cursor()
def main(self):
classifiedDict = self.getClassifiedDict()
for key in classifiedDict:
self.createClassifiedData(key, classifiedDict[key])
#------------------------------------------------------------------------------
def initLogging(self):
'''初始化日志对象'''
logging.basicConfig(
level=logging.INFO,
format='%(asctime)-15s %(lineno)-6d %(funcName)-30s %(message)s',
datefmt='%m-%d %H:%M:%S',
filename=r'D:\classifiedData.txt',
filemode='w')
def getClassifiedDict(self):
classifiedDict = collections.defaultdict(list)
sql = 'select symbol,industryname from industryclassified'
self.cur.execute(sql)
for record in self.cur.fetchall():
symbol = u'SH' + record[0] if record[0][0] in [
'5', '6'
] else u'SZ' + record[0]
classifiedDict[record[1]].append(symbol)
return classifiedDict
def createClassifiedData(self, classifiedName, symbolList):
'''生成行业的指数，从2007-01-01开始'''
stockDataList = []
firstDataList = []
insertDataList = []
firstDay = datetime.date(2007, 1, 4)
sql = 'select date,openprice,highprice,lowprice,closeprice from stockdata_day_tdx where symbol = "%s" and date >= "2007-01-01" order by date'
for symbol in symbolList:
stockData = []
self.cur.execute(sql % symbol)
for record in self.cur.fetchall():
stockData.append(list(record))
if not stockData: continue
stockData = np.array(stockData)
stockDataDict = {
'openprice': stockData[:, 1],
'highprice': stockData[:, 2],
'lowprice': stockData[:, 3],
'closeprice': stockData[:, 4]
}
stockDataFrame = pd.DataFrame(
stockDataDict,
index=stockData[:, 0],
columns=['openprice', 'highprice', 'lowprice', 'closeprice'])
if firstDay in stockDataFrame.index:
firstDataList.append(stockDataFrame.ix[firstDay].values)
# 存放该行业的所有的股票数据
stockDataFrame = (stockDataFrame / stockDataFrame.shift(1) -
1).dropna()
stockDataList.append(stockDataFrame)
# 获取第一天的数据
firstDataList = np.array(firstDataList)
firstOpen = 1000
firstHigh = round(
firstDataList[:, 1].sum() / firstDataList[:, 0].sum() * 1000, 2)
firstLow = round(
firstDataList[:, 2].sum() / firstDataList[:, 0].sum() * 1000, 2)
firstClose = round(
firstDataList[:, 3].sum() / firstDataList[:, 0].sum() * 1000, 2)
insertDataList.append([
classifiedName, firstDay, firstOpen, firstHigh, firstLow,
firstClose
])
# 获得其它日期的数据
dateList = [
dataDate.to_datetime().date() for dataDate in pd.date_range(
'2007-01-04', datetime.date.today(), freq='B')
]
dataDict = {
dataDate: [
stockDataFrame.ix[dataDate].values
for stockDataFrame in stockDataList
if dataDate in stockDataFrame.index
]
for dataDate in dateList
}
for key in sorted(dataDict.keys()):
yesterdayData = insertDataList[-1]
if not dataDict[key]: continue
otherDayData = np.array(dataDict[key])
otherOpen = round(
yesterdayData[2] * (1 + otherDayData[:, 0].mean()), 2)
otherHigh = round(
yesterdayData[3] * (1 + otherDayData[:, 1].mean()), 2)
otherLow = round(
yesterdayData[4] * (1 + otherDayData[:, 2].mean()), 2)
otherClose = round(
yesterdayData[5] * (1 + otherDayData[:, 3].mean()), 2)
insertDataList.append([
classifiedName, key, otherOpen, otherHigh, otherLow, otherClose
])
sql = 'insert ignore into classifieddata value(' + '%s,' * 5 + '%s)'
self.cur.executemany(sql, tuple(insertDataList))
self.con.commit()
class StockData():
'''通过通达信导出的txt文件，更新日线和分钟级数据'''
def __init__(self):
self.initialize()
self.main()
def initialize(self):
# 初始化日志服务
self.initLogging()
# 初始化路径值
self.initPath()
# 数据库连接，连接配置可在tool文件中修改
self.con = Connection().getConnection()
self.cur = self.con.cursor()
def main(self):
# 读入历史数据，只是第一次导入数据库时需要运行，以后每天更新即可。
self.historyData()
# self.currentData() # 更新數據庫的數據，每天运行
self.close()
#------------------------------------------------------------------------------ initialize
def initLogging(self):
'''初始化日志对象'''
logging.basicConfig(
level=logging.INFO,
format='%(asctime)-15s %(lineno)-6d %(funcName)-30s %(message)s',
datefmt='%m-%d %H:%M:%S',
filename=r'D:\tdxData.txt',
filemode='w')
def initPath(self):
'''初始化各种读入文件的路径名，包括历史的日数据，分钟数据路径；当天的收盘价和前收的对比数据路径，以及当天的日数据和分钟数据的路径名'''
self.historyDayPath = r'C:\Users\Administrator\Desktop\tdx\historyDayData' #历史日数据文件的路径，会把当前路径的数据全部写入数据库
self.historyMinPath = r'C:\Users\Administrator\Desktop\tdx\historyMinData' #历史分钟数据文件的路径，会把当前路径的数据全部写入数据库，并相应生成15,30,60数据
self.checkDataPath = r'C:\Users\Administrator\Desktop\tdx\checkData' #收盘价和前收的对比文件路径，也就是通过公式导出的文件的路径，该路径只应该存在最新的对比文件
self.currentMinPath = r'C:\Users\Administrator\Desktop\tdx\currentMinData' #当天分钟级的数据，并相应形成15,30,60数据
#------------------------------------------------------------------------------ history
def historyData(self):
'''读入历史数据'''
# self.getDayData()
self.getMinData()
def getDayData(self):
'''读入日线数据'''
# 得到文件夹下面所有txt结尾的文件路径
fileNameList = self.getFileNameList(
self.historyDayPath) # 内容是文件名，不包括前面的路径
filePathList = [
os.path.join(self.historyDayPath, fileName)
for fileName in fileNameList
]
symbolList = [fileName.split('.')[0] for fileName in fileNameList]
# 循环每个文件写入数据库
for i in range(len(fileNameList)):
stockFile = open(filePathList[i])
fileContent = stockFile.readlines()[:-1]
stockFile.close()
if len(fileContent) == 0: continue
# 读取数据
stockDataList = []
for row in fileContent:
rowData = row.strip().split('\t')
valueData = np.array([float(item) for item in rowData[1:]])
if all(valueData == 0.0): continue # 全部为0.证明该股票还未上市操作
if len(rowData) == 7: # 查看了海信在6-15日停牌的情况，停牌的数据没有包含在下载的文件中。
rowData.insert(0, symbolList[i])
stockDataList.append(rowData)
# 将这只股票的数据写入数据库
sql = "insert ignore into stockData_day_tdx values(" + "%s," * 7 + "%s)" # 一共有8列数据
self.cur.executemany(sql, tuple(stockDataList))
self.con.commit()
print '%s日线数据写入完毕' % symbolList[i]
print '全部日线数据写入完毕'
def getMinData(self):
'''读入分钟数据'''
# 得到文件夹下面所有txt结尾的文件路径
fileNameList = self.getFileNameList(
self.historyMinPath) # 内容是文件名，不包括前面的路径
filePathList = [
os.path.join(self.historyMinPath, fileName)
for fileName in fileNameList
]
symbolList = [fileName.split('.')[0] for fileName in fileNameList]
# 循环每个文件写入数据库
for i in range(len(fileNameList)):
# 读取文件,从第一行读取（不导出头文件）
stockFile = open(filePathList[i])
fileContent = stockFile.readlines()[:-1]
stockFile.close()
if len(fileContent) == 0: continue
# 读取数据
stockDataList5 = []
for row in fileContent:
rowData = row.strip().split('\t')
stockTime = '%s %s:%s:00' % (rowData[0], rowData[1][:-2],
rowData[1][-2:])
rowData[0:2] = [stockTime]
valueData = np.array([float(item) for item in rowData[1:]])
if all(valueData == 0.0): continue # 全部为0.证明该股票还未上市操作
if len(rowData) == 7: # 查看了海信在6-15日停牌的情况，停牌的数据没有包含在下载的min文件中。
rowData.insert(0, symbolList[i])
stockDataList5.append(rowData)
# 找到其他周期的数据
stockDataList15 = stockDataList5[2::3]
stockDataList30 = stockDataList15[1::2]
stockDataList60 = [
item for item in stockDataList30 if item[1].endswith('00:00')
]
# 将这只股票的数据写入数据库
for period in [5, 15, 30, 60]:
sql = "insert ignore into stockData_%smin_tdx" % period + " values(" + "%s," * 7 + "%s)"
self.cur.executemany(sql,
tuple(eval("stockDataList%s" % period)))
self.con.commit()
print '%s分钟线数据写入完毕' % symbolList[i]
print '全部分钟线数据写入完毕'
#------------------------------------------------------------------------------current
def currentData(self):
'''复权，更新当天的数据'''
stockCodeList = self.getStockCode()
reRightCode, stockDataList = self.getUpdateCode(stockCodeList)
self.reRightData(reRightCode) # 复权数据
self.insertDayData(stockDataList) # 插入今天日线数据
self.insertMinData() # 插入今天分钟线数据
def getUpdateCode(self, stockCodeList):
'''獲得不同情況下更新的股票代碼'''
reRightCode = [] # 需要復權的股票和复权因子的列表
# 得到数据库中最新一天的收盘价
closeDict = {} # 股票代码：收盘价
for code in stockCodeList:
sql = "select ClosePrice from stockdata_day_tdx where Symbol = %s order by date desc limit 1"
self.cur.execute(sql, code)
result = self.cur.fetchone()
closeDict[code] = result[0]
# 查找今天的數據
fileName = self.getFileNameList(self.checkDataPath)[0]
path = r'%s/%s' % (self.checkDataPath, fileName)
stockFile = open(path)
fileContent = stockFile.readlines()[2:-1] # 去掉最后一行
stockFile.close()
rowDataList = []
for row in fileContent:
rowData = [item.strip() for item in row.strip().split('\t')]
if len(rowData) != 11 or (rowData[3] == '0') or (rowData[4]
== '0'):
continue # 不等于11列则该股票还未上市，rowData[3]为空证明停牌，停牌不用复权
rowData[0] = rowData[0].replace('=', '')
rowData[0] = rowData[0].replace('"', '')
rowDataList.append(rowData)
# 由文件数据转化成结构数据
print len(rowDataList)
stockDataList = self.formatStockData(rowDataList)
for stockData in stockDataList:
symbol = stockData[0]
if symbol not in closeDict: continue
closePrice = closeDict[symbol] # 得到数据库中最新的收盘价
if closePrice != float(stockData[-1]): # 如果不一致则需要复权
rate = (float(stockData[-1]) - closePrice) / closePrice
reRightCode.append([symbol, rate])
print stockDataList
print '复权的数量为 %s' % len(reRightCode)
print '复权的股票代码为：'
print reRightCode
logging.info('需要复权的股票代码为：%s' % reRightCode)
return reRightCode, stockDataList
def formatStockData(self, rowDataList):
'''将从文件读入的数据变为数据库标准数据，代码加前缀，成交量和成交额改变;o,h,l,c,v,a'''
today = date.today()
stockDataList = []
for rowData in rowDataList:
rowData[0] = 'SH' + rowData[0] if rowData[0].startswith(
'6') else 'SZ' + rowData[0]
for i in [4, 5]:
if rowData[i].endswith('\xd2\xda'):
rowData[i] = float(rowData[i].replace('\xd2\xda',
'')) * (10**8)
elif rowData[i].endswith('\xcd\xf2'):
rowData[i] = float(rowData[i].replace('\xcd\xf2',
'')) * (10**4)
stockData = [
rowData[0], today, rowData[9], rowData[7], rowData[8],
rowData[6], rowData[4], rowData[5], rowData[10]
]
stockDataList.append(stockData)
return stockDataList
def reRightData(self, reRightCode):
''''''
code = [record[0] for record in reRightCode]
rate = [record[1] for record in reRightCode]
paraList = []
for i in range(len(reRightCode)):
paraList.append((rate[i], ) * 5 + (code[i], ))
sql = 'update stockData_day_tdx set '+\
'OpenPrice=OpenPrice*(1+%s),HighPrice=HighPrice*(1+%s),LowPrice=LowPrice*(1+%s),ClosePrice=ClosePrice*(1+%s),Amt=Amt*(1+%s)' +\
" where Symbol=%s"
self.cur.executemany(sql, paraList)
self.con.commit()
print '日线复权完毕'
paraList = []
for i in range(len(reRightCode)):
paraList.append((rate[i], ) * 5 + (code[i], ))
for period in [5, 15, 30, 60]:
sql = 'update stockData_%smin_tdx ' % period + \
'set OpenPrice=OpenPrice*(1+%s),HighPrice=HighPrice*(1+%s),LowPrice=LowPrice*(1+%s),ClosePrice=ClosePrice*(1+%s),Amt=Amt*(1+%s)' + \
" where Symbol=%s"
self.cur.executemany(sql, paraList)
self.con.commit()
print '分钟线复权完毕'
def insertDayData(self, todayData):
'''更新日数据'''
for data in todayData:
data[:] = data[:-1]
sql = "insert ignore into stockData_day_tdx values(" + "%s," * 7 + "%s)" # 一共有8列数据
self.cur.executemany(sql, tuple(todayData))
self.con.commit()
print 'day数据更新完成'
def insertMinData(self):
'''更新分钟数据'''
today = date.today().strftime('%Y-%m-%d')
# 得到文件夹下面所有txt结尾的文件路径
fileNameList = self.getFileNameList(
self.currentMinPath) # 内容是文件名，不包括前面的路径
filePathList = [
os.path.join(self.historyDayPath, fileName)
for fileName in fileNameList
]
symbolList = [fileName.split('.')[0] for fileName in fileNameList]
# 循环每个文件写入数据库
for i in range(len(fileNameList)):
# 读取文件,从第一行读取（不导出头文件）
stockFile = open(filePathList[i])
fileContent = stockFile.readlines()[:-1]
stockFile.close()
if len(fileContent) == 0: continue
stockDataList5 = []
for row in fileContent[::-1]:
rowData = row.strip().split('\t')
if rowData[0] != today: break # 从最后一行读取，如果其日期不是当天日期，则退出循环。
stockTime = '%s %s:%s:00' % (rowData[0], rowData[1][:-2],
rowData[1][-2:])
rowData[0:2] = [stockTime]
valueData = np.array([float(item) for item in rowData[1:]])
if all(valueData == 0.0): continue # 全部为0.证明该股票还未上市操作
if len(rowData) == 7: # 查看了海信在6-15日停牌的情况，停牌的数据没有包含在下载的min文件中。
rowData.insert(0, symbolList[i])
stockDataList5.append(rowData)
# 找到其他周期的数据
stockDataList15 = stockDataList5[2::3]
stockDataList30 = stockDataList15[1::2]
stockDataList60 = [
item for item in stockDataList30 if item[1].endswith('00:00')
]
# 将这只股票的数据写入数据库
for period in [5, 15, 30, 60]:
sql = "insert ignore into stockData_%smin_tdx" % period + " values(" + "%s," * 7 + "%s)"
self.cur.executemany(sql,
tuple(eval("stockDataList%s" % period)))
self.con.commit()
print '%s分钟线数据写入完毕' % symbolList[i]
print 'min数据更新完成'
def getFileNameList(self, filePath):
'''得到路径下所有的文件名'''
return [
filename for filename in os.listdir(filePath)
if os.path.splitext(filename)[-1] in ['.xls', '.xlsx']
]
def getStockCode(self):
'''获得股票代码'''
sql = 'select distinct Symbol from stockdata_day_tdx'
self.cur.execute(sql)
return [symbol[0] for symbol in self.cur.fetchall() if symbol[0]]
def close(self):
'''關閉數據庫'''
self.con.close()
self.cur.close()
class StockData():
'''通过通达信导出的txt文件，更新日线和分钟级数据'''
def __init__(self):
self.initialize()
self.main()
def initialize(self):
# 初始化日志服务
self.initLogging()
# 初始化路径值
self.initPath()
# 数据库连接，连接配置可在tool文件中修改
self.con = Connection().getConnection()
self.cur = self.con.cursor()
def main(self):
# 读入历史数据，只是第一次导入数据库时需要运行，以后每天更新即可。
self.historyData()
# self.currentData() # 更新數據庫的數據，每天运行
self.close()
#------------------------------------------------------------------------------ initialize
def initLogging(self):
'''初始化日志对象'''
logging.basicConfig(level=logging.INFO,
format='%(asctime)-15s %(lineno)-6d %(funcName)-30s %(message)s',
datefmt='%m-%d %H:%M:%S',
filename=r'D:\tdxData.txt',
filemode='w')
def initPath(self):
'''初始化各种读入文件的路径名，包括历史的日数据，分钟数据路径；当天的收盘价和前收的对比数据路径，以及当天的日数据和分钟数据的路径名'''
self.historyDayPath = r'C:\Users\Administrator\Desktop\tdx\historyDayData' #历史日数据文件的路径，会把当前路径的数据全部写入数据库
self.historyMinPath = r'C:\Users\Administrator\Desktop\tdx\historyMinData' #历史分钟数据文件的路径，会把当前路径的数据全部写入数据库，并相应生成15,30,60数据
self.checkDataPath = r'C:\Users\Administrator\Desktop\tdx\checkData' #收盘价和前收的对比文件路径，也就是通过公式导出的文件的路径，该路径只应该存在最新的对比文件
self.currentMinPath = r'C:\Users\Administrator\Desktop\tdx\currentMinData' #当天分钟级的数据，并相应形成15,30,60数据
#------------------------------------------------------------------------------ history
def historyData(self):
'''读入历史数据'''
# self.getDayData()
self.getMinData()
def getDayData(self):
'''读入日线数据'''
# 得到文件夹下面所有txt结尾的文件路径
fileNameList = self.getFileNameList(self.historyDayPath) # 内容是文件名，不包括前面的路径
filePathList = [os.path.join(self.historyDayPath,fileName) for fileName in fileNameList]
symbolList = [fileName.split('.')[0] for fileName in fileNameList]
# 循环每个文件写入数据库
for i in range(len(fileNameList)):
stockFile = open(filePathList[i])
fileContent = stockFile.readlines()[:-1]
stockFile.close()
if len(fileContent) == 0: continue
# 读取数据
stockDataList = []
for row in fileContent:
rowData = row.strip().split('\t')
valueData = np.array([float(item) for item in rowData[1:]])
if all(valueData==0.0): continue # 全部为0.证明该股票还未上市操作
if len(rowData) == 7: # 查看了海信在6-15日停牌的情况，停牌的数据没有包含在下载的文件中。
rowData.insert(0,symbolList[i])
stockDataList.append(rowData)
# 将这只股票的数据写入数据库
sql = "insert ignore into stockData_day_tdx values("+"%s,"*7+"%s)" # 一共有8列数据
self.cur.executemany(sql,tuple(stockDataList))
self.con.commit()
print '%s日线数据写入完毕' % symbolList[i]
print '全部日线数据写入完毕'
def getMinData(self):
'''读入分钟数据'''
# 得到文件夹下面所有txt结尾的文件路径
fileNameList = self.getFileNameList(self.historyMinPath) # 内容是文件名，不包括前面的路径
filePathList = [os.path.join(self.historyMinPath,fileName) for fileName in fileNameList]
symbolList = [fileName.split('.')[0] for fileName in fileNameList]
# 循环每个文件写入数据库
for i in range(len(fileNameList)):
# 读取文件,从第一行读取（不导出头文件）
stockFile = open(filePathList[i])
fileContent = stockFile.readlines()[:-1]
stockFile.close()
if len(fileContent) == 0: continue
# 读取数据
stockDataList5 = []
for row in fileContent:
rowData = row.strip().split('\t')
stockTime = '%s %s:%s:00' % (rowData[0],rowData[1][:-2],rowData[1][-2:])
rowData[0:2] = [stockTime]
valueData = np.array([float(item) for item in rowData[1:]])
if all(valueData==0.0): continue # 全部为0.证明该股票还未上市操作
if len(rowData) == 7: # 查看了海信在6-15日停牌的情况，停牌的数据没有包含在下载的min文件中。
rowData.insert(0,symbolList[i])
stockDataList5.append(rowData)
# 找到其他周期的数据
stockDataList15 = stockDataList5[2::3]
stockDataList30 = stockDataList15[1::2]
stockDataList60 = [item for item in stockDataList30 if item[1].endswith('00:00')]
# 将这只股票的数据写入数据库
for period in [5,15,30,60]:
sql = "insert ignore into stockData_%smin_tdx" % period + " values("+"%s,"*7+"%s)"
self.cur.executemany(sql,tuple(eval("stockDataList%s" % period)))
self.con.commit()
print '%s分钟线数据写入完毕' % symbolList[i]
print '全部分钟线数据写入完毕'
#------------------------------------------------------------------------------current
def currentData(self):
'''复权，更新当天的数据'''
stockCodeList = self.getStockCode()
reRightCode,stockDataList = self.getUpdateCode(stockCodeList)
self.reRightData(reRightCode) # 复权数据
self.insertDayData(stockDataList) # 插入今天日线数据
self.insertMinData() # 插入今天分钟线数据
def getUpdateCode(self,stockCodeList):
'''獲得不同情況下更新的股票代碼'''
reRightCode = [] # 需要復權的股票和复权因子的列表
# 得到数据库中最新一天的收盘价
closeDict = {} # 股票代码：收盘价
for code in stockCodeList:
sql = "select ClosePrice from stockdata_day_tdx where Symbol = %s order by date desc limit 1"
self.cur.execute(sql,code)
result = self.cur.fetchone()
closeDict[code] = result[0]
# 查找今天的數據
fileName = self.getFileNameList(self.checkDataPath)[0]
path = r'%s/%s' % (self.checkDataPath,fileName)
stockFile = open(path)
fileContent = stockFile.readlines()[2:-1] # 去掉最后一行
stockFile.close()
rowDataList = []
for row in fileContent:
rowData = [item.strip() for item in row.strip().split('\t')]
if len(rowData) != 11 or (rowData[3] == '0') or (rowData[4] == '0'): continue# 不等于11列则该股票还未上市，rowData[3]为空证明停牌，停牌不用复权
rowData[0] = rowData[0].replace('=','')
rowData[0] = rowData[0].replace('"','')
rowDataList.append(rowData)
# 由文件数据转化成结构数据
print len(rowDataList)
stockDataList = self.formatStockData(rowDataList)
for stockData in stockDataList:
symbol = stockData[0]
if symbol not in closeDict: continue
closePrice = closeDict[symbol] # 得到数据库中最新的收盘价
if closePrice != float(stockData[-1]): # 如果不一致则需要复权
rate = (float(stockData[-1]) - closePrice) / closePrice
reRightCode.append([symbol,rate])
print stockDataList
print '复权的数量为 %s' % len(reRightCode)
print '复权的股票代码为：'
print reRightCode
logging.info('需要复权的股票代码为：%s' % reRightCode)
return reRightCode,stockDataList
def formatStockData(self,rowDataList):
'''将从文件读入的数据变为数据库标准数据，代码加前缀，成交量和成交额改变;o,h,l,c,v,a'''
today = date.today()
stockDataList = []
for rowData in rowDataList:
rowData[0] = 'SH'+rowData[0] if rowData[0].startswith('6') else 'SZ'+rowData[0]
for i in [4,5]:
if rowData[i].endswith('\xd2\xda'):
rowData[i] = float(rowData[i].replace('\xd2\xda','')) * (10**8)
elif rowData[i].endswith('\xcd\xf2'):
rowData[i] = float(rowData[i].replace('\xcd\xf2','')) * (10**4)
stockData = [rowData[0],today,rowData[9],rowData[7],rowData[8],rowData[6],rowData[4],rowData[5],rowData[10]]
stockDataList.append(stockData)
return stockDataList
def reRightData(self,reRightCode):
''''''
code = [record[0] for record in reRightCode]
rate = [record[1] for record in reRightCode]
paraList = []
for i in range(len(reRightCode)):
paraList.append((rate[i],)*5 + (code[i],))
sql = 'update stockData_day_tdx set '+\
'OpenPrice=OpenPrice*(1+%s),HighPrice=HighPrice*(1+%s),LowPrice=LowPrice*(1+%s),ClosePrice=ClosePrice*(1+%s),Amt=Amt*(1+%s)' +\
" where Symbol=%s"
self.cur.executemany(sql,paraList)
self.con.commit()
print '日线复权完毕'
paraList = []
for i in range(len(reRightCode)):
paraList.append((rate[i],)*5 + (code[i],))
for period in [5,15,30,60]:
sql = 'update stockData_%smin_tdx ' % period + \
'set OpenPrice=OpenPrice*(1+%s),HighPrice=HighPrice*(1+%s),LowPrice=LowPrice*(1+%s),ClosePrice=ClosePrice*(1+%s),Amt=Amt*(1+%s)' + \
" where Symbol=%s"
self.cur.executemany(sql,paraList)
self.con.commit()
print '分钟线复权完毕'
def insertDayData(self,todayData):
'''更新日数据'''
for data in todayData:
data[:] = data[:-1]
sql = "insert ignore into stockData_day_tdx values("+"%s,"*7+"%s)" # 一共有8列数据
self.cur.executemany(sql,tuple(todayData))
self.con.commit()
print 'day数据更新完成'
def insertMinData(self):
'''更新分钟数据'''
today = date.today().strftime('%Y-%m-%d')
# 得到文件夹下面所有txt结尾的文件路径
fileNameList = self.getFileNameList(self.currentMinPath) # 内容是文件名，不包括前面的路径
filePathList = [os.path.join(self.historyDayPath,fileName) for fileName in fileNameList]
symbolList = [fileName.split('.')[0] for fileName in fileNameList]
# 循环每个文件写入数据库
for i in range(len(fileNameList)):
# 读取文件,从第一行读取（不导出头文件）
stockFile = open(filePathList[i])
fileContent = stockFile.readlines()[:-1]
stockFile.close()
if len(fileContent) == 0: continue
stockDataList5 = []
for row in fileContent[::-1]:
rowData = row.strip().split('\t')
if rowData[0] != today: break # 从最后一行读取，如果其日期不是当天日期，则退出循环。
stockTime = '%s %s:%s:00' % (rowData[0],rowData[1][:-2],rowData[1][-2:])
rowData[0:2] = [stockTime]
valueData = np.array([float(item) for item in rowData[1:]])
if all(valueData==0.0): continue # 全部为0.证明该股票还未上市操作
if len(rowData) == 7: # 查看了海信在6-15日停牌的情况，停牌的数据没有包含在下载的min文件中。
rowData.insert(0,symbolList[i])
stockDataList5.append(rowData)
# 找到其他周期的数据
stockDataList15 = stockDataList5[2::3]
stockDataList30 = stockDataList15[1::2]
stockDataList60 = [item for item in stockDataList30 if item[1].endswith('00:00')]
# 将这只股票的数据写入数据库
for period in [5,15,30,60]:
sql = "insert ignore into stockData_%smin_tdx" % period + " values("+"%s,"*7+"%s)"
self.cur.executemany(sql,tuple(eval("stockDataList%s" % period)))
self.con.commit()
print '%s分钟线数据写入完毕' % symbolList[i]
print 'min数据更新完成'
def getFileNameList(self,filePath):
'''得到路径下所有的文件名'''
return [filename for filename in os.listdir(filePath) if os.path.splitext(filename)[-1] in ['.xls','.xlsx']]
def getStockCode(self):
'''获得股票代码'''
sql = 'select distinct Symbol from stockdata_day_tdx'
self.cur.execute(sql)
return [symbol[0] for symbol in self.cur.fetchall() if symbol[0]]
def close(self):
'''關閉數據庫'''
self.con.close()
self.cur.close()