从本地文件分别加载Leg&Leg2，合成套利Tick，用于回测
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msincenselee
parent
651a8f2086
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1dd507d421
356
vn.trader/ctaStrategy/utilArbTickLoader.py
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356
vn.trader/ctaStrategy/utilArbTickLoader.py
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# encoding: UTF-8
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import os
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import cPickle
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import csv
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import logging
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import pandas
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import copy
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from datetime import datetime, timedelta
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from ctaBase import *
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class UtilArbTickLoader(object):
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"""一个套利tick的数据加载工具类"""
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# ----------------------------------------------------------------------
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def __init__(self, ticksFolder, symbol):
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# tick 存放的文件系统路径
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if not ticksFolder:
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self.ticksFolder = u'z:\\ticks'
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else:
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self.ticksFolder = ticksFolder
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self.symbol = symbol
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def writeCtaLog(self, content):
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"""记录日志"""
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# log = str(self.dt) + ' ' + content
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# self.logList.append(log)
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# 写入本地log日志
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logging.info(content)
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def writeCtaError(self, content):
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"""记录异常"""
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self.output(content)
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self.writeCtaLog(content)
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def output(self, content):
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"""输出内容"""
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print str(datetime.now()) + "\t" + content
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# ----------------------------------------------------------------------
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def loadArbTicks(self, mainPath, dtDate, leg1Symbol, leg2Symbol):
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self.writeCtaLog(u'加载日期:{0}\{1}的价差tick'.format(mainPath, dtDate))
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cachefilename = u'{0}_{1}_{2}_{3}_{4}'.\
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format(self.symbol, leg1Symbol, leg2Symbol, mainPath, dtDate.strftime('%Y%m%d'))
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arbTicks = self.__loadArbTicksFromLocalCache(cachefilename)
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dt = None
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if len(arbTicks) < 1:
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leg1File = self.ticksFolder + u'\\{0}\\{1}\\{2}\\{3}\\{4}.txt' \
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.format(mainPath, dtDate.strftime('%Y%m'), self.symbol, dtDate.strftime('%m%d'), leg1Symbol)
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if not os.path.isfile(leg1File):
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self.writeCtaLog(u'{0}文件不存在'.format(leg1File))
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return []
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leg2File = self.ticksFolder + u'\\{0}\\{1}\\{2}\\{3}\\{4}.txt' \
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.format(mainPath, dtDate.strftime('%Y%m'), self.symbol, dtDate.strftime('%m%d'), leg2Symbol)
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if not os.path.isfile(leg2File):
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self.writeCtaLog(u'{0}文件不存在'.format(leg2File))
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return []
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# 先读取leg2的数据到目录，以日期时间为key
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leg2Ticks = {}
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leg2CsvReadFile = file(leg2File, 'rb')
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#reader = csv.DictReader((line.replace('\0',' ') for line in leg2CsvReadFile), delimiter=",")
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reader = csv.DictReader(leg2CsvReadFile, delimiter=",")
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self.writeCtaLog(u'加载{0}'.format(leg2File))
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for row in reader:
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tick = CtaTickData()
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tick.vtSymbol = self.symbol
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tick.symbol = self.symbol
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tick.date = dtDate.strftime('%Y%m%d')
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tick.tradingDay = tick.date
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tick.time = row['Time']
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try:
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tick.datetime = datetime.strptime(tick.date + ' ' + tick.time, '%Y%m%d %H:%M:%S.%f')
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except Exception as ex:
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self.writeCtaError(u'日期转换错误:{0},{1}:{2}'.format(tick.date + ' ' + tick.time, Exception, ex))
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continue
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# 修正毫秒
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if tick.datetime.replace(microsecond = 0) == dt:
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# 与上一个tick的时间（去除毫秒后）相同,修改为500毫秒
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tick.datetime=tick.datetime.replace(microsecond = 500)
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tick.time = tick.datetime.strftime('%H:%M:%S.%f')
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else:
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tick.datetime = tick.datetime.replace(microsecond=0)
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tick.time = tick.datetime.strftime('%H:%M:%S.%f')
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dt = tick.datetime
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tick.lastPrice = float(row['LastPrice'])
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tick.volume = int(float(row['LVolume']))
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tick.bidPrice1 = float(row['BidPrice']) # 叫买价（价格低）
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tick.bidVolume1 = int(float(row['BidVolume']))
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tick.askPrice1 = float(row['AskPrice']) # 叫卖价（价格高）
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tick.askVolume1 = int(float(row['AskVolume']))
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# 排除涨停/跌停的数据
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if (tick.bidPrice1 == float('1.79769E308') and tick.bidVolume1 == 0) \
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or (tick.askPrice1 == float('1.79769E308') and tick.askVolume1 == 0):
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continue
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dtStr = tick.date + ' ' + tick.time
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if dtStr in leg2Ticks:
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self.writeCtaError(u'日内数据重复，异常,数据时间为:{0}'.format(dtStr))
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else:
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leg2Ticks[dtStr] = tick
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leg1CsvReadFile = file(leg1File, 'rb')
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#reader = csv.DictReader((line.replace('\0',' ') for line in leg1CsvReadFile), delimiter=",")
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reader = csv.DictReader(leg1CsvReadFile, delimiter=",")
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self.writeCtaLog(u'加载{0}'.format(leg1File))
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dt = None
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for row in reader:
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arbTick = CtaTickData()
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arbTick.date = dtDate.strftime('%Y%m%d')
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arbTick.time = row['Time']
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try:
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arbTick.datetime = datetime.strptime(arbTick.date + ' ' + arbTick.time, '%Y%m%d %H:%M:%S.%f')
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except Exception as ex:
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self.writeCtaError(u'日期转换错误:{0},{1}:{2}'.format(arbTick.date + ' ' + arbTick.time, Exception, ex))
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continue
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# 修正毫秒
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if arbTick.datetime.replace(microsecond=0) == dt:
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# 与上一个tick的时间（去除毫秒后）相同,修改为500毫秒
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arbTick.datetime = arbTick.datetime.replace(microsecond=500)
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arbTick.time = arbTick.datetime.strftime('%H:%M:%S.%f')
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else:
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arbTick.datetime = arbTick.datetime.replace(microsecond=0)
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arbTick.time = arbTick.datetime.strftime('%H:%M:%S.%f')
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dt = arbTick.datetime
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dtStr = ' '.join([arbTick.date, arbTick.time])
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if dtStr in leg2Ticks:
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leg2Tick = leg2Ticks[dtStr]
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arbTick.vtSymbol = self.symbol
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arbTick.symbol = self.symbol
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arbTick.lastPrice = EMPTY_FLOAT
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arbTick.volume = EMPTY_INT
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leg1AskPrice1 = float(row['AskPrice'])
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leg1AskVolume1 = int(float(row['AskVolume']))
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leg1BidPrice1 = float(row['BidPrice'])
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leg1BidVolume1 = int(float(row['BidVolume']))
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# 排除涨停/跌停的数据
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if ((leg1AskPrice1 == float('1.79769E308') or leg1AskPrice1 == 0) and leg1AskVolume1 == 0) \
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or ((leg1BidPrice1 == float('1.79769E308') or leg1BidPrice1 == 0) and leg1BidVolume1 == 0):
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continue
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# 叫卖价差=leg1.askPrice1 - leg2.bidPrice1，volume为两者最小
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arbTick.askPrice1 = leg1AskPrice1 - leg2Tick.bidPrice1
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arbTick.askVolume1 = min(leg1AskVolume1, leg2Tick.bidVolume1)
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# 叫买价差=leg1.bidPrice1 - leg2.askPrice1，volume为两者最小
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arbTick.bidPrice1 = leg1BidPrice1 - leg2Tick.askPrice1
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arbTick.bidVolume1 = min(leg1BidVolume1, leg2Tick.askVolume1)
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arbTicks.append(arbTick)
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del leg2Ticks[dtStr]
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# 保存到历史目录
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if len(arbTicks) > 0:
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self.__saveArbTicksToLocalCache(cachefilename, arbTicks)
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return arbTicks
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def __loadArbTicksFromLocalCache(self, filename):
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"""从本地缓存中，加载数据"""
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# 运行路径下cache子目录
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cacheFolder = os.getcwd() + '/cache'
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# cache文件
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cacheFile = u'{0}/{1}.pickle'. \
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format(cacheFolder, filename)
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if not os.path.isfile(cacheFile):
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return []
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else:
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# 从cache文件加载
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cache = open(cacheFile, mode='r')
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l = cPickle.load(cache)
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cache.close()
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return l
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def __saveArbTicksToLocalCache(self, filename, arbticks):
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"""保存价差tick到本地缓存目录"""
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# 运行路径下cache子目录
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cacheFolder = os.getcwd() + '/cache'
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# 创建cache子目录
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if not os.path.isdir(cacheFolder):
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os.mkdir(cacheFolder)
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# cache 文件名
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cacheFile = u'{0}/{1}.pickle'. \
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format(cacheFolder, filename)
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# 重复存在 返回
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if os.path.isfile(cacheFile):
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return False
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else:
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# 写入cache文件
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cache = open(cacheFile, mode='w')
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cPickle.dump(arbticks, cache)
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cache.close()
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return True
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def convert_to_dataframe(self, ticklist):
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"""转换为dataframe格式"""
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variables = ['date', 'time', 'askPrice1', 'askVolume1', 'bidPrice1', 'bidVolume1']
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dataframe = pandas.DataFrame([[getattr(i, j) for j in variables] for i in ticklist], columns=variables)
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return dataframe
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def __saveArbTicksToLocalCsv(self, filename, df):
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"""保存为本地csv文件"""
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# 运行路径下cache子目录
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cacheFolder = os.getcwd() + '/cache'
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# 创建cache子目录
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if not os.path.isdir(cacheFolder):
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os.mkdir(cacheFolder)
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# cache 文件名
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cacheFile = u'{0}/{1}.csv'. \
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format(cacheFolder, filename)
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# 重复存在 返回
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if os.path.isfile(cacheFile):
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return False
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df.to_csv(cacheFile, index=False)
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def __loadArbTicksFromLocalCsv(self ,filename):
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"""从本地缓存csv中，加载数据"""
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# 运行路径下cache子目录
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cacheFolder = os.getcwd() + '/cache'
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# cache文件
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cacheFile = u'{0}/{1}.csv'. \
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format(cacheFolder, filename)
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if not os.path.isfile(cacheFile):
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return None
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else:
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# 从cache文件加载
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df = pandas.read_csv(cacheFile)
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return df
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def loadDataFrame(self, mainPath, dtDate, leg1Symbol, leg2Symbol):
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self.writeCtaLog(u'加载日期:{0}\{1}的价差tick dataframe'.format(mainPath, dtDate))
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cachefilename = u'{0}_{1}_{2}_{3}_{4}'. \
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format(self.symbol, leg1Symbol, leg2Symbol, mainPath, dtDate.strftime('%Y%m%d'))
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df = self.__loadArbTicksFromLocalCsv(cachefilename)
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if df is None:
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ticks = self.loadArbTicks(mainPath, dtDate, leg1Symbol, leg2Symbol)
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if len(ticks) >0:
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df = self.convert_to_dataframe(ticks)
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self.__saveArbTicksToLocalCsv(cachefilename,df)
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return df
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def loadDataFrame2(self, mainPath, beginDate, endDate, leg1Symbol, leg2Symbol):
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dayIntervals = (endDate- beginDate).days
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if dayIntervals < 1:
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self.writeCtaLog(u'时间不足')
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return None
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df = None
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cachefilename = u'{0}_{1}_{2}_{3}_{4}'. \
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format(self.symbol, leg1Symbol, leg2Symbol, beginDate.strftime('%Y%m%d'), endDate.strftime('%Y%m%d'))
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df = self.__loadArbTicksFromLocalCsv(cachefilename)
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if df is not None:
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return df
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for i in range(0, dayIntervals):
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getDate = beginDate + timedelta(days=i)
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self.output(u'取数据日期:{0}'.format(getDate))
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df1,df2 =None,None
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# 白天数据
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df1 = self.loadDataFrame(mainPath, getDate, leg1Symbol, leg2Symbol)
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if df1 is not None and df is None:
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df = copy.copy(df1)
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self.output(u'数据{0}行'.format(len(df)))
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elif df1 is not None and df is not None:
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df = pandas.concat([df,df1], ignore_index=True)
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self.output(u'数据增加{0}行,共{1}行'.format(len(df1),len(df)))
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# 夜盘数据
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df2 = self.loadDataFrame(mainPath + '_night', getDate, leg1Symbol, leg2Symbol)
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if df2 is not None and df is None:
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df = copy.copy(df2)
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self.output(u'数据{0}行'.format(len(df)))
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elif df2 is not None and df is not None:
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df = pandas.concat([df,df2], ignore_index=True)
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self.output(u'数据增加{0}行,共{1}行'.format(len(df2), len(df)))
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self.__saveArbTicksToLocalCsv(cachefilename, df)
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return df
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if __name__ == '__main__':
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loader = UtilArbTickLoader(ticksFolder='z://ticks', symbol='RB')
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"""只取tick对象队列"""
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#ticks = loader.loadArbTicks(mainPath='SHFE',dtDate=datetime.strptime('20140801', '%Y%m%d'),
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# leg1Symbol='RB1501', leg2Symbol='RB1505')
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#df = loader.convert_to_dataframe(ticks)
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"""取单日dataframe"""
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#df = loader.loadDataFrame(mainPath='SHFE',dtDate=datetime.strptime('20140801', '%Y%m%d'),
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# leg1Symbol='RB1501', leg2Symbol='RB1505')
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"""取一段日期内的dataframe"""
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df = loader.loadDataFrame2(mainPath='SHFE', beginDate=datetime.strptime('20140801', '%Y%m%d'),
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endDate=datetime.strptime('20141030', '%Y%m%d'),
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leg1Symbol='RB1501', leg2Symbol='RB1505')
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#print df
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