代码拉取完成，页面将自动刷新
# -*- coding: utf-8 -*-
import sys
import os
import urllib2
import socket
import re
import time
import threading
from aclass import *
threadLock = threading.Lock()
dateTimePattern = re.compile(r',\d{2}(\d{2}-\d{2}-\d{2}),(\d{2}:\d{2}):\d{2},')
stockPattern = re.compile(r'var hq_str_s[hz]\d{6}="([^,"]+),([^,"]+),([^,"]+),([^,"]+),([^,"]+),([^,"]+),[^"]+";')
volumePattern = re.compile(r'var hq_str_s[hz]\d{6}="(([^,"]+),){8}([^,"]+),[^"]+";')
transPattern = re.compile(r'new Array\(\'([\d:]+)\', \'(\d+)\', \'([\d\.]+)\', \'(DOWN|UP|EQUAL)\'\)')
klinePattern = re.compile(r'\{day:"([\d\- :]+)",open:"([\d.]+)",high:"([\d.]+)",low:"([\d.]+)",close:"([\d.]+)",volume:"(\d+)"\}')
cahceMode = False # 缓存模式
testMode = False # 测试模式
cachePath = None # 缓存文件夹的路径
timePercent = 0 # 今天交易时间经过的百分比（例:午休-50%，14:00-75%）
correctDate = 0 # 如果没有停牌复牌K线数据第一天的正确日期
totalCount = 0
def calcTimePercent(dateTime):
timePercent = dateTime % 10000
if timePercent >= 1500:
timePercent = 240
elif timePercent >= 1400:
timePercent = timePercent - 1400 + 180
elif timePercent >= 1300:
timePercent = timePercent - 1300 + 120
elif timePercent >= 1130:
timePercent = 120
elif timePercent >= 1100:
timePercent = timePercent - 1100 + 90
elif timePercent >= 1000:
timePercent = timePercent - 1000 + 30
elif timePercent >= 930:
timePercent = timePercent - 930
else:
timePercent = 0
return timePercent / 240.0
def calcDuration(minutes):
return minutes % 60 + 100 * (minutes / 60)
def requestDateTime_():
url = 'http://hq.sinajs.cn/list=sh000001'
try:
content = urllib2.urlopen(url, timeout = 3).read()
except urllib2.URLError:
return False
except socket.timeout:
return False
match = dateTimePattern.search(content)
dateTime = int(match.group(1).replace('-', '')) * 10000 + int(match.group(2).replace(':', ''))
return dateTime
def requestDateTime():
dateTime = requestDateTime_()
while dateTime == False:
dateTime = requestDateTime_()
return dateTime
def requestStockData_(stockCode):
url = 'http://hq.sinajs.cn/list=' + stockCode
try:
content = urllib2.urlopen(url, timeout = 3).read()
except urllib2.URLError:
return False
except socket.timeout:
return False
stock = None
match = stockPattern.search(content)
if match:
stock = Stock(match.group(1), match.group(2), match.group(3), match.group(4), match.group(5), match.group(6))
return stock
def requestStockData(stockCode):
stock = requestStockData_(stockCode)
while stock == False:
stock = requestStockData_(stockCode)
return stock
def requestVolumnData_(stockCode):
url = 'http://hq.sinajs.cn/list=' + stockCode
try:
content = urllib2.urlopen(url, timeout = 3).read()
except urllib2.URLError:
return False
except socket.timeout:
return False
volume = 0
match = volumePattern.search(content)
if match:
volume = int(match.group(3))
return volume
def requestVolumnData(stockCode):
volume = requestVolumnData_(stockCode)
while volume == False:
volume = requestVolumnData_(stockCode)
return volume
def requestKlineData_(stockCode, count, scale):
url = 'http://money.finance.sina.com.cn/quotes_service/api/json_v2.php/CN_MarketData.getKLineData?symbol=%s&scale=%d&ma=no&datalen=%d' % (stockCode, scale, count)
try:
content = urllib2.urlopen(url, timeout = 3).read()
except urllib2.URLError:
return False
except socket.timeout:
return False
klineList = []
match = klinePattern.search(content)
while match:
kline = Kline(match.group(2), match.group(3), match.group(4), match.group(5), match.group(6), match.group(1))
klineList.append(kline)
match = klinePattern.search(content, match.end() + 1)
return klineList
def requestKlineData(stockCode, count, scale = 240):
klineList = requestKlineData_(stockCode, count, scale)
while klineList == False:
klineList = requestKlineData_(stockCode, count, scale)
return klineList
def requestCorrectDate():
klineList = requestKlineData('sh000001', 6)
if klineList[-1].date == dateTime / 10000 % 1000000:
return klineList[0].date
else:
return klineList[1].date
def requestTransData_(stockCode, count):
# 1小时最大数据量是1150左右，因为交易系统3秒撮合一次，所以理论最大值为1小时1200
url = 'http://vip.stock.finance.sina.com.cn/quotes_service/view/CN_TransListV2.php?num=%d&symbol=%s' % (count, stockCode)
try:
content = urllib2.urlopen(url, timeout = 3).read()
except urllib2.URLError:
return False
except socket.timeout:
return False
transList = []
match = transPattern.search(content)
while match:
trans = Trans(match.group(1), match.group(2), match.group(3), match.group(4))
if trans.price > 0 and trans.volume > 0:
transList.insert(0, trans)
match = transPattern.search(content, match.end() + 1)
return transList
def requestTransData(stockCode, minutes = 60):
filePath = None
transList = None
# 判断是不是已收盘，收盘会进入缓存判断逻辑
if cachePath is not None:
filePath = os.path.join(cachePath, stockCode)
# 命中缓存，直接从文件读取
if os.path.isfile(filePath) == True:
cacheFile = open(filePath, 'r')
lines = cacheFile.readlines()
cacheFile.close()
transList = []
for line in lines:
trans = Trans()
trans.loadLine(line)
transList.append(trans)
# 如果没有命中缓存，从网络请求数据
if transList is None:
# 已经收盘，拿到的数据顺带存进文件
if filePath is not None:
transList = requestTransData_(stockCode, 4800)
while transList == False:
transList = requestTransData_(stockCode, 4800)
lines = []
for trans in transList:
lines.append(trans.saveLine())
cacheFile = open(filePath, 'w')
cacheFile.writelines(lines)
cacheFile.close()
# 直接请求部分数据
else:
transList = requestTransData_(stockCode, 1200 * minutes / 60)
while transList == False:
transList = requestTransData_(stockCode, 1200 * minutes / 60)
# 仅筛取指定时间内的数据
filteredList = []
if len(transList) > 0:
validTime = transList[-1].time - calcDuration(minutes)
for trans in transList:
if trans.time > validTime:
filteredList.append(trans)
return filteredList
def cacheTransData(stockCode):
# 仅仅尝试缓存数据
transList = requestTransData(stockCode, 0)
def checkStockData(stockCode):
# 获得股票名称等数据
stock = requestStockData(stockCode)
# 排序无效股票并提示
if stock == None:
threadLock.acquire()
print('==== ' + stockCode[2:] + ' ====')
print('无效代码')
threadLock.release()
# 排除停牌股票
if stock.todayStart == 0 or stock.yesterdayEnd == 0:
return
# 排除跌幅较大的股票
if testMode == False and stock.current < stock.yesterdayEnd * 0.97:
return
# 获取K线数据
klineList = requestKlineData(stockCode, 6)
if klineList[-1].date != dateTime / 10000 % 1000000:
del klineList[0]
# 有复牌情况则排除
if klineList[0].date != correctDate:
return
# 如果今日数据没有拉取到需要手动计算补全
if len(klineList) < 6:
# 获取当前交易量，并计算成今日期望总交易量
totalVolume = requestVolumnData(stockCode)
totalVolume = int(totalVolume / timePercent)
# 合成一个今天的假K线数据方便计算
kline = Kline(stock.todayStart, stock.highest, stock.lowest, stock.current, totalVolume)
klineList.append(kline)
# 计算量比
volumeRatio5 = 0
volumeRatio1 = 0
volume5 = 0
for kline in klineList[0:5]:
volume5 += kline.volume
volumeRatio5 = klineList[-1].volume * 5.0 / volume5
volumeRatio1 = klineList[-1].volume * 1.0 / klineList[-2].volume
# 排除量比增长较小的股票
if testMode == False and (volumeRatio1 < 1.2 or volumeRatio5 < 1.1):
return
# 计算日OBV
obvDay = 0
for index in xrange(0, 5):
if klineList[index+1].end > klineList[index].end:
obvDay += klineList[index+1].volume
else:
obvDay -= klineList[index+1].volume
obvDay = obvDay * 1.0 / volume5
# 排除OBV低的股票
if testMode == False and obvDay <= 0:
return
# 计算小时OBV
klineList = requestKlineData(stockCode, 3 * 4 + 1, 60)
obvHour = 0
for index in xrange(0, 3 * 4):
if klineList[index+1].end > klineList[index].end:
obvHour += klineList[index+1].volume
else:
obvHour -= klineList[index+1].volume
obvHour = obvHour * 2.0 / volume5
# 排除OBV低的股票
if testMode == False and obvHour <= 0:
return
# 计算15分钟OBV
klineList = requestKlineData(stockCode, 16 + 1, 15)
obv15M = 0
for index in xrange(0, 16):
if klineList[index+1].end > klineList[index].end:
obv15M += klineList[index+1].volume
else:
obv15M -= klineList[index+1].volume
obv15M = obv15M * 6.0 / volume5
# 排除OBV低的股票
if testMode == False and obv15M <= 0:
return
# 打印数据
threadLock.acquire()
global totalCount
totalCount += 1
print('==== ' + stockCode[2:] + ' ====')
stock.printStockData()
print('量 比: (5)%.2f (1)%.2f' % (volumeRatio5, volumeRatio1))
print('量价得分: (日)%.2f (时)%.2f (15分)%.2f' % (obvDay, obvHour, obv15M))
threadLock.release()
def threadFunction(stockList):
if cahceMode == True:
if timePercent == 1.0:
for stockCode in stockList:
cacheTransData(stockCode)
elif testMode == True:
checkStockData(stockList[0])
else:
for stockCode in stockList:
checkStockData(stockCode)
# 判断是否开启特殊模式
if len(sys.argv) > 1:
if sys.argv[1] == 'cache':
cahceMode = True
elif sys.argv[1] == 'test':
testMode = True
# 获取当前新浪服务器时间
dateTime = requestDateTime()
timePercent = calcTimePercent(dateTime)
correctDate = requestCorrectDate()
# 如果尚未收盘但是使用的是缓存模式则退出
if timePercent < 1.0 and cahceMode == True:
print('尚未收盘，无法进行逐比交易明细缓存')
exit(0)
# 如果已经收盘，则准备好cache目录
if timePercent == 1.0:
cachePath = os.path.join(sys.path[0], 'cache')
dateStr = '%6d' % (dateTime / 10000 % 1000000)
cachePath = os.path.join(cachePath, dateStr)
if os.path.isdir(cachePath) == False:
os.mkdir(cachePath)
# 多线循环筛选所有股票数据
startTime = time.time()
validStockList = 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countPerThread = (len(validStockList) + 99) / 100 if testMode == False else (len(validStockList) + 9) / 10
threadCount = (len(validStockList) + countPerThread - 1) / countPerThread
threadList = []
for index in xrange(0, threadCount):
thread = threading.Thread(target = threadFunction, args = (validStockList[index * countPerThread:(index + 1) * countPerThread],))
threadList.append(thread)
for thread in threadList:
thread.start()
for thread in threadList:
thread.join()
print('================')
print('总数量: %d') % (totalCount)
print('总用时: %.2f秒' % (time.time() - startTime))
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