def setStackCode(self):
least = LeastSquare()
draw = DrawPictureReal()
loopBack = LoopBack()
queryStock = QueryStock()
queryStock.init(self.window)
self.indexCloseDict = {}
def sendYouCanBuy(self, currentPath):
query = QueryStock()
codes = query.queryYouCanBuyStock()
print(codes)
self.tendown = []
self.other = []
for item in codes:
temp = []
price = query.todayKlineByCode(item[0])
temp.append(item[0])
temp.append(item[1])
temp.append(item[4])
temp.append(item[5])
temp.append(price)
if price <= 10:
self.tendown.append(temp)
else:
self.other.append(temp)
#主力、散户、反转信号
if item[5] == 1:
self.Zsm.append(temp)
if item[5] == 2:
self.GSM.append(temp)
self.tendown = sorted(self.tendown, key=lambda s: s[2], reverse=False)
self.other = sorted(self.other, key=lambda s: s[2], reverse=False)
self.Zsm = sorted(self.Zsm, key=lambda s: s[2], reverse=True)
self.GSM = sorted(self.GSM, key=lambda s: s[2], reverse=True)
self.doSendStockInfoBeautiful(self.Zsm, currentPath, "回踩反弹")
self.doSendStockInfoBeautiful(self.GSM, currentPath, "底部吸筹")
self.doSendStatisticForZsm()
self.doSendStockInfoBeautiful(self.tendown, currentPath, " 10+元以内")
self.doSendStockInfoBeautiful(self.other, currentPath, " 10-元以上")
self.doSendStatisticPaper()
def scanStock(self):
query = QueryStock()
today = query.todayIsTrue()[0]
connect = pymysql.Connect(host=self.connection.host,
port=self.connection.port,
user=self.connection.user,
passwd=self.connection.passwd,
db=self.connection.db,
charset=self.connection.charset)
# 获取游标
cursor = connect.cursor()
tableCheckSql = "show tables like 'candidate_stock'"
cursor.execute(tableCheckSql)
if len(list(cursor)) == 0:
createTable = "create table candidate_stock(id varchar(64) primary key not null,code varchar(64),name varchar(64),collect_date varchar(64),industry varchar(64),grad float,cv float,price float,now_price float,profit float,other varchar(45),is_down_line int)"
cursor.execute(createTable)
print(
"-----------------------------scan stock------------------------------------"
)
print("start time:" +
time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
syn = StockInfoSyn()
basicStock = syn.getBiscicStock()
count = 0
for item in basicStock:
count = count + 1
test = Application()
print(
str(count) + " " + item[0] + " " + item[1] + " " +
item[2] + " " + item[3])
kk = test.execute(item[0])
if test.avgCostGrad < 0:
candidateTemp = []
candidateTemp.append(item[0])
candidateTemp.append(item[1])
candidateTemp.append(item[3])
candidateTemp.append(test.avgCostGrad)
self.candidate.append(candidateTemp)
# 插入数据
sql = "select * from candidate_stock where code='%s' and collect_date='%s'"
data = (item[0], today)
cursor.execute(sql % data)
if len(list(cursor)) == 0:
print(item)
sql = "INSERT INTO candidate_stock (id, code, name,collect_date,industry,grad,cv,is_down_line) VALUES ( '%s', '%s','%s', '%s','%s', %.8f, %.8f,%i)"
data = (uuid.uuid1(), item[0], item[1], today, item[3],
test.avgCostGrad, test.cvValue, test.isDownLine)
cursor.execute(sql % data)
connect.commit()
# 垃圾回收
del kk, test
if count == int(self.connection.scans):
print("测试退出")
break
def doSendStatisticPaper(self):
query = QueryStock()
successCount = 0
#暂时统计0.618以下的
result = query.queryStockYouBrought()
htmls = "<table border='1'>"
htmls = htmls + "<tr><td>代码</td><td>名称</td><td>买入时间</td><td>grad</td><td>cv</td><td>买入价格</td><td>当前价格</td><td>增长幅度100%</td></tr>"
for item in result:
htmls = htmls + "<tr>"
if float(item[7]) > 0:
successCount = successCount + 1
for vo in range(len(item)):
if float(item[7]) > 0:
htmls = htmls + "<td bgcolor='#FFCC66'><font color='red'>" + str(
item[vo]) + "</font></td>"
else:
htmls = htmls + "<td bgcolor='#00FF00'><font color='blue'>" + str(
item[vo]) + "</font></td>"
htmls = htmls + "</tr>"
htmls = htmls + "</table>"
totalCount = len(result)
endHtml = "增长个数:" + str(
successCount) + "    总共个数：" + str(
totalCount) + " </br> 百分比：" + str(
successCount * 100 / totalCount) + "%" + htmls
con = Connection()
endDate = time.strftime('%Y-%m-%d', time.localtime(time.time()))
my_pass = con.emailPass
my_user = con.emaialUser
sender = con.sender
receivers = con.receivers
msgRoot = MIMEMultipart('related')
msgRoot['From'] = Header(str(endDate) + " 股票统计", 'utf-8')
msgRoot['To'] = Header("测试", 'utf-8')
subject = str(endDate) + ' 历史股票涨跌幅统计表'
msgRoot['Subject'] = Header(subject, 'utf-8')
msgAlternative = MIMEMultipart('alternative')
msgRoot.attach(msgAlternative)
mail_msg = endHtml
msgAlternative.attach(MIMEText(mail_msg, 'html', 'utf-8'))
try:
smtpObj = smtplib.SMTP()
smtpObj.connect('smtp.qq.com', 25) # 25 为 SMTP 端口号
smtpObj.login(my_user, my_pass)
smtpObj.sendmail(sender, receivers, msgRoot.as_string())
print("邮件发送成功")
except smtplib.SMTPException:
print("Error: 无法发送邮件")
def sendYouCanBuy(self, currentPath):
query = QueryStock()
codes = query.queryYouCanBuyStock()
print(codes)
self.tendown = []
self.other = []
for item in codes:
temp = []
price = query.todayKlineByCode(item[0])
temp.append(item[0])
temp.append(item[1])
temp.append(item[4])
temp.append(price)
if price <= 10:
self.tendown.append(temp)
else:
self.other.append(temp)
self.tendown = sorted(self.tendown, key=lambda s: s[2], reverse=False)
self.other = sorted(self.other, key=lambda s: s[2], reverse=False)
# self.doSendStockInfoBeautiful(self.tendown,currentPath,"平民股票")
# self.doSendStockInfoBeautiful(self.other,currentPath,"土豪股票")
self.doSendStatisticPaper()
def fetchStocks(self):
query = QueryStock()
codeList = query.queryHistoryStock()
for item in codeList:
#拿到基期和当前时间的价格
priceList = query.fetchPriceList(item[1], item[3])
#利益差额的百分比
profit = (float(priceList[1][0]) -
float(priceList[0][0])) * 100 / float(priceList[0][0])
#更新数据库
query.updateCandidate(item[0], priceList[0][0], priceList[1][0],
profit, priceList[1][1])
class ApplicationWithDraw:
window = 160
downlimit = -20
indexCloseDict = {}
least = LeastSquare()
draw = DrawPictureReal()
loopBack = LoopBack()
queryStock = QueryStock()
avgCostGrad = 0
def setStackCode(self):
least = LeastSquare()
draw = DrawPictureReal()
loopBack = LoopBack()
queryStock = QueryStock()
queryStock.init(self.window)
self.indexCloseDict = {}
# 筹码计算
def chipCalculate(self, result, start):
chipCalculateList = []
for index, row in result.iterrows():
temp = []
currentIndex = index - start
temp.append(currentIndex)
temp.append(row['open'])
temp.append(row['high'])
temp.append(row['low'])
temp.append(row['close'])
temp.append(row['volume'])
temp.append(row['tprice'])
temp.append(row['turn'])
temp.append(int(row['tradestatus']))
chipCalculateList.append(temp)
calcualate = ChipCalculate()
resultEnd = calcualate.getDataByShowLine(chipCalculateList, True)
return resultEnd
def executeForTest(self, code, savePath):
result = self.queryStock.queryStock(code)
if len(result[0]) < 200:
return self
return self.core(result[0], code, True, savePath, True)
# 执行器
def execute(self, code, isShow, savePath):
result = self.queryStock.queryStock(code)
if len(result[0]) < 200:
return self
return self.core(result[0], code, isShow, savePath, False)
# 核心调度器
def core(self, result, code, isShow, savePath, isTest):
self.draw.showK(code, result, isShow, savePath)
self.draw.isTest = isTest
# 十四天
Kflag = self.least.everyErChengPrice(result, 14, True)
# 三十天
erjieSlow = self.least.everyErChengPrice(result, 30, True)
# 三天二阶导数
erjieK = self.least.doubleErJie(Kflag, 3, True)
# 将收盘价转化为字典
testX = []
testY = []
H1 = []
H2 = []
H3 = []
for index, row in result.iterrows():
currentIndex = index - self.queryStock.start
price = row['close']
testX.append(currentIndex)
testY.append(price)
tempH1 = row['h1']
tempH2 = row['h2']
tempH3 = row['h3']
if tempH1 == None:
H1.append(0)
else:
H1.append(float(tempH1))
if tempH2 == None:
H2.append(0)
else:
H2.append(float(tempH2))
if tempH3 == None:
H3.append(0)
else:
H3.append(float(tempH3))
self.indexCloseDict = dict(zip(testX, testY))
self.draw.shenxianQS(testX, H1, H2, H3)
# 一阶导数
wangX = []
wangY = []
for item in Kflag:
kX = item[0]
kk = item[1]
wangX.append(kX)
wangY.append(kk)
self.draw.ax1Show(wangX, wangY)
yijiedict = dict(zip(wangX, wangY))
# 二阶导数
wangX = []
wangY = []
for item in erjieK:
kX = item[0]
kk = item[1]
wangX.append(kX)
wangY.append(kk)
self.draw.ax2Show(wangX, wangY)
# 慢速一阶导数
wangXSlow = []
wangYSlow = []
for item in erjieSlow:
kX1 = item[0]
kk1 = item[1]
wangXSlow.append(kX1)
wangYSlow.append(kk1)
self.draw.ax3showSlow(wangXSlow, wangYSlow)
yijieSlowdict = dict(zip(wangXSlow, wangYSlow))
# 筹码计算
resultEnd = self.chipCalculate(result, self.queryStock.start)
resultEnd.sort(key=lambda resultEnd: resultEnd[0])
resultEndLength = len(resultEnd)
string = ""
x = []
p = []
priceBigvolPriceIndexs = []
bigVolPrice = {}
myUp = {}
for i in range(len(resultEnd)):
x.append(resultEnd[i][0])
string = string + "," + str(resultEnd[i][1])
p.append(resultEnd[i][1])
if i == resultEndLength - 1:
priceJJJ = resultEnd[i][1]
# 价格大于50%的筹码线
if resultEnd[i][5] == 1:
priceBigvolPriceIndexs.append(resultEnd[i][0])
bigVolPrice[resultEnd[i][0]] = 1
if resultEnd[i][6] == 1:
myUp[resultEnd[i][0]] = 1
# 主力散户反转信号
iList = []
zList = []
sList = []
fList = []
zsm = {}
for index, row in result.iterrows():
iList.append(index - self.queryStock.start)
z = float(row['z'])
s = float(float(row['s']))
zList.append(z)
sList.append(s)
convert = int(row['m'])
if convert == 1:
fList.append(index - self.queryStock.start)
if z > s and convert == 1:
zsm[index - self.queryStock.start] = 1
myResult = pd.DataFrame()
myResult['tprice'] = p
tianjingle = self.least.everyErChengPriceForArray(
np.array(x), np.array(p), 30)
x1 = []
y1 = []
if tianjingle == None:
return
for item in tianjingle:
kX = item[0]
kk = item[1]
x1.append(kX)
y1.append(kk)
pingjunchengbendic = dict(zip(x1, y1))
self.draw.ax3Show(x1, y1, 'r', '一阶导数')
oldTwok = 0
oldOne = 0
# 牛顿策略
NewtonBuySall = []
downlimitTemp = 0
# 回测的缓存数据
buyList = []
sellList = []
total = len(result)
for i in range(len(erjieK)):
item = erjieK[i]
currentx = item[0]
twok = item[1]
downParent = item[2]
onek = yijiedict.get(currentx)
onkslow = yijieSlowdict.get(currentx)
onkchengben = pingjunchengbendic.get(currentx)
buyTemp = []
sellTemp = []
if onek == None or onkslow == None or onkchengben == None:
continue
if onkslow < 0 and onkchengben < 0:
onslowyestaday = yijieSlowdict.get(currentx - 1)
chengbenyestaday = pingjunchengbendic.get(currentx - 1)
if onslowyestaday == None or chengbenyestaday == None:
continue
if onslowyestaday < 0 and chengbenyestaday < 0 and onslowyestaday < onkslow and onkchengben < chengbenyestaday:
buyTemp.append(currentx)
buyTemp.append(twok)
buyTemp.append("g")
#筹码的上涨动力要足
if bigVolPrice.__contains__(
currentx) and myUp.__contains__(currentx):
buyTemp.append(1)
else:
buyTemp.append(0)
buyList.append(buyTemp)
if currentx == total - 1:
self.avgCostGrad = onkchengben
# 一阶导数大于0，二阶导数大于0，一阶导数大于二阶导数，二阶导数递减
if oldTwok > 0 and oldOne > 0 and oldTwok >= oldOne and onek > 0 and onek > twok:
sellTemp.append(currentx)
sellTemp.append(twok)
sellTemp.append("r")
sellList.append(sellTemp)
if oldOne > 0 and onek > 0 and oldOne > onek and oldTwok > oldOne and onek > twok:
# 添加历史回测里
sellTemp.append(currentx)
sellTemp.append(twok)
sellTemp.append("r")
sellList.append(sellTemp)
if onek > 0 and oldOne < 0:
# 添加历史回测里
sellTemp.append(currentx)
sellTemp.append(twok)
sellTemp.append("orange")
sellList.append(sellTemp)
# 一阶导数小于0，二阶导数小于0,一阶导数小于二阶导数，二阶导数递增,并且在之前的三天都被一阶导数压制
if onek <= 0 and twok > onek and oldTwok < oldOne and downParent < self.downlimit and abs(
twok - oldTwok) > abs(onek - oldOne):
# 添加到历史回测里
buyTemp.append(currentx)
buyTemp.append(twok)
buyTemp.append("g")
if bigVolPrice.__contains__(currentx):
buyTemp.append(1)
else:
buyTemp.append(0)
buyList.append(buyTemp)
oldTwok = twok
oldOne = onek
# 画线条
self.draw.klineInfo(buyList, sellList)
# 找到最小的那一个
for item in erjieK:
if item[1] != None and item[1] < downlimitTemp:
downlimitTemp = item[1]
downlimitTemp = abs(downlimitTemp)
self.draw.drawDownLine(abs(downlimitTemp) * (self.downlimit / 100))
for item in erjieK:
item[2] = item[1] / downlimitTemp * 100
# self.loopBack.testNewTon(NewtonBuySall,self.indexCloseDict)
# self.draw.ax5Show(self.loopBack.baseRmb,self.loopBack.buysell,self.loopBack.myRmb)
self.draw.ax5ShowZsm(zsm, fList, priceBigvolPriceIndexs, iList, zList,
sList)
self.draw.savePng()
return self
class Application:
window = 160
downlimit = -20
indexCloseDict = {}
least = LeastSquare()
loopBack = LoopBack()
queryStock = QueryStock()
avgCostGrad = 0
cvValue = -1
maxPrice = 0
currentPrice = 0
isDownLine = 0
def setStackCode(self):
least = LeastSquare()
draw = DrawPicture()
loopBack = LoopBack()
queryStock = QueryStock()
queryStock.init(self.window)
self.indexCloseDict = {}
return
#筹码计算
def chipCalculate(self, result, start, isProd):
chipCalculateList = []
for index, row in result.iterrows():
temp = []
currentIndex = index - start
temp.append(currentIndex)
temp.append(row['open'])
temp.append(row['high'])
temp.append(row['low'])
temp.append(row['close'])
temp.append(row['volume'])
temp.append(row['tprice'])
temp.append(row['turn'])
temp.append(int(row['tradestatus']))
chipCalculateList.append(temp)
if isProd == False:
chipCalculateList = chipCalculateList[-112:]
calcualate = ChipCalculate()
resultEnd = calcualate.getDataByShowLine(chipCalculateList)
del calcualate
return resultEnd
def cv(self, temp):
# print(temp)
# minTemp=temp[0][1]
# for i in range(len(temp)):
# if temp[i][1]!=0 and temp[i][1]<minTemp:
# minTemp=temp[i][1]
# print(minTemp)
# temp[:,1]=temp[:,1]-minTemp
sumF = np.sum(temp[:, 1])
sumfx = 0
sumfdoubleX = 0
for i in range(len(temp)):
#次数
f = temp[i][1]
price = (temp[i][0] / 100)
sumfx = sumfx + f * price
sumfdoubleX = sumfdoubleX + f * price * price
sumfx = sumfx * sumfx
rightup = sumfx / sumF
result = math.sqrt((sumfdoubleX - rightup) / sumF)
print("--方差" + str(result))
return result
#执行器
def execute(self, code):
result = self.queryStock.queryStock(code)
if len(result[0]) < 200:
return self
return self.core(result[0], result[1])
#核心调度器
def core(self, result, maxPrice):
self.maxPrice = maxPrice
#十四天
Kflag = self.least.everyErChengPrice(result, 14, False)
#三十天
erjieSlow = self.least.everyErChengPrice(result, 30, False)
# 三天二阶导数
erjieK = self.least.doubleErJie(Kflag, 3, False)
#慢速一阶导数
wangXSlow = []
wangYSlow = []
for item in erjieSlow:
kX1 = item[0]
kk1 = item[1]
wangXSlow.append(kX1)
wangYSlow.append(kk1)
yijieSlowdict = dict(zip(wangXSlow, wangYSlow))
# 筹码计算
resultEnd = self.chipCalculate(result, self.queryStock.start, False)
choumaList = np.array(resultEnd[2][2])
x = []
p = []
resultEnd.sort(key=lambda resultEnd: resultEnd[0])
for i in range(len(resultEnd)):
x.append(resultEnd[i][0])
p.append(resultEnd[i][1])
myResult = pd.DataFrame()
myResult['tprice'] = p
tianjingle = self.least.everyErChengPriceForArray(
np.array(x), np.array(p), 30)
x1 = []
y1 = []
if tianjingle == None:
return
for item in tianjingle:
kX = item[0]
kk = item[1]
x1.append(kX)
y1.append(kk)
pingjunchengbendic = dict(zip(x1, y1))
total = len(result)
for i in range(len(erjieK)):
item = erjieK[i]
currentx = item[0]
onkslow = yijieSlowdict.get(currentx)
onkchengben = pingjunchengbendic.get(currentx)
if onkslow == None or onkchengben == None:
continue
if onkslow < 0 and onkchengben < 0:
onslowyestaday = yijieSlowdict.get(currentx - 1)
chengbenyestaday = pingjunchengbendic.get(currentx - 1)
if onslowyestaday == None or chengbenyestaday == None:
continue
if onslowyestaday < 0 and chengbenyestaday < 0 and onslowyestaday < onkslow and onkchengben < chengbenyestaday:
if currentx == total - 1:
self.avgCostGrad = onkchengben
self.cvValue = self.cv(choumaList)
self.currentPrice = float(result['close'][len(result) -
1])
if self.currentPrice <= self.maxPrice * 0.618:
self.isDownLine = 1
else:
self.isDownLine = 0
print(self.currentPrice)
print(self.maxPrice)
print(self.isDownLine)
self.least = None
self.loopBack = None
self.queryStock = None
return self
def doSendStatisticForZsm(self):
query = QueryStock()
result = query.queryStockYouBrought("zsm=1")
self.sendStatistic(result, " 回踩反弹-统计")
result = query.queryStockYouBrought("zsm=2")
self.sendStatistic(result, " 底部吸筹-统计")
def doSendStatisticPaper(self):
query = QueryStock()
#暂时统计0.618以下的
result = query.queryStockYouBrought(
"is_down_line=1 and profit!=0 and price<=10 and price>3")
self.sendStatistic(result, " zMain吸筹统计")