def get_code():
r = ts.RemoteCallFunc('Option_Contract', {}, {})
print(r[1])
return tsbytestostr(r[1])
def getTSdata_day(sdate, edate, stockID, cy):
'''通过天软获取日线'''
d2 = ts.RemoteCallFunc('MyGetTimeSeries', [sdate, edate, stockID, cy], {})
if d2[0] == 0:
return d2[1]
else:
print(d2[2])
# 搞成天软格式的时间
# 起始日
sdate = ts.EncodeDate(2017, 6, 4)
# 终止日
edate = ts.EncodeDate(2018, 6, 4)
# 天软时间变正常时间
# ts.DecodeDate(43200)
# stock1='IC01' # 天软里面的当月连续
# stock2='IC02' # 天软里面的次月连续
#
# 获取期货合约代码
# 周期
cy = '1分钟线'
setsysparam(pn_date(),inttodate({0}));
return
Query("A股","",True,"","代码",DefaultStockID(),
"名称",CurrentStockName(),
"最高价",high(),
"最低价",low(),
"昨收",StockPrevClose3(),
"收盘价",close(),
"开盘价",open(),
"涨幅(%)",StockZf3(),
"换手率(%)",StockHsl3(),
"量比",volrate(),
"对数收益率(%)",StockLnZf3(),
"是否下跌",IsDown(),
"是否上涨",IsUp(),
"是否平盘",IsEqual(),
"指定日是否一字涨停({1})",StockIsZt2(42466),
"指定日是否一字跌停({2})",StockIsDt2(42437),
"是否涨停({3})",StockIsZt(38450),
"是否跌停({4})",StockIsDt(38450),
"是否曾经涨停({5})",StockIsCJZt(38450),
"是否曾经跌停({6})",StockIsCJDt(38450),
"最新总市值(万)",StockTotalValue3(),
"最新流通市值(万)",StockMarketValue3(),
"市盈率(最近12个月)(类型=0)",StockPE3_V(0),
"市盈率(专用)(类型=0)",StockPE3_IV(0),
"市净率(最新财务数据)",StockPNA3_II());
""".format(date, date, date, date, date, date, date)
d2 = TSLPy3.RemoteExecute(t1, {})[1]
df5 = change_code(pd.DataFrame(d2))
# -*- coding: utf-8 -*- # @Time : 2018/12/20 16:07 # @Author : Big Huang # @Email : [email protected] # @File : tslfun.py # @Software: PyCharm import pandas as pd import sys import datetime sys.path.append(r"E:\software\Analyse.NET") import TSLPy3 as ts ts.ConnectServer("tsl.tinysoft.com.cn", 443) dl = ts.LoginServer("indexsh","888888") #Tuple(ErrNo,ErrMsg) 登陆用户 assert dl[0] == 0 print("登陆成功") print("服务器设置:", ts.GetService()) ts.SetComputeBitsOption(64) # 设置计算单位 print("计算位数设置:", ts.GetComputeBitsOption()) def tsl_fun(start_date: datetime.datetime, end_date:datetime.datetime): start_date_str = start_date.strftime("%Y-%m-%d") end_date_str = end_date.strftime("%Y-%m-%d") # data = ts.RemoteExecute("return 'return a string';",{}) #执行一条语句 data = ts.RemoteCallFunc("big", [start_date_str, end_date_str, "SH000050"], {}) df = pd.DataFrame(data[1]) df.columns = df.columns.map(lambda x: x.decode("gbk")) for col, dtype in df.dtypes.iteritems(): if dtype.name == "object": df[col] = df[col].str.decode("gbk")
def getTickDetails(self, BegDate, EndDate, contract_code, symbol):
# tick_details = pd.DataFrame(self.tsbytestostr(ts.RemoteExecute( '''a:=select ["StockID"],["StockName"],["date"],["price"],["vol"],["amount"],["cjbs"],["yclose"],["syl1"],["syl2"],["buy1"],["sale1"],["bc1"],["sc1"] from tradetable datekey %s+21/24 to %s+16/24 of '%s' end;b:=update a set ['date']=datetimetostr(['date']) end;return a;''' % (
# ts.LocalCallFunc("StrToDate", [BegDate])[1], ts.LocalCallFunc("StrToDate", [EndDate])[1], contract_code),{}))[1])
# tick_details.to_csv('%s%s_%s.csv'%(path,symbol,EndDate),index=False)
# return tick_details
# tick_details = pd.DataFrame(self.tsbytestostr(ts.RemoteExecute(
# '''a:=select ["StockID"],["StockName"],["date"],["price"],["vol"],["amount"],["cjbs"],["yclose"],["syl1"],["syl2"],["buy1"],["sale1"],["bc1"],["sc1"] from tradetable datekey %s+21/24 to %s+16/24 of '%s' end;b:=update a set ['date']=datetimetostr(['date']) end;return a;''' % (
# ts.LocalCallFunc("StrToDate", [BegDate])[1], ts.LocalCallFunc("StrToDate", [EndDate])[1], contract_code),
# {}))[1])
if self.mc is None:
# self.mc = mongodb_client()
self.mc.dbConnect()
# dateList=self.getTradeDays(
# (datetime.datetime.strptime(BegDate, '%Y-%m-%d') - datetime.timedelta(3)).strftime('%Y-%m-%d'), EndDate)
# BegDateAdj=dateList[max(0,dateList.index(BegDate)-1)]
tick_dict = self.tsbytestostr(
ts.RemoteExecute(
'''a:=select ["StockID"],["StockName"],["date"],["price"],["vol"],["amount"],["cjbs"],["yclose"],["syl1"],["syl2"],["buy1"],["sale1"],["bc1"],["sc1"] from tradetable datekey %s to %s+0.9999999 of '%s' end;b:=update a set ['date']=datetimetostr(['date']) end;return a;'''
% (ts.LocalCallFunc("StrToDate", [BegDate])[1],
ts.LocalCallFunc("StrToDate", [EndDate])[1], contract_code),
{}))[1]
# datetime.datetime.strptime(tick_dict['date'][0], '%Y-%m-%d %H:%M:%S').replace(microsecond=500000)
last_tick_datetime = None
count = 0
for d in tick_dict:
tick = CtaTickData()
tick.vtSymbol = d['StockName']
tick.symbol = d['StockID'] # 合约代码 CF1705 StockID
# tick.exchange = EMPTY_STRING # 交易所代码
# 成交数据
tick.lastPrice = d['price'] # 最新成交价
tick.volume = d['vol'] #最新成交量
tick.amount = d['amount'] # 成交金额
tick.cjbs = d['cjbs'] # 周期内成交笔数
tick.yclose = d['yclose'] # 上一收盘价
tick.preSettlement = d['syl2'] # 上一日结算价
# tick的时间
# 转换为datetime格式
try:
if len(d['date']) > 10:
tick.datetime = datetime.datetime.strptime(
d['date'], '%Y-%m-%d %H:%M:%S') # python的datetime时间对象
else:
tick.datetime = datetime.datetime.strptime(
d['date'], '%Y-%m-%d')
tick.date = tick.datetime.strftime('%Y-%m-%d') # 日期
tick.time = tick.datetime.strftime('%H:%M:%S') # 时间
# tick.tradingDay = d['price'] # 交易日期
except Exception as ex:
# 抛弃本tick
print('日期转换错误:%s,error:%s' % (d['date'], ex))
continue
# 1档行情
tick.bidPrice1 = d['buy1']
tick.askPrice1 = d['sale1']
tick.bidVolume1 = d['bc1']
tick.askVolume1 = d['sc1']
# 修正毫秒
if tick.datetime.replace(microsecond=0) == last_tick_datetime:
# 与上一个tick的时间（去除毫秒后）相同,修改为500毫秒
tick.datetime = tick.datetime.replace(microsecond=500000)
tick.time = tick.datetime.strftime('%H:%M:%S.%f')
else:
tick.datetime = tick.datetime.replace(microsecond=0)
tick.time = tick.datetime.strftime('%H:%M:%S.%f')
# 记录最新tick的时间
last_tick_datetime = tick.datetime
if symbol == 'TC':
symbol = 'ZC'
if symbol == 'RO':
symbol = 'OI'
if symbol == 'ER':
symbol = 'RI'
if symbol == 'WS':
symbol = 'WH'
if symbol == 'ME':
symbol = 'MA'
self.mc.dbInsert('FUTURE_TICK_DB',
'TS_%s_TickDatas' % symbol,
d=tick.__dict__)
count = count + 1
print('写入合约%s完成，共%d条' % (contract_code, count))
return
def __enter__(self):
if ts.Logined() is False:
print('天软未登陆或客户端未打开，将执行登陆操作')
self.__tsLogin()
return self
def __exit__(self, *arg):
ts.Disconnect()
print('天软连接断开')
def decode_date(dt):
dt_decode = tsl.DecodeDate(dt)
return pd.Timestamp(*dt_decode)
def run_script(script, sysparams):
data = tsl.RemoteExecute(script, sysparams)
return data
def __exit__(self, *arg):
ts.Disconnect()
def encode_datetime(dt):
return tsl.EncodeDateTime(dt.year, dt.month, dt.day, dt.hour, dt.minute,
dt.second, 0)
def __enter__(self):
if ts.Logined() is False:
self.__tsLogin()
return self
def TSDate(Y, M, D):
d = tp.EncodeDate(Y, M, D)
return d
import os
import sys
sys.path.append("C:\Program Files\Tinysoft\Analyse.NET")
import traceback
import pickle
import datetime
# from WindPy import *
# 实际上我有这个模块的，但是pycharm找不到，我也没办法
import TSLPy3 as ts
ts.DefaultConnectAndLogin("test") #调用函数登陆
def tsbytestostr(data):
"把gbk的字符转化为uft的字符"
if (isinstance(data, (tuple)) or isinstance(data, (list))):
lendata = len(data)
ret = []
for i in range(lendata):
ret.append(tsbytestostr(data[i]))
elif isinstance(data, (dict)):
lendata = len(data)
ret = {}
for i in data:
ret[tsbytestostr(i)] = tsbytestostr(data[i])
def autoOrder():
now = datetime.datetime.now()
hour = int(now.strftime("%H%M"))
#if hour > 1500 or hour < 930:
# print('autoOrder not running time :' + str(hour))
# return
#dayOfWeek = int(now.strftime("%w"))
#if dayOfWeek == 0 or dayOfWeek == 6:
# print('autoOrder not running day :' + str(dayOfWeek))
# return
date = now.strftime("%Y-%m-%d")
orderRuleList = OrderRule.objects.using('stockdb').filter(
isvalid="1", expiretime__gt=date + ' 23:59:59')
orderLogNewList = []
url = "http://47.100.100.244:3000/stock/publish?message="
message = ""
for orderRule in orderRuleList:
try:
#判断当天该股票是否已经自动下单
orderLog = OrderLog.objects.filter(datetime__contains=date,
stockId=orderRule.stockId)
print(orderRule.stockId)
if orderLog:
print('already order')
continue
#判断因子是否达标
isMatch = matchRule(orderRule, date)
print(isMatch)
if not isMatch:
continue
#获取实时价格，获取失败时不发送信息
orderPrice = orderRule.orderPrice
if orderPrice == 0.00:
returnData = TSLPy3.RemoteCallFunc("stock_realtime_data",
[orderRule.stockId], {})
if returnData[0] == 0:
orderPrice = returnData[1][b'close']
else:
print(returnData[2].decode('gbk'))
continue
#拼装消息字符串
stockMessage = "b," + orderRule.stockId[2:] + ',' + str(
orderPrice) + ',' + str(orderRule.orderQuantity)
if message == '':
message = stockMessage
else:
message = message + ";" + stockMessage
#初始化下单日志对象
orderLogNew = OrderLog(datetime=datetime.datetime.now().strftime(
"%Y-%m-%d %H:%M:%S.%f"),
stockId=orderRule.stockId,
stockName=orderRule.stockName,
orderPrice=orderPrice,
orderQuantity=orderRule.orderQuantity,
request=stockMessage,
response=str(orderRule.id))
orderLogNewList.append(orderLogNew)
except KeyError:
break
print(url + message)
#消息不为空时发送消息
if message != '':
req = Request(url + message)
response = urlopen(req)
responseData = response.read().decode('utf-8')
if responseData.find("发布消息成功") != -1:
#发送成功将规则设置为失效，并更新日志的返回信息字段
for log in orderLogNewList:
rule = OrderRule.objects.using('stockdb').get(
id=int(log.response))
rule.isvalid = '0'
rule.ordertime = log.datetime
rule.save()
log.response = responseData
OrderLog.objects.bulk_create(orderLogNewList)
insertTaskLog(now.strftime("%Y-%m-%d %H:%M:%S.%f"),
datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f"),
'autoOrderRule', 'success', '', 0)
def m_options_daily_market(date):
d = ts.RemoteCallFunc("m_options_daily_market", [date], {})
return (tsbytestostr(d[1]))
def getData(sDate, intervel, sContract):
#intervel 表示数据间隔要5秒的，还是一分钟数据，还是日线数据 e.g "5s"
#contract 合约名称 e.g "sc"
try:
os.makedirs('E:\CLionProjects\HedgeArbitrage/data')
except:
pass
while True:
ts.ConnectServer('211.100.23.205', 443)
ts.LoginServer('fuchunguang', 'Fcg=888888')
if ts.Logined() == True:
print('already login')
daycount = 0
for code in sContract:
hdateInfo = {}
notNullcounter = 0
for date in sDate:
daycount += 1
if intervel == '1m':
temp1 = 'cy_1m()'
temp2 = 240
elif intervel == '5s':
temp1 = 'cy_5s()'
temp2 = 2880
sql = 'setsysparam(pn_stock(),\'{}\');' \
'setsysparam(PN_Cycle(), {});setsysparam(pn_date(),inttodate({}));' \
'return nday({},"mdate",datetimetostr(sp_time()),"open",Open(),"high",High(),"low",Low(),"close",Close(),"vol",Vol(),"amount",Amount());' \
.format(code, temp1,date, temp2)
result = (ts.RemoteExecute(sql, {}))[1]
if result:
for data in result:
temp = data[b'mdate'].decode('gbk').replace(
':', '').replace('-', '').replace(' ', '')
if len(temp) < 14:
temp += '0' * (14 - len(temp))
if int(sDate[0]) <= int(temp[:8]) <= int(
sDate[-1]):
notNullcounter += 1
hdateInfo[temp] = [
data[b'open'], data[b'high'], data[b'low'],
data[b'close'], data[b'vol'],
data[b'amount']
]
print(temp)
# print('{},{},{},{},{},{},{},{}\n'.format(code,
# temp,
# data[b'open'],
# data[b'high'],
# data[b'low'],
# data[b'close'],
# data[b'vol'],
# data[b'amount']))
if notNullcounter:
with open(
'E:\CLionProjects\HedgeArbitrage/data/{}_{}.js'.
format(code, intervel), 'w') as f:
json.dump(hdateInfo, f)
ts.Disconnect()
break
else:
print('not login ')
return 0
def get_date_option(code, date):
d = ts.RemoteCallFunc("Option_byDateFuture", [code, date], {})
return (tsbytestostr(d[1]))
def __tsLogin(self):
ts.ConnectServer("tsl.tinysoft.com.cn", 443)
dl = ts.LoginServer("fzzqjyb", "fz123456")
print('天软登陆成功')
def getTradeDays(self, start, end):
daysList = self.tsbytestostr(
ts.RemoteExecute(
"begt:=strtodate('%s');endt:=strtodate('%s');return datetostr(spec(specdate(nday3(tradedays(begt,endt),sp_time()),endt),'SH000001'));"
% (start, end), {}))
return daysList[1]
return d2[1]
else:
print(d2[2])
if __name__ == '__main__':
cy = '日线'
dfcode = pd.read_excel('stockcode.xlsx')
stockcode = dfcode['代码'].tolist()
# 搞成天软格式的时间
# 起始日
sdate = ts.EncodeDate(2017, 1, 1)
# 终止日
edate = ts.EncodeDate(2019, 10, 20)
# 获取交易日序列
dateS = getTSdate(sdate, edate)
# 解析结果的list
s2_close = []
s2_low = []
s2_datetime = []
s2_high = []
s2_code = []
df2 = pd.DataFrame() # 整理所有数据
def update_rank(self):
tsl = tslFunctions()
tsl.tsl_login()
# conn_Local=create_engine(str(r"mysql+pymysql://root:xxxx@localhost:3306/test"))
conn_Local = create_engine(
str(r"mysql+pymysql://root:[email protected]:3306/test"))
self.__start=(dt.parser.parse(str(pd.read_sql("select max(截止日) from rank_raw",con=conn_Local\
).values[0][0]))+datetime.timedelta(days=1)).strftime('%Y-%m-%d')
tradedaysList = tsl.getTradeDays(self.__start, self.__end)
print(tradedaysList)
if len(tradedaysList) == 0:
print("已经更新至最新日期%s" % self.__end)
return
for tday in tradedaysList:
update_rank_raw = pd.DataFrame(
tsl.tsbytestostr(
ts.RemoteExecute(
f'''endt:={tday.replace('-','')+'T'};
X:=GetFuturesID('',endt);
r:=array();
for i:=0 to length(X)-1 do
begin
SetSysParam(PN_Stock(),x[i]);
Ret:= GetFuturesTradeRankingByDate(endt,t);
r&=t;
end;
return r;''', {})[1]))
if len(update_rank_raw) == 0:
print("No Datas")
else:
print(tday)
#can_l=update_cangdan_raw.截止日.unique()#记录下返回表的所有日期
update_rank_raw['utime'] = datetime.datetime.now()
update_rank_raw['机构简称2'] = update_rank_raw['机构简称'].apply(name)
update_rank_raw['code'] = update_rank_raw.代码.apply(
lambda x: re.split('\d+', x.upper())[0])
update_rank_raw.to_sql('rank_raw',
conn_Local,
if_exists='append',
index=False,
chunksize=5000)
#update_rank_raw.dropna(axis=1, inplace=True)
duo = update_rank_raw.loc[update_rank_raw.排名类型 == '持买单量排名']
kong = update_rank_raw.loc[update_rank_raw.排名类型 == '持卖单量排名']
rlt_duo = duo.groupby(['code', '截止日', '机构简称'],
as_index=False)['数量', '比上交易日增减'].sum()
rlt_duo['rename'] = rlt_duo['机构简称'].apply(name)
rank_duo = rankk(rlt_duo)
rank_duo.columns = [
'code', 'date', 'name', 'value', 'change', 'rename', 'rank'
]
rank_duo.to_sql('rank_long',
conn_Local,
if_exists='append',
index=False,
chunksize=5000)
rlt_kong = kong.groupby(['code', '截止日', '机构简称'],
as_index=False)['数量', '比上交易日增减'].sum()
rlt_kong['rename'] = rlt_kong['机构简称'].apply(name)
rank_kong = rankk(rlt_kong)
rank_kong.columns = [
'code', 'date', 'name', 'value', 'change', 'rename', 'rank'
]
rank_kong.to_sql('rank_short',
conn_Local,
if_exists='append',
index=False,
chunksize=5000)
ts.Disconnect()
