def use_ma(dss):
dates = get_trading_dates(dss)
preday = dates[-2]
today = dates[-1]
print(today)
#pfFile = dss + 'csv/hold.csv'
b1 = Book(dss)
codes = []
for tactic in b1.tactic_List:
if tactic.tacticName == 'boll':
for hold in tactic.hold_Array:
code = hold[0]
codes.append(code)
codes += hit_ma(dss, today)
r = []
symbols = set(codes)
print(symbols)
for vtSymbol in symbols:
df = ts.get_realtime_quotes(vtSymbol)
name = df.at[0, 'name']
r.append([vtSymbol, 1, 0.01, '0.00003', 0, 0.01, name])
df = pd.DataFrame(r,
columns=[
'vtSymbol', 'size', 'priceTick',
'variableCommission', 'fixedCommission', 'slippage',
'name'
])
filename = dss + 'csv/setting_stk_boll' + '.csv'
df.to_csv(filename, index=False)
return r
def loadHold(self):
"""每日重新加载持仓"""
b1 = Book(self.engine.dss)
for tactic in b1.tactic_List:
if tactic.tacticName == self.name:
for hold in tactic.hold_Array:
code = hold[0]
num = hold[2]
self.posDict[code] = num
def stare_hold():
print('stare_hold begin... ')
loaded = False
codes = ()
mailed = []
while True:
time.sleep(30)
if is_price_time():
# 读入codes
if not loaded:
b1 = Book(dss)
codes = b1.get_codes()
loaded = True
for code in codes:
try:
time.sleep(1)
df = ts.get_realtime_quotes(code)
name = df.at[0, 'name']
price = float(df.at[0, 'price'])
pre_close = float(df.at[0, 'pre_close'])
#print(code, price, pre_close)
if code not in mailed:
if price / pre_close - 1 > 0.05:
send_email(dss, 'up_warn', str(code + ' ' + name))
#print('up_warn', str(code+' '+name))
mailed.append(code)
if price / pre_close - 1 < -0.05:
send_email(dss, 'down_warn',
str(code + ' ' + name))
#print('down_warn', str(code+' '+name))
mailed.append(code)
except Exception as e:
print('error')
print(e)
else:
loaded = False
codes = ()
mailed = []
time.sleep(300)
def on_order_done(order_dict):
#to_log( 'in on_order_done ' + str(order_dict.keys()) )
for key in order_dict.keys():
ins_dict = order_dict[key]
if ins_dict['done'] == False:
try:
#to_log( 'in on_order_done ' + str(ins_dict) )
df_q = ts.get_realtime_quotes(ins_dict['code'])
name = df_q.at[0, 'name']
price_now = float(df_q.at[0, 'price'])
#to_log(name + price_now)
if ins_dict['ins'] == 'buy_order' and ins_dict[
'price'] > price_now:
b1 = Book(dss)
b1.deal_ins(ins_dict.copy())
ins_dict['done'] = True
if ins_dict['ins'] == 'sell_order' and ins_dict[
'price'] < price_now:
b1 = Book(dss)
b1.deal_ins(ins_dict.copy())
ins_dict['done'] = True
except Exception as e:
to_log('error in on_order_done')
to_log(e)
import time
import os
import pandas as pd
import tushare as ts
from nature import Book
dss = 'ini\\'
b1 = Book(dss, 'hold_security.csv')
ins_dict = {
'ins': 'open_portfolio',
'portfolio': 'overlap',
'code': 'profit',
'agent': 'pingan'
}
#ins_dict = {'ins':'close_portfolio', 'portfolio':'overlap','agent':'pingan'}
b1.deal_ins(ins_dict)
import time import os import pandas as pd import tushare as ts from nature import Book dss = 'ini\\' b1 = Book(dss,'hold_security.csv') b1.pandian()