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 signal_run(dss):
all_dates = get_trading_dates(dss)
date = all_dates[-1]
#print(codes)
r1 = calc_signal_buy(dss, date)
r2 = calc_signal_sell(dss, date)
df = pd.DataFrame(r1 + r2, columns=['date', 'code', 'stratege'])
filename = dss + 'csv/signal_macd.csv'
df.to_csv(filename, index=False, mode='a', header=None)
return r1 + r2
def up_run(dss):
all_dates = get_trading_dates(dss)
begin_date = all_dates[-1]
end_date = all_dates[-1]
begin_date = '2019-06-26'
end_date = '2019-06-28'
codes = get_stk_codes(dss)
# codes = ['002454','300433','002570','300136','002273','300073']
#print(codes)
r = signal_k_pattern(dss, codes, begin_date, end_date)
df = pd.DataFrame(r, columns=['date', 'code', 'strategy', 'expire'])
#filename = dss + 'csv/bottle.csv'
filename = 'a1.csv'
df.to_csv(filename, index=False, mode='a', header=None)
def run_price_signal():
try:
now = datetime.datetime.now()
weekday = int(now.strftime('%w'))
if 2 <= weekday <= 6:
dates = get_trading_dates(dss)
today = dates[-1]
arr = price_signal(dss, today)
r = []
for a in arr:
r.append(str(a))
#print(str(r))
send_email(dss, 'price_signal', '\n'.join(r))
except Exception as e:
s = traceback.format_exc()
to_log(s)
def down_daily_run(dss):
listfile = os.listdir(dss + 'daily')
listfile.sort(reverse=True)
lastday = listfile[0][:10]
print(lastday)
dates = get_trading_dates(dss, lastday)
dates.pop(0) #担心daily数据更新不及时
#dates = ['2019-04-01']
for today in dates:
fss = dss + 'daily/' + today + '_stk_all.csv'
try:
if os.path.exists(fss):
print('exist', today)
else:
df = ts.get_day_all(today)
df.to_csv(fss, index=False, encoding='gbk')
print('got ', today)
except:
print('error ', today)
r = []
for i, row in df1.iterrows():
# print(row.code, row['name'], row.p_change)
if be_bottom(row.code, day):
df2 = pro.concept_detail(ts_code=get_ts_code(row.code))
concept = str(df2.concept_name.tolist())
r.append([day, row.code, row['name'], row.p_change, concept])
# 拷贝数据文件到下载目录，以备下载。windows下一定要用\\
ins = 'copy ' + get_dss(
) + 'hfq\\' + row.code + '.csv ' + 'C:\\Users\\Administrator\\Downloads\\' + row.code + '_' + row[
'name'] + '.csv '
print(ins)
os.system(ins)
#break
df = pd.DataFrame(r, columns=['date', 'code', 'name', 'change', 'concept'])
fn = get_dss() + 'csv/price_signal.csv'
df.to_csv(fn, index=False, mode='a')
return r
if __name__ == '__main__':
dates = get_trading_dates(get_dss())
#preday = dates[-2]
today = dates[-1]
print(today)
r = price_signal(get_dss(), today)
print(r)