def __init__(self, path = '~/'):
data_path = os.path.join(path, ".rqalpha")
data_bundle_path = os.path.join(os.path.expanduser(data_path), "bundle")
if not os.path.isdir(data_bundle_path ):
print("not exist this file", data_bundle_path)
exit(-1)
data_source = BaseDataSource(data_bundle_path)
self.data_source_ = data_source
Instru = InstrumentMixin(data_source._instruments._instruments)
self.sym_inst_ = Instru
self.insts_ = data_source._instruments._instruments
if not os.path.exists(path_market):
os.makedirs(path_market)
scu = SCU(path=path)
stocks = scu.stock_codes_remove_no_stock_basic()
stocks = scu.add_allstock_xshg_xshe(stocks)
#rqa.update_bundle()
rqalpha_path = r"~/.rqalpha"
data_bundle_path = os.path.join(os.path.expanduser(rqalpha_path), "bundle")
if not os.path.isdir(data_bundle_path):
print("not exist this file", data_bundle_path)
exit(-1)
data_source = BaseDataSource(data_bundle_path)
Instru = InstrumentMixin(data_source._instruments._instruments)
# for stock_code in stocks:
# print('procesing...',stock_code)
# stock_data = pd.DataFrame(data_source._all_day_bars_of(Instru.instruments(stock_code)))
# stock_data.datetime = stock_data.datetime.apply(lambda x: datetime.strptime(str(x)[:-6],'%Y%m%d'))
# stock_data.to_csv(os.path.join(path_market,stock_code[:-5]+'.csv'),index=False)
date_time = date(2019, 9, 5)
bars = data_source.history_bars(instrument = Instru.instruments('603032.XSHG'), bar_count = 100,
frequency = '1d', fields = 'close', dt = date_time,
skip_suspended=False, adjust_orig = date_time)
bar_series = pd.Series(bars)
bar_pct = bar_series.pct_change()
bar_means = np.mean(bar_pct)
bar_vars = np.var(bar_pct)
path = '../../../data/'
path_market = os.path.join(path, 'trade_market')
if not os.path.exists(path_market):
os.makedirs(path_market)
scu = SCU(path=path)
stocks = scu.stock_codes_remove_no_stock_basic()
stocks = scu.add_allstock_xshg_xshe(stocks)
#rqa.update_bundle()
rqalpha_path = "~/.rqalpha"
data_bundle_path = os.path.join(os.path.expanduser(rqalpha_path), "bundle")
data = BaseDataSource(data_bundle_path)
Instru = InstrumentMixin(data._instruments._instruments)
for stock_code in stocks:
print('procesing...', stock_code)
stock_data = pd.DataFrame(
data._all_day_bars_of(Instru.instruments(stock_code)))
stock_data.datetime = stock_data.datetime.apply(
lambda x: datetime.strptime(str(x)[:-6], '%Y%m%d'))
stock_data.to_csv(os.path.join(path_market, stock_code[:-5] + '.csv'),
index=False)
sec_name = []
sec_index = []
for k, v in Instru._sym_id_map.items():
sec_name.append(k)
sec_index.append(v)