def output_feeds(instrument: str, st: datetime, et: datetime, short_win: int,
long_win: int, ema_period: int,
save_dir: str) -> pd.DataFrame:
"""
Output ohlc price feeds to csv for strategy back testing
:param instrument: ccy_pair
:param st: start date
:param et: end date
:param short_win:
:param long_win:
:param ema_period:
:param save_dir:
:return:
"""
pd_h1 = read_price_df(instrument=instrument,
granularity='H1',
start=st,
end=et)
pd_h1[f'last_{long_win}_high'] = pd_h1['high'].rolling(window=long_win *
24).max()
pd_h1[f'last_{short_win}_high'] = pd_h1['high'].rolling(window=short_win *
24).max()
pd_h1[f'last_{long_win}_low'] = pd_h1['low'].rolling(window=long_win *
24).min()
pd_h1[f'last_{short_win}_low'] = pd_h1['low'].rolling(window=short_win *
24).min()
pd_h1.to_csv(f'{save_dir}/{instrument.lower()}_h1.csv')
pd_d = read_price_df(instrument=instrument,
granularity='D',
start=st,
end=et)
pd_d[f'last_{long_win}_high'] = pd_d['high'].rolling(window=long_win).max()
pd_d[f'last_{short_win}_high'] = pd_d['high'].rolling(
window=short_win).max()
pd_d[f'last_{long_win}_low'] = pd_d['low'].rolling(window=long_win).min()
pd_d[f'last_{short_win}_low'] = pd_d['low'].rolling(window=short_win).min()
pd_d['atr'] = TA.ATR(pd_d, period=14)
pd_d['adx'] = TA.ADX(pd_d, period=14)
pd_d['rsi'] = TA.RSI(pd_d, period=14)
pd_d[f'ema_{ema_period}'] = TA.EMA(pd_d, period=ema_period)
pd_d.to_csv(f'{save_dir}/{instrument.lower()}_d.csv')
pd_h1.reset_index(level=0, inplace=True)
pd_merged = pd_h1.apply(partial(enrich, pd_d, ema_period),
axis=1).set_index('time')
logger.info(pd_merged.info())
pd_merged.to_csv(f"{save_dir}/{instrument.lower()}_h1_enrich.csv")
logger.info(f'output feeds complete for [{instrument}]!')
return pd_merged
def output_feeds(instrument: str,
short_win: int,
long_win: int,
ema_period: int,
save_dir: str,
st: datetime,
et: datetime = None) -> pd.DataFrame:
"""
Output daily ohlc price feeds to csv
:param instrument: ccy_pair
:param st: start date
:param et: end date
:param short_win:
:param long_win:
:param ema_period:
:param save_dir:
:return:
"""
pd_d = read_price_df(instrument=instrument,
granularity='D',
start=st,
end=et)
pd_d[f'last_{long_win}_high'] = pd_d['high'].rolling(window=long_win).max()
pd_d[f'last_{short_win}_high'] = pd_d['high'].rolling(
window=short_win).max()
pd_d[f'last_{long_win}_low'] = pd_d['low'].rolling(window=long_win).min()
pd_d[f'last_{short_win}_low'] = pd_d['low'].rolling(window=short_win).min()
pd_d['atr'] = TA.ATR(pd_d, period=14)
pd_d['adx'] = TA.ADX(pd_d, period=14)
pd_d['rsi'] = TA.RSI(pd_d, period=14)
pd_d[f'ema_{ema_period}'] = TA.EMA(pd_d, period=ema_period)
pd_d.to_csv(f'{save_dir}/{instrument.lower()}_d.csv')
logger.info(f'output feeds complete for [{instrument}]!')
return pd_d