def main(indexname, dtstr):
# ----------------------------------------------------------------
indexspec = {
'r1000': cfg.r1000spec,
's500': cfg.s500spec,
'n100': cfg.n100spec,
}[indexname]
# ----------------------------------------------------------------
enddt = str_to_dt(dtstr)
startdt = enddt - datetime.timedelta(days=500)
run_single_spec = {
**indexspec,
"universe/opt/date_range/0": startdt,
"universe/opt/date_range/1": enddt,
}
print(run_single_spec)
# ----------------------------------------------------------------
(actions, rtcfg) = run_single(run_single_spec)
print(containerChecksum(rtcfg))
for action in actions:
print("#" * 80)
print('rundate', dt64_to_str(action['rundate']))
print('sysfilter', action['sysfilter'])
print('stageopen', action['stageopen'][1].tolist())
print('stageclose', action['stageclose'])
def load_history_for_symbols(symbols,pp_opt={},startdate=str_to_dt('1970-01-01'),enddate=None,interval="D"):
pp_opt_json = json.dumps(pp_opt)
pricehistory = {}
symbar = tqdm(symbols,leave=None,desc="history")
for symbol in symbar:
pricehistory[symbol] = load_history(symbol,pp_opt=pp_opt_json,startdate=startdate,enddate=enddate,interval=interval)
pricehistory = pd.concat(pricehistory.values(),keys=pricehistory.keys(),axis=1)
return pricehistory
def symbols_btw(self,startdate=None,enddate=None):
if(startdate is None):
startdate = str_to_dt('1970-01-01')
if(enddate is None):
enddate = datetime.datetime.now().date()
# --
uni = self.__membership
uni = uni[inrange(uni.index,ge=startdate,le=enddate)]
return uni.columns.to_numpy()
def trade_dates_btw_(self, startdate=None, enddate=None):
if (startdate is None):
# startdate = __0_date_str__('1970-01-01')
startdate = str_to_dt('1970-01-01')
if (enddate is None):
enddate = datetime.datetime.now().date()
# --
uni = self.__universe
# uni = uni[__inrange__(uni.index,ge=startdate,le=enddate)]
uni = uni[inrange(uni.index, ge=startdate, le=enddate)]
return list(uni.index)
def load_ng_index_membership(indexname,symbol,startdate=str_to_dt('1970-01-01'),enddate=None):
mbr_array = ng.index_constituent_timeseries(
symbol,
indexname,
start_date=startdate,
end_date=enddate,
padding_setting=ng.PaddingType.ALLWEEKDAYS,
format='pandas-dataframe')
mbr_array.rename(inplace=True,columns={"Index Constituent":symbol})
mbr_array.replace(0,math.nan,inplace=True)
return mbr_array
def load_history(symbol,pp_opt=None,startdate=str_to_dt('1970-01-01'),enddate=None,interval="D"):
ngprice = load_ng_historical(symbol,startdate=startdate,enddate=enddate,interval=interval).copy()
# --
ngprice.drop(inplace=True,columns=['Turnover','Dividend'])
ngprice.rename(inplace=True,columns={ 'Unadjusted Close':'Uclose' })
ngprice['note'] = ""
ngprice['last_n_bar'] = range(len(ngprice)-1,-1,-1)
# --
for pp in postprocessors(pp_opt) :
pp(symbol,ngprice)
return ngprice
def load_ng_historical(symbol,startdate=str_to_dt('1970-01-01'),enddate=None,interval="D"):
pricedata = ng.price_timeseries(
symbol,
stock_price_adjustment_setting = ng.StockPriceAdjustmentType.TOTALRETURN,
padding_setting=ng.PaddingType.ALLWEEKDAYS,
start_date = startdate,
end_date = enddate,
interval=interval,
format='pandas-dataframe'
)
return pricedata
"cls": demo1_entry_algo.demo1_entry_algo,
"opt": {
"pp": {
'lperiod': 200,
'speriod': 50,
},
},
},
"exitalgo": {
"cls": demo1_exit_algo.demo1_exit_algo,
"opt": {
"pp": {
'period': 60,
'multiple': 20,
'max_pct_risk': 0.35,
},
"op": {
'max_age': 650,
},
},
},
"universe": {
"cls": index_universe.IndexUniverse,
"opt": {
"indexname": "NASDAQ 100",
"date_range": [str_to_dt('2000-01-01'),
str_to_dt('2020-03-31')],
}
}
}