@nicostro
Here is Supertrend indicator
https://github.com/mementum/backtrader/pull/374/files

@Wayne-Filkins
resample data means if you have minute of data and you want to convert it into 15 minutes period or 30 minutes period etc...

@vladisld
ok i am checking thanks for your help

I am translating Thinkorswim strategy into to backtrader need help translating TOS built in function in backtrader

https://github.com/sureshja/ThinkOrSwim/blob/master/HeikinAshiSuperTrendStrategy.ts

input aggrPd1 = AggregationPeriod.FOUR_HOURS;
def haop1 = CompoundValue(1, (haop1[1] + hacl1[1]) / 2, (open(period = aggrPd1)[1] + close(period = aggrPd1)[1]) / 2);

compound value reference
https://tlc.thinkorswim.com/center/reference/thinkScript/Functions/Others/CompoundValue

Here is code i have used it and its working perfectly also there resample it

if not alpaca_paper:
  broker = store.getbroker()  # or just alpaca_backtrader_api.AlpacaBroker()
  cerebro.setbroker(broker)

DataFactory = store.getdata  # or use alpaca_backtrader_api.AlpacaData
data0 = DataFactory(
    dataname='AAPL',
    timeframe=bt.TimeFrame.TFrame("Minutes"),
    fromdate=pd.Timestamp('2018-11-15'),
    todate=pd.Timestamp('2018-11-17'),
    historical=True)
cerebro.adddata(data0)
#Resampler for 15 minutes
cerebro.resampledata(data0,timeframe=bt.TimeFrame.Minutes,compression=15)

@mudassar031
full code example using alpaca api with TimeFrame.minutes and resample data

import alpaca_backtrader_api
import backtrader as bt
import pandas as pd
from datetime import datetime
from strategies.tos_strategy import TOS

from dotenv import load_dotenv
import os
load_dotenv()

api_key = os.getenv('API_KEY_ID')
api_secret = os.getenv('API_SECRET')
alpaca_paper = os.getenv('ALPACA_PAPER')

cerebro = bt.Cerebro()
cerebro.addstrategy(TOS)

cerebro.broker.setcash(100000)
cerebro.broker.setcommission(commission=0.0)
cerebro.addsizer(bt.sizers.PercentSizer, percents=20)

store = alpaca_backtrader_api.AlpacaStore(
    key_id=api_key,
    secret_key=api_secret,
    paper=alpaca_paper
)

if not alpaca_paper:
  broker = store.getbroker()  # or just alpaca_backtrader_api.AlpacaBroker()
  cerebro.setbroker(broker)

DataFactory = store.getdata  # or use alpaca_backtrader_api.AlpacaData
data0 = DataFactory(
    dataname='AAPL',
    timeframe=bt.TimeFrame.TFrame("Minutes"),
    fromdate=pd.Timestamp('2018-11-15'),
    todate=pd.Timestamp('2018-11-17'),
    historical=True)
cerebro.adddata(data0)

#Resampler for 15 minutes
cerebro.resampledata(data0,timeframe=bt.TimeFrame.Minutes,compression=15)

print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.run()
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
cerebro.plot()

@Wayne-Filkins
perfect

@run-out
Thanks for your help i am checking and update you if needed something

I want to compare next bar data
self.data.close[-1] > self.l.super_trend[-1] means previous values so how can i access next bar values ?

i am trying like this

if self.data.close[1] > self.l.super_trend[1] and self.data.close[0] < self.l.super_trend[0]:
               self.log('BUY CREATE, %.2f' % self.data.close[0])
               # adds buy to self.order so we can run the check above
               self.order = self.buy()

this code throwing error
Thanks

@vladisld
thanks for your reply
actually i have interpreted thinkorswim strategy in backtrader i am on last step buy or sell order and they are following same way as i have mentioned above, so i want to know one thing Backtrader support AI/ML to predict future values, as you mention "As a side note: using the information from the future is not a good idea in general ( it will definitely not work in real time trading)"

@vladisld
thanks for your reply
actually i have interpreted thinkorswim strategy in backtrader i am on last step buy or sell order and they are following same way as i have mentioned above, so i want to know one thing Backtrader support AI/ML to predict future values, as you mention "As a side note: using the information from the future is not a good idea in general ( it will definitely not work in real time trading)"

I want to compare next bar data
self.data.close[-1] > self.l.super_trend[-1] means previous values so how can i access next bar values ?

i am trying like this

if self.data.close[1] > self.l.super_trend[1] and self.data.close[0] < self.l.super_trend[0]:
               self.log('BUY CREATE, %.2f' % self.data.close[0])
               # adds buy to self.order so we can run the check above
               self.order = self.buy()

this code throwing error
Thanks

i am using 4 hours of resampledata

data0 = DataFactory(
        dataname=args.symbol or "MSFT",
        timeframe=bt.TimeFrame.TFrame("Minutes"),
        fromdate=pd.Timestamp('2020-07-27'),
        todate=pd.Timestamp('2020-07-29'),
        compression=1,
        historical=True)
    cerebro.adddata(data0)

    cerebro.resampledata(data0, timeframe=bt.TimeFrame.Minutes, compression=60 * 4)

and i am fetching 4 hours resample data in def init(self):
like this

self.data4h = self.datas[1]  # 240 minute resampled data

its giving me error

File "4hresample.py", line 74, in __init__
    self.data4h = self.datas[1]  # 240 minute resampled data
IndexError: list index out of range

@mudassar031
I have resolved it actually
this must be

if len(self.data) % 240 == 0:

Thanks

@ab_trader
another question i am using 4 hours of resampledata

 data0 = DataFactory(
        dataname=args.symbol or "MSFT",
        timeframe=bt.TimeFrame.TFrame("Minutes"),
        fromdate=pd.Timestamp('2020-07-27'),
        todate=pd.Timestamp('2020-07-29'),
        compression=1,
        historical=True)
    cerebro.adddata(data0)

    cerebro.resampledata(data0, timeframe=bt.TimeFrame.Minutes, compression=60 * 4)

and i am fetching 4 hours resample data in def init(self):
like this

self.data4h = self.datas[1]  # 240 minute resampled data

its giving me error

File "4hresample.py", line 74, in __init__
    self.data4h = self.datas[1]  # 240 minute resampled data
IndexError: list index out of range

@ab_trader
i have minutes of data and i want to fetch 4 hours our data but it always executing one minutes on data i want only to display row after 240th row

     if len(self.data) % 240 != 0:

        self.log(
            'Open: %.2f '
            'High: %.2f '
            'Low: %.2f '
            'Close: %.2f '
            % (
                self.data.open[0],
                self.data.high[0],
                self.data.low[0],
                self.data.close[0]
            ))

@ab_trader
Thanks

@run-out
can you please give me an code example to consider every fourth row in next function?

@mudassar031
if we have minutes of data and use resampling with compression=60 so backtrader give us data after averaging 60 mins actually i want to skip data in between and want to grab specific row as i have explained above example Thanks

I want to grab every 4th row in data without resampling in backtrader as i have done in python here is code

ts = TimeSeries(key='av_api_key', output_format='pandas')
data, meta_data = ts.get_intraday(symbol='MSFT', interval='60min', outputsize='full')
# Convert the index to datetime.
data.index = pd.to_datetime(data.index)
data.columns = ['Open', 'High', 'Low', 'Close', 'Volume']
# Grabs every 4th row
data = data.iloc[::4, :]