@run-out thank you very much

Hi All
I have a question regarding Stop Loss Trading article
https://www.backtrader.com/blog/posts/2018-02-01-stop-trading/stop-trading/
why do we need to have a parent child order to do stop loss?

    def next(self):
        if not self.position and self.crossup > 0:
            if self.buy_order:  # something was pending
                self.cancel(self.buy_order)

            # not in the market and signal triggered
            if not self.p.buy_limit:
                self.buy_order = self.buy(transmit=False)
            else:
                price = self.data.close[0] * (1.0 - self.p.buy_limit)

                # transmit = False ... await child order before transmission
                self.buy_order = self.buy(price=price, exectype=bt.Order.Limit,
                                          transmit=False)

            # Setting parent=buy_order ... sends both together
            if not self.p.trail:
                stop_price = self.data.close[0] * (1.0 - self.p.stop_loss)
                self.sell(exectype=bt.Order.Stop, price=stop_price,
                          parent=self.buy_order)
            else:
                self.sell(exectype=bt.Order.StopTrail,
                          trailamount=self.p.trail,
                          parent=self.buy_order)

I thought we could we can use something like below to do both buy and stop loss together

self.buy(size=1, exectype=bt.Order.StopTrail, trailamount=0.25)

@petehe said in question about sample code mixing-timeframes:

it can't work out

should be I can't work out

I was reading the sample code below, it can't work out

1. if pp is PivotPoint object, what is pp1 if pp1=pp(), what is pp1.s1 and pp.s1()?
2. In cerebro.addstrategy(St, multi=args.multi) what is parameter multi?

class St(bt.Strategy):
    params = (('multi',True),)

    def __init__(self):
        self.pp = pp = btind.PivotPoint(self.data1)
        pp.plotinfo.plot = False  # deactivate plotting

        if self.p.multi:
            pp1 = pp()  # couple the entire indicators
            self.sellsignal = self.data0.close < pp1.s1
        else:
            self.sellsignal = self.data0.close < pp.s1()

    def next(self):
        txt = ','.join(
            ['%04d' % len(self),
             '%04d' % len(self.data0),
             '%04d' % len(self.data1),
             self.data.datetime.date(0).isoformat(),
             '%.2f' % self.data0.close[0],
             '%.2f' % self.pp.s1[0],
             '%.2f' % self.sellsignal[0]])

        print(txt)


def runstrat():
    args = parse_args()

    cerebro = bt.Cerebro()
    data = btfeeds.BacktraderCSVData(dataname=args.data)
    cerebro.adddata(data)
    cerebro.resampledata(data, timeframe=bt.TimeFrame.Months)

    cerebro.addstrategy(St, multi=args.multi)

    cerebro.run(stdstats=False, runonce=False)
    if args.plot:
        cerebro.plot(style='bar')


def parse_args():
    parser = argparse.ArgumentParser(
        formatter_class=argparse.ArgumentDefaultsHelpFormatter,
        description='Sample for pivot point and cross plotting')

    parser.add_argument('--data', required=False,
                        default='../../datas/2005-2006-day-001.txt',
                        help='Data to be read in')

    parser.add_argument('--multi', required=False, action='store_true',
                        help='Couple all lines of the indicator')

    parser.add_argument('--plot', required=False, action='store_true',
                        help=('Plot the result'))

    return parser.parse_args()


if __name__ == '__main__':
    runstrat()

@run-out thank you very much

Hi All

I am new to backtrader. I used to build strategy with pandas and it was easy to check the data that you are back testing and verify the strategy is working correctly.

I am not sure what's the best way to inspect OHLC data in the data feeds, it is bit confusing for me.

Can someone shed some light on it?

format it a bit better

if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()

    datapath = 'datas\\orcl-1995-2014.txt'
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # # Do not pass values before this date
        fromdate=datetime.datetime(2000, 1, 1),
        # # Do not pass values before this date
        todate=datetime.datetime(2010, 12, 31),
        # # Do not pass values after this date
        reverse=False
    )

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)
    cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')
    thestrats = cerebro.run()
    pyfstats = thestrats[0].analyzers.getbyname('pyfolio')
    returns, positions, transactions, gross_lev = pyfstats.get_pf_items()

    import pyfolio as pf

    pf.create_full_tear_sheet(
        returns,
        positions=positions,
        transactions=transactions,
        gross_lev=gross_lev,
        live_start_date='2000-01-01',  # This date is sample specific
        round_trips=True
    )

I was doing a very simple test on pyfolio, but it gives me an error below,

Does anyone know how this can be fixed?

TypeError: create_full_tear_sheet() got an unexpected keyword argument 'gross_lev'

code block

if name == 'main':
# Create a cerebro entity
cerebro = bt.Cerebro()
datapath = 'datas\orcl-1995-2014.txt'
data = bt.feeds.YahooFinanceCSVData(
dataname=datapath,
# # Do not pass values before this date
fromdate=datetime.datetime(2000, 1, 1),
# # Do not pass values before this date
todate=datetime.datetime(2010, 12, 31),
# # Do not pass values after this date
reverse=False
)
# Add the Data Feed to Cerebro
cerebro.adddata(data)
cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')
thestrats = cerebro.run()
pyfstats = thestrats[0].analyzers.getbyname('pyfolio')
returns, positions, transactions, gross_lev = pyfstats.get_pf_items()
import pyfolio as pf
pf.create_full_tear_sheet(
returns,
positions=positions,
transactions=transactions,
gross_lev=gross_lev,
live_start_date='2000-01-01', # This date is sample specific
round_trips=True
)
····# code block