TA-LIB expecting numpy array?

[Vypy1]

Hey, in the docs of Ta-Lib on BT it is mentioned that BT manages the conversion of the input of ndarray in the background but I get an error when I execute the below code which says:

TypeError: Argument 'open' has incorrect type (expected numpy.ndarray, got LineBuffer)

Not sure why I have passed in arguments similar to what are mentioned in code samples on Ta-Lib reference on bt.

# Bracket order

import datetime
import backtrader as bt


class St(bt.Strategy):
    params = dict(
        ma=bt.ind.SMA,
        p1=20,
        p2=50,
        stop = 0.98,
        tgt = 1.05   
    )

    def __init__(self):
        self.dataclose = self.datas[0].close
#         self.dataopen = self.datas[0].open
#         self.datahigh = self.datas[0].high
#         self.datalow = self.datas[0].low
        ma1 = self.p.ma(period=self.p.p1)
        ma2 = self.p.ma(period=self.p.p2)
        self.cross = bt.ind.CrossOver(ma1, ma2)
        self.engulf = ta.CDLENGULFING(self.data.open, self.data.high, self.data.low, self.data.close)

        self.orefs = list()
        print(f'Order Numbers are : {self.orefs}')
        self.execprice = None
        

    def log(self, txt, dt=None):
        dt = self.datas[0].datetime.date()
        print(f'{dt}: {txt}')
    
            
    def notify_order(self, order):
        print(f'{self.data.datetime.date()}: Close: {self.dataclose[0]}, Order ref: {order.ref} / Type {"Buy" * order.isbuy() or "Sell"} / Status {order.getstatusname()}')
        
     
        if order.status == order.Completed:
            self.execprice = order.executed.price
            self.log(f'Executed price: {self.execprice}')


        if not order.alive() and order.ref in self.orefs:
            self.orefs.remove(order.ref)
            print(f'Order Numbers are {self.orefs}')
            

    def next(self):
        self.log(f'Close: {self.dataclose[0]}')
        
        if self.orefs:
            return  # pending orders do nothing

        if not self.position:
            
            if (self.ma1[0] > self.ma2[0]) and (self.engulf[0] == 100):  # crossing up

                p1 = self.data.open[1]
                p2 = self.p.stop * self.data.open[1] # Stop and Tgt prices should be set from the executed price 
                p3 = self.p.tgt * self.data.open[1] # not the submitted price     

            
                os = self.buy_bracket(price=p1, stopprice=p2, limitprice=p3, exectype = bt.Order.Market)
                self.log(f'Buy at {p1}, Stop sell at {p2}, Tgt sell at {p3}')
                

                self.orefs = [o.ref for o in os]
                print(f'Order Numbers are : {self.orefs}')     



cerebro = bt.Cerebro()
cerebro.broker.set_cash(100000)
print(f'Cash Available: {cerebro.broker.get_cash()}')

data = bt.feeds.PandasData(dataname=hdfc, datetime=None, open=-1, high=-1, low=-1, close=-1, volume=-1)
cerebro.adddata(data)
cerebro.addsizer(bt.sizers.FixedSize, stake = 50)
cerebro.addstrategy(St)
cerebro.run()

print(f'Final Value: {cerebro.broker.get_cash()}')

[Vypy1]

@vypy1 Was able to fix this.

For anyones future reference.

# Bracket order

import datetime
import backtrader as bt


class St(bt.Strategy):
    params = dict(
        ma=bt.ind.SMA,
        p1=20,
        p2=50,
        stop = 0.98,
        tgt = 1.05   
    )

    def __init__(self):
        self.dataclose = self.datas[0].close
#         self.dataopen = self.datas[0].open
#         self.datahigh = self.datas[0].high
#         self.datalow = self.datas[0].low
        self.ma1 = bt.indicators.SMA(period=self.p.p1)
        self.ma2 = bt.indicators.SMA(period=self.p.p2)
        self.cross = bt.ind.CrossOver(self.ma1, self.ma2)
        self.engulf = bt.talib.CDLENGULFING(self.data.open, self.data.high, self.data.low, self.data.close)

        self.orefs = list()
        print(f'Order Numbers are : {self.orefs}')
        self.execprice = None
        

    def log(self, txt, dt=None):
        dt = self.datas[0].datetime.date()
        print(f'{dt}: {txt}')
    
            
    def notify_order(self, order):
        print(f'{self.data.datetime.date()}: Close: {self.dataclose[0]}, Order ref: {order.ref} / Type {"Buy" * order.isbuy() or "Sell"} / Status {order.getstatusname()}')
        
     
        if order.status == order.Completed:
            self.execprice = order.executed.price
            self.log(f'Executed price: {self.execprice}')


        if not order.alive() and order.ref in self.orefs:
            self.orefs.remove(order.ref)
            print(f'Order Numbers are {self.orefs}')
            

    def next(self):
        self.log(f'Close: {self.dataclose[0]}')
        
        if self.orefs:
            return  # pending orders do nothing

        if not self.position:
            
            if (self.ma1[0] > self.ma2[0]) and (self.engulf[0] == 100):  # crossing up

                p1 = self.data.open[1]
                p2 = self.p.stop * self.data.open[1] # Stop and Tgt prices should be set from the executed price 
                p3 = self.p.tgt * self.data.open[1] # not the submitted price     

            
                os = self.buy_bracket(price=p1, stopprice=p2, limitprice=p3, exectype = bt.Order.Market)
                self.log(f'Buy at {p1}, Stop sell at {p2}, Tgt sell at {p3}')
                

                self.orefs = [o.ref for o in os]
                print(f'Order Numbers are : {self.orefs}')     



cerebro = bt.Cerebro()
cerebro.broker.set_cash(100000)
print(f'Cash Available: {cerebro.broker.get_cash()}')

data = bt.feeds.PandasData(dataname=hdfc, datetime=None, open=-1, high=-1, low=-1, close=-1, volume=-1)
cerebro.adddata(data)
cerebro.addsizer(bt.sizers.FixedSize, stake = 50)
cerebro.addstrategy(St)
cerebro.run()

print(f'Final Value: {cerebro.broker.get_cash()}')