Help with starting up

[Shubham]

Hello,
I am a newbee to backtrader and I am trying to backtest my strategy but whenever I start my code it gets stuck and I don't get any output.
Can someone please help me to find the issue with my strategy.
Thanks in advance

class ABC(bt.Strategy):
    alias = ('ABC',)

    # list of parameters which are configurable for the strategy
    params = dict(
        sma50=10,  # period for the fast moving average
        pslow=30  # period for the slow moving average
    )

    def log(self, txt, dt=None):
        ''' Logging function for this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))

    def __init__(self):
        self.log(f'Initial portfolio value of {self.broker.get_value():.2f}\n')
        self.sma20 = bt.ind.SMA(period=20)  # fast moving average
        self.sma50 = bt.ind.SMA(period=50)  # slow moving average
        # self.stddev = self.data.close.rolling(window=20).std()
        self.stddev = bt.ind.StdDev(self.close,period=20)
        self.lower_band = self.sma20 - (2 * self.stddev)
        self.upper_band = self.sma20 + (2 * self.stddev)
        offset = 0.005 * self.data.close
        a = abs(self.sma50 - self.lower_band)
        b = abs(self.data.Low - self.lower_band)
        c = abs(self.data.close - self.lower_band)
        self.buy_sig = bt.And(a < offset, bt.Or(b < offset,c < offset))

    def next(self):
        tar = 0
        SL = 0
        print("Scanning")
        if not self.position:  # not in the market
            if self.buy_sig > 0:
                self.log(f'BUY {self.getsizing()} shares of {self.data._name} at {self.data.close[0]}')
                print('Entered Trade')
                if self.data.close[0] > self.data.close[-1]:  # if fast crosses slow to the upside
                    if self.sma50[0] > self.sma2[-3]:
                        if self.sma50[-3] > self.sma2[-6]:
                            if self.sma50[-6] < self.sma2[-9]:
                                self.buy()  # enter long
                                tar = self.data.close[0] + 10
                                SL = self.data.close[0] + 10

        elif self.data.close[0]>tar:
            self.sell()  # exit long
            self.log(f'CLOSE LONG position of {self.position.size} shares '
                     f'of {self.data._name} at {self.data.close[0]:.2f}')
        # elif self.data.close[0]<SL:

        elif self.data.close[0] <SL:
            self.sell()  # exit long
            self.log(f'CLOSE LONG position of {self.position.size} shares '
                         f'of {self.data._name} at {self.data.close[0]:.2f}')
            print('Do nothing')




def startBackTestEngine(strategyName):
    # Declare position of each column in csv file

    btdata = GenericCSVData(dataname='backtestEngine_ABC.csv',
                            dtformat=('%Y-%m-%d'),
                            datetime=0,
                            high=5,
                            low=6,
                            open=4,
                            close=8,
                            volume=10,
                            openinterest=-1,
                            # fromdate=date(2021, 2, 16),
                            # todate=date(2021, 2, 16)
                            )

    # Create Buy and Sell Signal Observers

    # Create cerebro Engine
    cerebro = bt.Cerebro()

    # Set Fixed Position Sizing
    cerebro.addsizer(bt.sizers.SizerFix, stake=20)

    # Add datafeed to Cerebro Engine
    cerebro.adddata(btdata)

    # Set Initial Trading Capital and Trading Commissions
    cerebro.broker.setcash(300000.0)
    cerebro.broker.setcommission(commission=0.002)

    # Add Trading Strategy to Cerebro
    cerebro.addstrategy(strategyName)

    # Add Buy Sell Signals Observer to Cerebro
    cerebro.addobserver(bt.observers.Value)

    # Add Trading Statistics Analyzer
    cerebro.addanalyzer(bt.analyzers.PyFolio, _name='pyfolio')

    bt.observers.BuySell = BuySellSignal

    # Run Cerebro Engine

    start_portfolio_value = cerebro.broker.getvalue()

    cerebro.run()

    end_portfolio_value = cerebro.broker.getvalue()
    pnl = end_portfolio_value - start_portfolio_value
    print(f'Starting Portfolio Value: {start_portfolio_value:.2f}')
    print(f'Final Portfolio Value: {end_portfolio_value:.2f}')
    print(f'PnL: {pnl:.2f}')

    # Plot the Line Chart with Buy or Sell Signals
    cerebro.plot()