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TypeError: __init__() takes 1 positional argument but 2 were given



  • hi everyone I have created a code composed of two indicators but when i run it this error comes up:
    TypeError: init() takes 1 positional argument but 2 were given
    can anyone help me with this error?
    here is the code:

          from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
    
          import datetime  # For datetime objects
          import os.path  # To manage paths
          import sys  # To find out the script name (in argv[0])
    
          # Import the backtrader platform
          import backtrader as bt
    
    
          # Create a Stratey
          class TestStrategy(bt.Strategy):
    params = (
        ('emaperiod', 30),
        ('me1_period', 12),
        ('me2_period', 26),
        ('signal_period', 9),
    )
    
    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.date(0)
        print('%s, %s' % (dt.isoformat(), txt))
    
    def __init__(self):
        # Keep a reference to the "close" line in the data[0] dataseries
        self.dataclose = self.datas[0].close
    
        # To keep track of pending orders and buy price/commission
        self.order = None
        self.buyprice = None
        self.buycomm = None
    
        # Add a MovingAverageSimple indicator
        self.ema = bt.indicators.EMA(self.datas[0], period=self.params.emaperiod)
        self.macd = bt.indicators.EMA(self.datas[0], self.params.me1_period) - bt.indicators.EMA(self.datas[0], self.params.me2_period)
        self.signal = bt.indicators.EMA(self.macd, self.params.signal_period)
        # Indicators for the plotting show
        bt.indicators.ExponentialMovingAverage(self.datas[0], period=25)
        bt.indicators.WeightedMovingAverage(self.datas[0], period=25,
                                            subplot=True)
        bt.indicators.StochasticSlow(self.datas[0])
        bt.indicators.MACDHisto(self.datas[0])
        rsi = bt.indicators.RSI(self.datas[0])
        bt.indicators.SmoothedMovingAverage(rsi, period=10)
        bt.indicators.ATR(self.datas[0], plot=False)
    
    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            # Buy/Sell order submitted/accepted to/by broker - Nothing to do
            return
    
        # Check if an order has been completed
        # Attention: broker could reject order if not enough cash
        if order.status in [order.Completed]:
            if order.isbuy():
                self.log(
                    'BUY EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                    (order.executed.price,
                     order.executed.value,
                     order.executed.comm))
    
                self.buyprice = order.executed.price
                self.buycomm = order.executed.comm
            else:  # Sell
                self.log('SELL EXECUTED, Price: %.2f, Cost: %.2f, Comm %.2f' %
                         (order.executed.price,
                          order.executed.value,
                          order.executed.comm))
    
            self.bar_executed = len(self)
    
        elif order.status in [order.Canceled, order.Margin, order.Rejected]:
            self.log('Order Canceled/Margin/Rejected')
    
        # Write down: no pending order
        self.order = None
    
    def notify_trade(self, trade):
        if not trade.isclosed:
            return
    
        self.log('OPERATION PROFIT, GROSS %.2f, NET %.2f' %
                 (trade.pnl, trade.pnlcomm))
    
    def next(self):
        # Simply log the closing price of the series from the reference
        self.log('Close, %.2f' % self.dataclose[0])
    
        # Check if an order is pending ... if yes, we cannot send a 2nd one
        if self.order:
            return
    
        # Check if we are in the market
        if not self.position:
    
            # Not yet ... we MIGHT BUY if ...
            if self.dataclose[0] > self.ema[0]:
                if self.macd > 0:
                    if self.macd > self.signal:
    
                        # BUY, BUY, BUY!!! (with all possible default parameters)
                        self.log('BUY CREATE, %.2f' % self.dataclose[0])
    
                        # Keep track of the created order to avoid a 2nd order
                        self.order = self.buy()
    
        else:
    
            if self.dataclose[0] < self.ema[0]:
                if self.macd < 0:
                    if self.macd < self.signal:
                    
                        # SELL, SELL, SELL!!! (with all possible default parameters)
                        self.log('SELL CREATE, %.2f' % self.dataclose[0])
    
                        # Keep track of the created order to avoid a 2nd order
                        self.order = self.sell()
    
    
    if __name__ == '__main__':
    # Create a cerebro entity
    cerebro = bt.Cerebro()
    
     # Add a strategy
    cerebro.addstrategy(TestStrategy)
    
    # Datas are in a subfolder of the samples. Need to find where the script is
    # because it could have been called from anywhere
    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'C:\\Users\\Queen\\Desktop\\boursedata\\Book2.csv')
    
    # Create a Data Feed
    data = bt.feeds.YahooFinanceCSVData(
        dataname=datapath,
        # Do not pass values before this date
        fromdate=datetime.datetime(2008, 3, 24),
        # Do not pass values before this date
        todate=datetime.datetime(2018, 3, 18),
        # Do not pass values after this date
        reverse=False)
    
    # Add the Data Feed to Cerebro
    cerebro.adddata(data)
    
    # Set our desired cash start
    cerebro.broker.setcash(100000000.0)
    
    # Add a FixedSize sizer according to the stake
    cerebro.addsizer(bt.sizers.FixedSize, stake=100)
    
    # Set the commission
    cerebro.broker.setcommission(commission=0.007575)
    
    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
    
    # Run over everything
    cerebro.run()
    
    # Print out the final result
    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    
    # Plot the result
    cerebro.plot()


  • @feiz said in TypeError: __init__() takes 1 positional argument but 2 were given:

    self.ema = bt.indicators.EMA(self.datas[0], period=self.params.emaperiod)
    self.macd = bt.indicators.EMA(self.datas[0], self.params.me1_period) - bt.indicators.EMA(self.datas[0], self.params.me2_period)
    self.signal = bt.indicators.EMA(self.macd, self.params.signal_period)

    change this to

    self.ema = bt.indicators.EMA(self.datas[0], period=self.params.emaperiod)
    self.macd = bt.indicators.EMA(self.datas[0], period=self.params.me1_period) - bt.indicators.EMA(self.datas[0], period=self.params.me2_period)
    self.signal = bt.indicators.EMA(self.macd, period=self.params.signal_period)
    

    the period value is missing in macd and signal



  • @dasch
    Thank you for your reply.
    it worked


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