main.py

# pip install backtrader pandas
# https://finance.yahoo.com/quote/GAZP.ME/history?p=GAZP.ME

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import backtrader as bt
import pandas as pd
import datetime  # For datetime objects
import os.path  # To manage paths
import sys  # To find out the script name (in argv[0])


# Create a Stratey
class TestStrategy(bt.Strategy):

    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
        self.order = None

    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, %.2f' % order.executed.price)
            elif order.issell():
                self.log('SELL EXECUTED, %.2f' % order.executed.price)

            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])
        # print("*", self.datas[0].close[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.dataclose[-1]:
                    # current close less than previous close

                    if self.dataclose[-1] < self.dataclose[-2]:
                        # previous close less than the previous close

                        # BUY, BUY, BUY!!! (with 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:

            # Already in the market ... we might sell
            if len(self) >= (self.bar_executed + 50):
                # 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__':

    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, 'GAZP_D1.csv')

    # print(datapath)
    # exit(1)

    data = pd.read_csv(datapath, sep=',', index_col='Date')    # this data is from metatrader 5
    print(data)
    data = data.reset_index()
    data.rename(columns={'Date': 'datetime', 'Open': 'open', 'High': 'high',
                           'Low': 'low', 'Close': 'close', 'Volume': 'volume'},
                  inplace=True)  # Чтобы получить дату/время переименовываем колонки
    data.index = pd.to_datetime(data['datetime'])
    print(data)

    cerebro = bt.Cerebro()

    # Add a strategy
    cerebro.addstrategy(TestStrategy)

    cerebro.broker.setcash(100000.0)

    # Set the commission - 0.1% ... divide by 100 to remove the %
    cerebro.broker.setcommission(commission=0.001)

    # modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    # datapath = os.path.join(modpath, 'GAZP.ME (1).csv')
    # Create a Data Feed
    # data = bt.feeds.YahooFinanceCSVData(
    #     dataname=datapath, # yahoo data downloaded from site
    #     # Do not pass values before this date
    #     fromdate=datetime.datetime(2022, 1, 1),
    #     # Do not pass values after this date
    #     todate=datetime.datetime(2022, 4, 1),
    #     reverse=False)

    # Pass it to the backtrader datafeed and add it to the cerebro
    data = bt.feeds.PandasData(dataname=data)

    # Add the Data Feed to Cerebro
    cerebro.adddata(data)

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

    cerebro.run()

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