Backtrader Community

X-Mars

@run-out Thank you for your reply.
My PC have 64G memory, and AMD 5950X .
Something wrong with my code.
It's OK now.

X-Mars

Dear all,

I got 'Out of memory ' when run backtrader by two datas.
Someone can help me?
Thk for your job.

These is codes.

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 pandas as pd
from typing import Union

# Import the backtrader platform
import backtrader as bt
import logging, itertools
from charts.bar import MakeBarOptinons
from charts.line import MakeLineOptinons



class BarAnalysis(bt.analyzers.Analyzer):

    def start(self):
        self.rets = {
            'strategy': [],
            'profit': [],
            'profit_percentage': []
        }

    def stop(self):
        self.rets['strategy'].append(str(self.strategy.params.hours) + '--' + str(self.strategy.params.percentage) + '--' + str(self.strategy.params.portfolio))
        self.rets['profit'].append(self.strategy.broker.getvalue() - 100000)
        self.rets['profit_percentage'].append((self.strategy.broker.getvalue() - 100000) / 100000)

    def get_analysis(self):
        return self.rets


class TestStrategy(bt.Strategy):
    """
        percentage 数字货币资产 占 总资产的比例
        portfolio [1] 数字货币1（BTC） 占 数字货币资产
        portfolio [2] 数字货币2（ETH） 占 数字货币资产
    """
    params = {
        'hours': 1,
        'percentage': 1,
        'portfolio': (1, 1),
        'name': 'test'
    }

    def log(self, txt, dt=None):
        ''' Logging function fot this strategy'''
        dt = dt or self.datas[0].datetime.datetime()
        print('%s, %s' % (dt.strftime('%Y-%m-%d %H:%M:%S'), txt))

    def log_write(self, txt, dt=None):
        logging.basicConfig(filename=self.params.name + '.csv',
                            filemode='a',
                            level=logging.INFO,
                            format='%(asctime)s , %(message)s',
                            datefmt='%Y-%m-%d %H:%M:%S')
        # logger = logging.getLogger('urbanGUI')

        dt = dt or self.datas[0].datetime.datetime()
        logging.info('%s, %s' % (dt.strftime('%Y-%m-%d %H:%M:%S'), txt))

    def next(self):
        if hasattr(self, 'order_datetime'):

            """
                用于买币的资金：总资产的 10%
            """
            cash_for_coin = self.broker.getvalue() * (self.params.percentage / 100)

            current_datetime = self.data0.datetime.datetime()
            time_ago = (current_datetime - self.order_datetime).seconds
            # print(cash_for_coin)

            if time_ago >= (self.params.hours * 60 * 60):
                price0 = self.data0.close[0]
                position_value0 = self.getposition(self.data0).size * price0

                """
                    购币/售币 数量 = (持仓价值 - (用于买币的资金 * 当前币种所占比例)) / 当前收盘价
                """
                size0 = (position_value0 - (cash_for_coin * (self.params.portfolio[0] / 100))) / price0
                # print(price0)
                # print(position_value0)
                # print(size0)
                if float(size0) > float(0):
                    self.sell(data=self.data0, size=size0, price=price0)
                    # self.log_write('SELL , %.2f , %.2f , %s , %.10f , %.10f' % (
                    #     self.params.hours, self.params.percentage, str(self.params.portfolio), price0, size0))
                    self.log('SELL , %.2f , %.2f , %s , %.10f , %.10f' % (
                    self.params.hours, self.params.percentage, str(self.params.portfolio), price0, size0))

                elif float(size0) < float(0):
                    self.buy(data=self.data0, size=size0, price=price0)
                    # self.log_write('BUY , %.2f , %.2f , %s , %.10f , %.10f' % (
                    #     self.params.hours, self.params.percentage, str(self.params.portfolio), price0, size0))
                    self.log('BUY , %.2f , %.2f , %s , %.10f , %.10f' % (
                    self.params.hours, self.params.percentage, str(self.params.portfolio), price0, size0))

                price1 = self.data1.close[0]
                position_value1 = self.getposition(self.data1).size * price1

                """
                    购币/售币 数量 = (持仓价值 - (用于买币的资金 * 当前币种所占比例)) / 当前收盘价
                """
                size1 = (position_value1 - (cash_for_coin * (self.params.portfolio[1] / 100))) / price1
                # print(price1)
                # print(position_value1)
                # print(size1)
                if float(size1) > float(0):
                    self.sell(data=self.data1, size=size1, price=price1)
                    # self.log_write('SELL , %.2f , %.2f , %s , %.10f , %.10f' % (
                    #     self.params.hours, self.params.percentage, str(self.params.portfolio), price1, size1))
                    self.log('SELL , %.2f , %.2f , %s , %.10f , %.10f' % (
                    self.params.hours, self.params.percentage, str(self.params.portfolio), price1, size1))

                elif float(size1) < float(0):
                    self.buy(data=self.data1, size=size1, price=price1)
                    # self.log_write('BUY , %.2f , %.2f , %s , %.10f , %.10f' % (
                    #     self.params.hours, self.params.percentage, str(self.params.portfolio), price1, size1))
                    self.log('BUY , %.2f , %.2f , %s , %.10f , %.10f' % (
                    self.params.hours, self.params.percentage, str(self.params.portfolio), price1, size1))

        else:

            """
                用于买币的资金：总现金的 10%
            """
            cash_for_coin = self.params.percentage / 100 * self.broker.cash

            current_datetime = self.data0.datetime.datetime()

            """
                用于购买当前币种的资金 
            """
            cash_for_coin_this0 = self.params.portfolio[0] / 100 * cash_for_coin
            price0 = self.data0.close[0]
            size0 = cash_for_coin_this0 / price0
            self.buy(data=self.data0, size=size0, price=price0)
            self.log('BUY , %.2f , %.2f , %s , %.10f , %.10f' % (self.params.hours, self.params.percentage, str(self.params.portfolio), price0, size0))

            cash_for_coin_this1 = self.params.portfolio[1] / 100 * cash_for_coin
            price1 = self.data1.close[0]
            size1 = cash_for_coin_this1 / price1
            self.buy(data=self.data1, size=size1, price=price1)
            self.log('BUY , %.2f , %.2f , %s , %.10f , %.10f' % (self.params.hours, self.params.percentage, str(self.params.portfolio), price1, size1))

            self.order_datetime = current_datetime

        # print('========================================================================================================================')

    def stop(self):
        position_value_data0 = self.data0.close[0] * self.getposition(self.data0).size
        position_value_data1 = self.data1.close[0] * self.getposition(self.data1).size
        profit = self.broker.getvalue() - 100000
        profit_percentage = round(profit / 100000 * 100, 4)
        self.log_write('Profit , %.2f , %.2f , %s , %.10f , %.10f , %.10f , %.10f , %.10f , %.4f' % (self.params.hours, self.params.percentage, str(self.params.portfolio), self.broker.cash, position_value_data0, position_value_data1, self.broker.getvalue(), profit, profit_percentage))

if __name__ == '__main__':

    action = int(sys.argv[1]) if len(sys.argv) > 1 else 0
    portfolio_tuple = itertools.product(range(1, 101), range(1, 101))
    portfolio_list = [list(portfolio) for portfolio in portfolio_tuple if portfolio[0] + portfolio[1] == 100]
    print(portfolio_list)

    if action == 0:
        print('请选择执行类型：')
        print("""
    
               action == 1:
                   name = 'bearToBull'
                   from_date = datetime.datetime(2019, 1, 1)
                   to_date = datetime.datetime(2019, 6, 30)
               action == 2:
                   name = 'bearTobullToBear'
                   from_date = datetime.datetime(2020, 10, 1)
                   to_date = datetime.datetime(2021, 6, 30)
               action == 3:
                   name = 'bullToBear'
                   from_date = datetime.datetime(2017, 12, 1)
                   to_date = datetime.datetime(2018, 12, 31)
               action == 4:
                   name = 'bullToBearToShockToBullToBear'
                   from_date = datetime.datetime(2017, 10, 1)
                   to_date = datetime.datetime(2020, 3, 31)
               action == 5:
                   name = 'shock'
                   from_date = datetime.datetime(2019, 7, 1)
                   to_date = datetime.datetime(2020, 9, 30)
               action == 6:
                   name = 'all'
                   from_date = datetime.datetime(2017, 12, 1)
                   to_date = datetime.datetime(2021, 6, 30)
           """)
        sys.exit()
    elif action == 1:
        name = 'bearToBull-two-coin'
        from_date = datetime.datetime(2019, 1, 1)
        to_date = datetime.datetime(2019, 6, 30)
    elif action == 2:
        name = 'bearTobullToBear-two-coin'
        from_date = datetime.datetime(2020, 10, 1)
        to_date = datetime.datetime(2021, 6, 30)
    elif action == 3:
        name = 'bullToBear-two-coin'
        from_date = datetime.datetime(2017, 12, 1)
        to_date = datetime.datetime(2018, 12, 31)
    elif action == 4:
        name = 'bullToBearToShockToBullToBear-two-coin'
        from_date = datetime.datetime(2017, 10, 1)
        to_date = datetime.datetime(2020, 3, 31)
    elif action == 5:
        name = 'shock-two-coin'
        from_date = datetime.datetime(2019, 7, 1)
        to_date = datetime.datetime(2020, 9, 30)
    elif action == 6:
        name = 'all-two-coin'
        from_date = datetime.datetime(2017, 12, 1)
        to_date = datetime.datetime(2021, 6, 30)
    else:
        sys.exit()

    print(name)
    print(from_date)
    print(to_date)

    cerebro = bt.Cerebro()

    cerebro.optstrategy(TestStrategy, hours=range(1, 11), portfolio=portfolio_list, percentage=range(5, 101, 10), name=name)

    df0 = pd.read_csv('/app/data/Binance_BTCUSDT_minute.csv', parse_dates=['time'])
    # df0 = pd.read_csv('/Users/mars/Downloads/Binance_BTCUSDT_minute.csv', parse_dates=['time'])
    data0 = bt.feeds.PandasData(dataname=df0,
                                timeframe=bt.TimeFrame.Minutes,
                                datetime='time',
                                open='open',
                                high='high',
                                low='low',
                                close='close',
                                volume='volume',
                                openinterest=-1,
                                fromdate=from_date,
                                todate=to_date)

    df1 = pd.read_csv('/app/data/Binance_ETHUSDT_minute.csv', parse_dates=['time'])
    # df1 = pd.read_csv('/Users/mars/Downloads/Binance_ETHUSDT_minute.csv', parse_dates=['time'])
    data1 = bt.feeds.PandasData(dataname=df1,
                                timeframe=bt.TimeFrame.Minutes,
                                datetime='time',
                                open='open',
                                high='high',
                                low='low',
                                close='close',
                                volume='volume',
                                openinterest=-1,
                                fromdate=from_date,
                                todate=to_date)

    # Add the Data Feed to Cerebro
    cerebro.adddata(data0)
    cerebro.adddata(data1)

    cerebro.addanalyzer(BarAnalysis, _name="data_all")
    # Set our desired cash start
    cerebro.broker.setcash(100000.0)
    cerebro.broker.setcommission(commission=0.001)

    # Print out the starting conditions
    print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())

    # Run over everything
    stratruns = cerebro.run()

    print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())
    data_end = {
        'strategy': [],
        'profit': [],
        'profit_percentage': []
    }
    for stratrun in stratruns:
        for strat in stratrun:
            data_end['strategy'].extend(strat.analyzers.data_all.rets['strategy'])
            data_end['profit'].extend(strat.analyzers.data_all.rets['profit'])
            data_end['profit_percentage'].extend(strat.analyzers.data_all.rets['profit_percentage'])
    print(data_end)
    print(name + '  最大收益为：')
    profit_max = max(data_end['profit'])
    print(profit_max)
    print(name + '  最大收益模式为：')
    indices = [data_end['strategy'][i] for i, x in enumerate(data_end['profit']) if x == profit_max]
    print(indices)
    M = MakeLineOptinons(data=data_end, file_name=name + '.html')
    M.make_options()

These is error log.

[Fri Jul 16 14:52:18 2021] oom-kill:constraint=CONSTRAINT_NONE,nodemask=(null),cpuset=/,mems_allowed=0,global_oom,task_memcg=/user.slice/user-1000.slice/session-1.scope,task=python,pid=3834,uid=1000
[Fri Jul 16 14:52:18 2021] Out of memory: Killed process 3834 (python) total-vm:5423880kB, anon-rss:3722984kB, file-rss:176kB, shmem-rss:0kB, UID:1000 pgtables:8360kB oom_score_adj:0
[Fri Jul 16 14:52:18 2021] oom_reaper: reaped process 3834 (python), now anon-rss:0kB, file-rss:0kB, shmem-rss:0kB

Have nice day.

Posts made by X-Mars