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我有在 backtrader 中回测交易策略的文件。我想收集文件中的数据，然后我可以分析它们。现在我打印出我想要的信息，但我想让它自动写下来。有人可以告诉我怎么做吗？我想要存储的信息是：交易数量、盈利/亏损交易数量、回撤、最大回撤和账户发展百分比。我真的不明白如何实现分析器、观察器或编写器来让程序执行此操作。

这是现在的代码：

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

import datetime 
import os.path  
import sys  
import backtrader.feeds as btfeeds
import backtrader as bt
import matplotlib
import argparse


class TestStrategy(bt.Strategy):
    params = (
        ('exitbars', 5),('stop_loss', 0.98),('take_profit',1.04),
    )
    
    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

        self.order = None
        self.buyprice = None
        self.buycomm = None

    def notify_order(self, order):
        if order.status in [order.Submitted, order.Accepted]:
            return

        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')

        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):
        
        if self.order:
            return
        if not self.position:
            
            # Not yet ... we MIGHT BUY if ...
            if self.dataclose[0] < self.dataclose[-1]:

                    if self.dataclose[-1] < self.dataclose[-2]:


                        self.order = self.buy()

        else:
            
            SL_price = ( self.params.stop_loss* self.buyprice)
            TP_price = (self.params.take_profit * self.buyprice)
            if self.dataclose[0] <= SL_price or self.dataclose[0] >= TP_price:
                self.order = self.sell()

if __name__ == '__main__':

    cerebro = bt.Cerebro()
    cerebro.addobserver(bt.observers.DrawDown)
    cerebro.addstrategy(TestStrategy)

    modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
    datapath = os.path.join(modpath, '../../datas/orcl-1995-2014.txt')

    data = bt.feeds.YahooFinanceCSVData(
        dataname='AAPL.csv',
        fromdate=datetime.datetime(2015, 1, 1),
        todate=datetime.datetime(2021, 1, 1),
        reverse=False)

    cerebro.adddata(data)


    cerebro.broker.setcash(100000.0)

    cerebro.addsizer(bt.sizers.FixedSize, stake=1000)

    cerebro.broker.setcommission(commission=0.001)

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

    cerebro.run()
    cerebro.plot()

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