Backtrader 量化回测实践（7）——在jupyter中执行bt的samples
Backtrader 量化回测实践（7）——在jupyter中执行bt的samples
Backtrader提供了大量的测试用例，在samples目录下，测试程序主要都是用argparse解析参数，但是不能在jupyter中直接执行。
找到一个解决方法，可以方便在jupyter中执行samples中的示例。
把datas目录上传到ipython的当前路径，以calmar-test.py程序为例，简单修改程序如下：
#!/usr/bin/env python
# -*- coding: utf-8; py-indent-offset:4 -*-
###############################################################################
#
# Copyright (C) 2015-2023 Daniel Rodriguez
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
###############################################################################
from __future__ import (absolute_import, division, print_function,unicode_literals)import argparse
import datetimeimport backtrader as bt%matplotlib inlineclass St(bt.SignalStrategy):params = ()def __init__(self):ma1, ma2, = bt.ind.SMA(period=15), bt.ind.SMA(period=50)self.signal_add(bt.signal.SIGNAL_LONG, bt.ind.CrossOver(ma1, ma2))def next2(self):passdef runstrat(args=None):args = parse_args(args)cerebro = bt.Cerebro()# Data feed kwargskwargs = dict()# Parse from/to-datedtfmt, tmfmt = '%Y-%m-%d', 'T%H:%M:%S'for a, d in ((getattr(args, x), x) for x in ['fromdate', 'todate']):if a:strpfmt = dtfmt + tmfmt * ('T' in a)kwargs[d] = datetime.datetime.strptime(a, strpfmt)# Data feeddata0 = bt.feeds.YahooFinanceCSVData(dataname=args.data0, **kwargs)cerebro.adddata(data0)# Brokercerebro.broker = bt.brokers.BackBroker(**eval('dict(' + args.broker + ')'))cerebro.addanalyzer(bt.analyzers.Calmar)# Sizercerebro.addsizer(bt.sizers.FixedSize, **eval('dict(' + args.sizer + ')'))# Strategycerebro.addstrategy(St, **eval('dict(' + args.strat + ')'))# Executest0 = cerebro.run(**eval('dict(' + args.cerebro + ')'))[0]i = 1for k, v in st0.analyzers.calmar.get_analysis().items():print(i, ': '.join((str(k), str(v))))i += 1if args.plot: # Plot if requested to#cerebro.plot(**eval('dict(' + args.plot + ')'))cerebro.plot(iplot=False)def parse_args(pargs=None):parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter,description=('Sample Skeleton'))parser.add_argument('--data0', default='./datas/orcl-1995-2014.txt',required=False, help='Data to read in')# Defaults for datesparser.add_argument('--fromdate', required=False, default='',help='Date[time] in YYYY-MM-DD[THH:MM:SS] format')parser.add_argument('--todate', required=False, default='',help='Date[time] in YYYY-MM-DD[THH:MM:SS] format')parser.add_argument('--cerebro', required=False, default='',metavar='kwargs', help='kwargs in key=value format')parser.add_argument('--broker', required=False, default='',metavar='kwargs', help='kwargs in key=value format')parser.add_argument('--sizer', required=False, default='',metavar='kwargs', help='kwargs in key=value format')parser.add_argument('--strat', required=False, default='',metavar='kwargs', help='kwargs in key=value format')parser.add_argument('--plot', required=False, default='',nargs='?', const='{}',metavar='kwargs', help='kwargs in key=value format')return parser.parse_args(pargs)if __name__ == '__main__':#runstrat()#runstrat('--plot'.split())runstrat('--plot --fromdate=1998-01-01 --todate=2000-01-01'.split())修改点如下：
-
- jupyter环境：在import 后增加 %matplotlib inline
-
- 调整数据导入路径，因为在当前路径
parser.add_argument('--data0', default='./datas/orcl-1995-2014.txt',required=False, help='Data to read in')- 3.绘图参数：
在jupyter中绘图参数
#cerebro.plot(**eval('dict(' + args.plot + ')'))
cerebro.plot(iplot=False)`
- 4.调用参数
通过split方法，带入调用参数。
#runstrat()runstrat('--plot --fromdate=1998-01-01 --todate=2000-01-01'.split())修改以上内容后，就可以直接在jupyter中执行Backtrader的示例了。