Following the documention sample code, "Strategy Selection Revisited", https://www.backtrader.com/blog/posts/2017-05-16-stsel-revisited/stsel-revisited/
when --maxcpus 1, everything is OK, but when --maxcpus 2, or anything else but 1, it reports :
multiprocessing.pool.MaybeEncodingError: Error sending result: '[<backtrader.cerebro.OptReturn object at 0x0000000015921988>]'. Reason: 'PicklingError("Can't pickle <class
'mp_main.St0'>: it's not the same object as mp_main.St0")'
what's the problem?
the related details:
(backtrader37) D:\Python\Jupyter\BackTrader\Test>python ./stselection-revisited.py --optreturn --maxcpus 2
Traceback (most recent call last):
File "./stselection-revisited.py", line 89, in <module>
runstrat()
File "./stselection-revisited.py", line 59, in runstrat
results = cerebro.run(maxcpus=args.maxcpus, optreturn=args.optreturn)
File "C:\Users\WEI.conda\envs\backtrader37\lib\site-packages\backtrader\cerebro.py", line 1143, in run
for r in pool.imap(self, iterstrats):
File "C:\Users\WEI.conda\envs\backtrader37\lib\multiprocessing\pool.py", line 748, in next
raise value
multiprocessing.pool.MaybeEncodingError: Error sending result: '[<backtrader.cerebro.OptReturn object at 0x0000000015921988>]'. Reason: 'PicklingError("Can't pickle <class
'mp_main.St0'>: it's not the same object as mp_main.St0")'
from future import (absolute_import, division, print_function,
unicode_literals)
import argparse
import backtrader as bt
from backtrader.utils.py3 import range
class StFetcher(object):
_STRATS = []
@classmethod
def register(cls, target):
cls._STRATS.append(target)
@classmethod
def COUNT(cls):
return range(len(cls._STRATS))
def __new__(cls, *args, **kwargs):
idx = kwargs.pop('idx')
obj = cls._STRATS[idx](*args, **kwargs)
return obj
@StFetcher.register
class St0(bt.SignalStrategy):
def init(self):
sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30)
crossover = bt.ind.CrossOver(sma1, sma2)
self.signal_add(bt.SIGNAL_LONG, crossover)
@StFetcher.register
class St1(bt.SignalStrategy):
def init(self):
sma1 = bt.ind.SMA(period=10)
crossover = bt.ind.CrossOver(self.data.close, sma1)
self.signal_add(bt.SIGNAL_LONG, crossover)
def runstrat(pargs=None):
args = parse_args(pargs)
cerebro = bt.Cerebro()
data = bt.feeds.BacktraderCSVData(dataname=args.data)
cerebro.adddata(data)
cerebro.addanalyzer(bt.analyzers.Returns)
cerebro.optstrategy(StFetcher, idx=StFetcher.COUNT())
results = cerebro.run(maxcpus=args.maxcpus, optreturn=args.optreturn)
strats = [x[0] for x in results] # flatten the result
for i, strat in enumerate(strats):
rets = strat.analyzers.returns.get_analysis()
print('Strat {} Name {}:\n - analyzer: {}\n'.format(
i, strat.__class__.__name__, rets))
def parse_args(pargs=None):
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
description='Sample for strategy selection')
parser.add_argument('--data', required=False,
default='../../datas/2005-2006-day-001.txt',
help='Data to be read in')
parser.add_argument('--maxcpus', required=False, action='store',
default=None, type=int,
help='Limit the numer of CPUs to use')
parser.add_argument('--optreturn', required=False, action='store_true',
help='Return reduced/mocked strategy object')
return parser.parse_args(pargs)
if name == 'main':
runstrat()
