I get the OnWarmupFinished error below when overloading OptionUniverseSelectionModel. The code below is copied directly from the BasicTemplateOptionsFrameworkAlgorithm.py example on github, with the strikes and expirations modified. If I create a dummy OnWarmupFinished, I then get the second error.Has anyone else had trouble with this? I don't know if it's a bug, but it seems like it could be.class MyOptionUniverseSelectionModel(OptionUniverseSelectionModel):
def __init__(self, select_option_chain_symbols):
super().__init__(timedelta(1), select_option_chain_symbols)
def Filter(self, filter):
'''Defines the option chain universe filter'''
return (filter.Strikes(-1, -1).Expiration(90-15, 90-15))Runtime Error: SystemError : <bound method 'OnWarmupFinished'> returned a result with an error set SystemError : <bound method 'OnWarmupFinished'> returned a result with an error set (Open Stacktrace)
Runtime Error: SystemError : PyEval_EvalFrameEx returned a result with an error set SystemError : PyEval_EvalFrameEx returned a result with an error set (Open Stacktrace)
Derek Melchin
Hi Ryan,
We were unable to reproduce the error. See the attached backtest for reference. If the attached backtest doesn't solve the issue, please attach a full backtest so we can further assist.
Best,
Derek Melchin
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Ryan Morrow
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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