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Can't import zipline.TradingAlgorithm() or zipline.run_algorithm() in Notebook

Hi, I'm trying to run a backtest in the research environment. I can't seem to import zipline.run_algorithm() or zipline.TradingAlgorithm(). I get the following error:

"Importing zipline.run_algorithm raised ImportError. No modules or attributes with a similar name were found. Last warning! One more import error and your account will be suspended for security reasons until a human can talk to you. "

Needless to say, I tried to import it in several ways, several times. :)

How do I solve this? And what function do I use to run a backtest? They have very similar inputs.

Thank you.

4 responses

Hi David, as of June 18, we removed the ability to import and use the zipline.TradingAlgorithm class in Research and in Backtesting. You can read the reasoning behind why it was removed in this forum thread. The feature was poorly supported, as it make running pipelines within algorithms difficult, and it required static data to be passed into the constructor.

Because of this we recommend you move your work from the research environment to the IDE.


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Understood. Is there a way to analyze a DataFrame that I output at the end of the backtest (via in the notebook? I haven't found anything. Having to run a huge backtest and dealing with the log limitations takes a lot of time, that's the only reason I was looking to do the backtest with the Notebook.

Until Q's new end_of_backtest() function :) with extra room available, there's this, however it is still subject to the logging limits.

Yes, I've been using something similar to that, although I didn't know about get_environment('end').date(), that will be really useful. From what I've been able to test, the logging limits aren't that extreme (you can print about 22 dataframes that are 12x7 per day), but maybe I could print a few dataframes at 1/2/3/4/5 days before the backtest ends, since the results would be identical with big backtests. I don't know if the logging limits allow that, I'll have to see. Thank you.