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Parallelize a Single Algorithm with Zipline

I'm using zipline to backtest a strategy involving thousands of equities with daily-level historical data. I'd like to speed this up by splitting the single backtest among all of my cpu cores, but as someone with shallow knowledge in both Python and CS, I'm not sure how to proceed or if this is even do-able.

4 responses

Run separate instances of python by splitting equities.

Luke, have you heard about our plans for a new Research environment? This will allow you to do this kind of analysis in an IPython Notebook. Take a look here and you can sign up to reserve your beta spot: https://www.quantopian.com/research

Here is a sneak-peek demo of the environment: https://www.youtube.com/watch?v=vKyGWMCEXYA

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I've signed up.

That said, I'm still looking for an easy way to parallelize now, perhaps using pool or some other multiprocessing tool. Pappu, your answer seems like a pain to implement, especially in the analysis phase when I'll have to somehow combine a bunch of separate performance outputs into one. Is there nothing simpler?

I was able to do this fairly easily a year or two ago using picloud. Unfortunately, it looks like that service has been shut down.