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Can we rely on zipline inside our algos?

In the FAQ, zipline is on the whitelist of Python libraries we can use in our algorithms. Zipline has a lot of functionality that isn't documented in the Quantopian API, a fact that strikes me as a double-edged sword. On the one hand, a lot of this functionality seems useful for writing algorithms. What if, for example, you want your algo to take the federal funds rate into account when making decisions? But on the other hand, if features like that are likely to change, I wouldn't want to rely on one of them and then have a change to zipline break my algo. Also, we're not allowed to use fetcher in the contest, so if we rely on a feature of zipline that in turn relies in fetcher, will the algo be disqualified from the contest?

1 response

Zipline is our open-sourced backtester, and the Quantopian IDE runs on top of this engine. Majority of the features are already pre-imported and available in the IDE such as ordering, logging, transformations, and more. The differences come down to the data source.

Using Zipline on your local machine, you'll need your own data feed. Most people use Yahoo Finance or their own data source (i.e. if they're backtesting international equities).

In Quantopian, the IDE runs using our native price, fundamental, and custom data. We've had minute-level pricing available since our platform's inception, and earlier this year added fundamental data from Morningstar. Last month we launched the [Quantopian Store][1], offering 22 custom datasets including earnings calendar, buybacks, dividends, and more. And we're far from done! Currently, we're working to add over 50 additional datasets. Interest rates are part of this group. Once available, they'll be seamlessly integrated into the platform and you can import the data into your algo. You can also use this data in your contest entry.

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