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This release includes a small number of bug fixes, documentation improvements, and build/dependency enhancements.
Conda packages for zipline and its dependencies are now available for python 3.6 on the ‘conda-forge’ Anaconda channel. They’re also available on the ‘Quantopian’ channel, but we’ll stop updating those eventually.
This release includes several enhancements and performance improvements along with a small number of bug fixes. We recommend that all users upgrade to this version.
NOTE: This will likely be the last minor release in the Zipline 1.x series. The release next will be Zipline 2.0, which will include a number of small breaking changes required to support international equities.
Support for Newer Numpy/Pandas Versions
Zipline has historically been very conservative when updating versions of numpy, pandas, and other "PyData" ecosystem packages. This conservatism is primarily due to the fact that Zipline is used as the backtesting engine for Quantopian, which means that updating package versions risks breaking a large installed codebase. Of course, many Zipline users don't have the backwards compatibility requirements that Quantopian has, and they'd like to be able to use the latest and greatest package versions.
As part of this release, we're now building and testing Zipline with two package configurations:
- "Stable", using numpy version 1.11 and pandas version 0.18.1.
- "Latest", using numpy version 1.14 and pandas version 0.22.0.
Other combinations of numpy and pandas may work, but these package sets will be built and tested during our normal development cycle.
Moving forward, our goal is to continue to maintain support for two sets of packages at any given time. The "stable" package set will change relatively infrequently, and will contain the versions of numpy and pandas supported on Quantopian. The "latest" package set will change regularly, and will contain recently-released versions of numpy and pandas.
Our hope with these changes is to strike a balance between stability and novelty without taking on too great a maintenance burden by supporting every possible combination of packages.
One of the most popular features of Zipline is its collection of trading calendars, which provide information about holidays and trading hours of various markets. As part of this release, Zipline's calendar-related functionality has been moved to a separate trading-calendars_ package, allowing users that only needed access to the calendars to use them without taking on the rest of Zipline's dependencies.
For backwards compability, Zipline will continue to re-export calendar-related functions. For example, zipline.get_calendar still exists, but is now an alias for
trading_calendars.get_calendar. Users that depend on this functionality are encouraged to update their imports to the new locations in
This release adds experimental support for running Zipline with user-defined subclasses of ~zipline.finance.blotter.blotter.Blotter. The primary motivation for this change is to make it easier to run live algorithms from the Zipline CLI.
There are two primary ways to configure a custom blotter:
- You can pass an instance of
blotterparameter to zipline.run_algorithm. (This functionality had existed previously, but wasn't well-documented.)
- You can register a named factory for a blotter in your
extension.pyand pass the name on the command line via the
An example usage of (2) might look like this:
from zipline.extensions import register from zipline.finance.blotter import Blotter, SimulationBlotter from zipline.finance.cancel_policy import EODCancel @register(Blotter, 'my-blotter') def my_blotter(): """Create a SimulationBlotter with a non-default cancel policy. """ return SimulationBlotter(cancel_policy=EODCancel())
To use this factory when running zipline from the command line, we would invoke zipline like this:
$ zipline run --blotter my-blotter <...other-args...>
As part of this change, the
zipline.finance.blotter.blotter.Blotter class has been converted to an abstract base class. The default blotter used in simulations is now named zipline.finance.blotter.SimulationBlotter.
Custom Command-Line Arguments
This release adds support for passing custom arguments to the
zipline command-line interface. Custom command-line arguments are passed via the
-x flag followed by a
key=value pair. Arguments passed this way can be accessed from Python code (e.g., an algorithm or an extension) via attributes of
zipline.extension_args. For example, if zipline is invoked like this:
$ zipline -x argle=bargle run ...
then the result of
zipline.extension_args.argle would be the string
Custom arguments can be grouped into namespaces by including
. characters in keys. For example, if zipline is invoked like this:
$ zipline -x argle.bargle=foo
zipline.extension_args.argle will contain an object with a
bargle attribute containing the string
"foo". Keys can contain multiple dots to create nested namespaces.
- Added support for pandas 0.22 and numpy 1.14. See above for details.
zipline.utils.calendarsinto a separately-installable trading-calendars_ package.
- Added support for specifying custom string arguments with the
-xflag. See above for details.
- Added support for registering custom subclass of zipline.finance.blotter.Blotter. See above for details.
Fixed a bug in zipline.pipeline.Factor.winsorize where NaN values were incorrectly included in value counts when determining cutoff thresholds for winsorization.
Fixed a crash in zipline.pipeline.Factor.top with a count of 1 and no groupby.
Fixed a bug where calling
data.historywith a negative lookback would fetch prices from the future.
Fixed a bug where StopOrder, LimitOrder, and StopLimitOrder prices were being rounded to the nearest penny regardless of asset tick size. Prices are now rounded based on the
tick_sizeattribute of the asset being ordered.
- Improved performance when fetching minutely prices for assets that trade regularly.
- Improved performance when fetching minutely prices for many assets by tuning cache sizes.
Maintenance and Refactorings
- Refactored large parts of the Zipline test suite to make it easier to change the signature of TradingAlgorithm.
- Added support for running travis builds with pandas 0.18 and 0.22.
- Added OSX builds to the travis build matrix.