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Richard Frank
113 lines
3.9 KiB
Plaintext
113 lines
3.9 KiB
Plaintext
Release 0.9.0
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-------------
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:Release: 0.9.0
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:Date: March 29, 2016
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Highlights
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~~~~~~~~~~
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* Added classifiers and normalization methods to pipeline, along with new
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datasets and factors.
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* Added support for Windows with continuous integration on AppVeyor.
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Enhancements
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~~~~~~~~~~~~
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* Added new datasets
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:class:`~zipline.pipeline.data.buyback_auth.CashBuybackAuthorizations`
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and :class:`~zipline.pipeline.data.buyback_auth.ShareBuybackAuthorizations`
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for use in the Pipeline API. These datasets provide an abstract interface for
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adding cash and share buyback authorizations data, respectively, to a new
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algorithm. pandas-based reference implementations for these datasets can be
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found in :mod:`zipline.pipeline.loaders.buyback_auth`, and experimental
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blaze-based implementations can be found in
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:mod:`zipline.pipeline.loaders.blaze.buyback_auth`. (:issue:`1022`).
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* Added new datasets
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:class:`~zipline.pipeline.data.dividends.DividendsByExDate`,
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:class:`~zipline.pipeline.data.dividends.DividendsByPayDate`, and
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:class:`~zipline.pipeline.data.dividends.DividendsByAnnouncementDate`
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for use in the Pipeline API. These datasets provide an abstract interface for
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adding dividends data organized by ex date, pay date, and announcement date,
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respectively, to a new algorithm. pandas-based reference implementations for
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these datasets can be found in :mod:`zipline.pipeline.loaders.dividends`, and
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experimental blaze-based implementations can be found in
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:mod:`zipline.pipeline.loaders.blaze.dividends`. (:issue:`1093`).
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* Added new built-in factors,
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:class:`zipline.pipeline.factors.BusinessDaysSinceCashBuybackAuth` and
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:class:`zipline.pipeline.factors.BusinessDaysSinceShareBuybackAuth`. These
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factors use the new ``CashBuybackAuthorizations`` and
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``ShareBuybackAuthorizations`` datasets, respectively. (:issue:`1022`).
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* Added new built-in factors,
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:class:`zipline.pipeline.factors.BusinessDaysSinceDividendAnnouncement`,
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:class:`zipline.pipeline.factors.BusinessDaysUntilNextExDate`, and
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:class:`zipline.pipeline.factors.BusinessDaysSincePreviousExDate`. These
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factors use the new ``DividendsByAnnouncementDate` and ``DividendsByExDate``
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datasets, respectively. (:issue:`1093`).
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* Implemented :class:`zipline.pipeline.Classifier`, a new core pipeline API
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term representing grouping keys. Classifiers are primarily used by passing
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them as the ``groupby`` parameter to factor normalization methods.
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(:issue:`1046`)
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* Added factor normalization methods:
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:meth:`zipline.pipeline.Factor.demean` and
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:meth:`zipline.pipeline.Factor.zscore`. (:issue:`1046`)
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* Added :meth:`zipline.pipeline.Factor.quantiles`, a method for computing a
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Classifier from a Factor by partitioning into equally-sized buckets. Also
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added helpers for common quantile sizes
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(:meth:`zipline.pipeline.Factor.quartiles`,
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:meth:`zipline.pipeline.Factor.quartiles`, and
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:meth:`zipline.pipeline.Factor.deciles`) (:issue:`1075`).
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Experimental Features
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~~~~~~~~~~~~~~~~~~~~~
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.. warning::
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Experimental features are subject to change.
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None
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Bug Fixes
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~~~~~~~~~
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* Fixed a bug where merging two numerical expressions failed given too many
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inputs. This caused running a pipeline to fail when combining more than ten
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factors or filters. (:issue:`1072`)
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Performance
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~~~~~~~~~~~
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None
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Maintenance and Refactorings
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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None
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Build
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~~~~~
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* Added AppVeyor for continuous integration on Windows. Added conda build of
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zipline and its dependencies to AppVeyor and Travis builds, which upload
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their results to anaconda.org labeled with "ci". (:issue:`981`)
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Documentation
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~~~~~~~~~~~~~
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None
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Miscellaneous
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~~~~~~~~~~~~~
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* Adds :class:`~zipline.testing.fixtures.ZiplineTestCase` which provides hooks
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to consume test fixtures. Fixtures are things like:
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:class:`~zipline.testing.fixtures.WithAssetFinder` which will make
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``self.asset_finder`` available to your test with some mock data
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(:issue:`1042`).
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