loaders
This allows people to set their cutoff time to the time they will
actually execute 'before_trading_start'. Currently this is just passed
to the constructor of the loader; however, I would like to make this
managed by the algorithm simulation runner. This would help keep all of
the loaders in sync and lock 'before_trading_start's execution to the
time the data is queried for.
EarningsCalendar loader.
- Moves most of AdjustedArray back into Python. The window iterator is
the only part that's performance-intensive.
- Adds a bootleg templating system for creating specialized versions of
AdjustedArrayWindow for each concrete type we care about.
- Adds support for differently dtyped terms in pipeline. This allows us
to use datetime64s which are needed in the EarningsCalendar.
- Adds EarningsCalendar dataset for the next and previous earnings
announcements in pipeline.
- Adds in memory loader for EarningsCalendar.
- Adds blaze loader for EarningsCalendar.
nan* functions should get passed the actual array.
Also adds code-block directives to the docstring so that they get
highlighted by Sphinx as Python code.
- Generate links to sourcecode via the Sphinx `viewcode` extension.
- Generate reference docs for Asset/Equity/Future, AssetFinder, and
AssetDBWriter.
- Generate reference docs for Pipeline API classes.
- Fix broken links and formatting issues in the 0.8.4 whatsnew.
- Use embedsignature in _assets.pyx so that the signatures of Asset
subclasses are inspectable.
Fixes the case where a delta has an asof_date of the last requested
day and an index error would occur. This guards against this
specifically to make the delta be effective through the end of the
requested window.
Adds a test case for this behavior.
Rather than a list that's ordered the same as the received columns.
Most nontrivial loaders were constructing dicts internally and then
converting back to lists, only to have the engine convert **back again**
into a dict. This cuts out the middleman, and prevents bugs due to
incorrect ordering of the output arrays.
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