The daily/session bar reader's `spot_price` took the same parameters and
returned the same kind of output as the minute bar reader's `get_value`.
Standardize on one method to make a common interface, which may be
formally factored out in a later patch; to help enable writing reader
implementations or mixins which can be agnostic to the bar frequency.
Instead of having separate ExchangeCalendar and TradingSchedule objects, we
now just have TradingCalendar. The TradingCalendar keeps track of each
session (defined as a contiguous set of minutes between an open and a close).
It's also responsible for handling the grouping logic of any given minute
to its containing session, or the next/previous session if it's not a market
minute for the given calendar.
In preparation of adding futures, add equity to the names of both the
classes and methods for writing bcolz data. Futures data will use a
different minutes per day with a separate reader. This change will allow
both equity and futures fixtures to be side by side.
Also, break out the method which generates the dataframes and trading
days member into fixtures (`EquityMinuteBarData` and
`EquityDailyBarData`) on which the `*BarReader` fixture depends. This
fixture is separated out to enable reader/writers in different formats
to use the same data setup. (There is internal code which needs to write
minute and daily bar data in a database format.)
Changes BcolzDailyBarWriter to not be an abc, data is passed as an
iterator of (sid, dataframe) pairs to the write method.
Changes the AssetsDBWriter to be a single class which accepts an engine
at construction time and has a `write` method for writing dataframes for
the various tables. We no longer support writing the various other data
types, callers should coerce their data into a dataframe themselves. See
zipline.assets.synthetic for some helpers to do this.
Adds many new fixtures and updates some existing fixtures to use the new
ones:
WithDefaultDateBounds
A fixture that provides the suite a START_DATE and END_DATE. This is
meant to make it easy for other fixtures to synchronize their date
ranges without depending on eachother in strange ways. For example,
WithBcolzMinuteBarReader and WithBcolzDailyBarReader by default should
both have data for the same dates, so they may use depend on
WithDefaultDates without forcing a dependency between them.
WithTmpDir, WithInstanceTmpDir
Provides the suite or individual test case a temporary directory.
WithBcolzDailyBarReader
Provides the suite a BcolzDailyBarReader which reads from bcolz data
written to a temporary directory. The data will be read from
dataframes and then converted to bcolz files with
BcolzDailyBarWriter.write
WithBcolzDailyBarReaderFromCSVs
Provides the suite a BcolzDailyBarReader which reads from bcolz data
written to a temporary directory. The data will be read from a
collection of CSV files and then converted into the bcolz data through
BcolzDailyBarWriter.write_csvs
WithBcolzMinuteBarReader
Provides the suite a BcolzMinuteBarReader which reads from bcolz data
written to a temporary directory. The data will be read from
dataframes and then converted to bcolz files with
BcolzMinuteBarWriter.write
WithAdjustmentReader
Provides the suite a SQLiteAdjustmentReader which reads from an in
memory sqlite database. The data will be read from dataframes and then
converted into sqlite with SQLiteAdjustmentWriter.write
WithDataPortal
Provides each test case a DataPortal object with data from temporary
resources.
Renames zipline.utils.test_utils to zipline.testing
Adds zipline.testing.fixtures.ZiplineTestCase to manage setup and
teardown and adds mixins to define fixtures like an asset finder or
trading calendar.
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.
To prepare for querying for payouts from SQLite, write the dividend
payouts to a new table `dividend_payouts`.
Change the expected columns of the passed dividend frame to contain the
payout data, and use that data to calculate the ratios (this moves
internal code that was calcualting the ratios into Zipline.)
The end result is that instead of just a `dividends` table with the
backward looking adjustment ratios, also write a `dividend_payouts`
table and a `stock_dividend_payout` table.
Put the logic for reading and writing the equity price and adjustment
data into a module located in data, making it distinct from the pipeline
loader usage of the formats.
This prepares for both incoming changes of how adjustments are written,
(which includes using the bcolz daily reader as an input), as well as
eventually providing the readers to a DataPortal object.
Conner Fromknecht