- Don't create unnecessary extra data (requires passing fastd_period=1
to TA-Lib or else it fills the FastK with NaNs even though it must
have already computed them...
- Use random_sample instead of random_integers so that we're not
dependent on integer arithmetic.
- Pass array_decimal to assert_equal so that we do almost equal checking
on results.
Use the future asset equity pricing reader, instead of reading directly
from the bcolz table. Required since the format for writing the future
data now uses the minute bar reader/writer pair.
Add test cases to `test_data_portal` asserting both equity and future
`get_spot_value` results.
Also, add direct coverage of last_traded_dt in the `test_data_portal`
module.
Prepares for adding test coverage of `get_last_traded_dt` for `Future` assets.
Encapsulate the shared global calendar map in an object.
This allows consumers that don't want to participate in custom
registration to pass around a calendar dispatcher, and would make it
easier to support contextual management of the global calendar map if we
want to do that in the future.
As a bonus, we now only create one instance of each calendar, instead of
one per alias.
Change the mock minute data to no longer use an increasing arange, so
that a days worth of minute data can be summed and fit inside of a
uint32.
This change was required because of working on new test data that looked
like [0, 100, 200, 0, ] which was resulting in a daily rollup of 0 data,
when the coverage needed a non-0 value.
Also, factor out the resampling function, with an eye on a making it
easier to convert from minute bars to daily bars during ingest/load
processes.
When adding fixtures for futures data, there will be a need for multiple
calendars in the fixture ecosystem. e.g. a test that includes both
equities and futures would need an overall calendar which encompasses
both equities and futures; however, the test data for equities should
still still be limited to the bounds set by the NYSE calendar.
Make the fixtures that setup trading calendars and values dervied from
the trading calendar (e.g. trading sessions) accept an iterable of
calendars which need to be created, then populate those values into a
dict keyed by the calendar name.
Change `WithNYSETradingDays` to include sessions in the name,
since we are moving to session as the name for the 'day' unit.
Provide `trading_days` which is really "NYSE trading sessions` on
`WithTradingSessions` for backwards compatibility.
Eddie Hebert