To support using a `DataPortal` and `HistoryLoader` in a notebook, allow
the prefetch length to be configurable, so that it can be set to 0.
Unlike backtesting where the prefetch is useful for repeated history
windows viewed from datetimes which are monotonically increasing by a
small amount, the notebook usage of history windows needs only to
retrieve the exact data needed for the window specified.
This patch also fixes some boundary conditions related to rolls and
adjustments which were uncovered by querying for the adjustments with an
end date near the end of the window.
Rename _get_daily_window_for_sids to _get_daily_window_data.
Rename _get_minute_window_for_assets to _get_minute_window_data.
Rename _get_daily_data to get_daily_spot_value.
Instead of using the difference between the session close of the front
contract before the roll and and the open of back contract on the
beginning of the roll, use the close of both at the end of the session
before the roll.
The closes of the session prior to roll is in lieu of settlement data.
Make `__next__` and `seek` share code instead of seek() calling
`__next__`. This avoids having to make a large number of integer
comparisons and `asanyarray` calls when seeking more than one tick
forward.
There have been cases where the requested start or end date is not in
the history calendar.
Add the beginning and of the calendar to the KeyError to give more
detail to figure out root cause.
Add roll style which takes the volume of the contracts into account.
If the volume moves from the front to the back before the auto close
date, the roll is put at that session.
Also, factors out some of the common logic shared with calendar based rolls.
Match the behavior of the minute bar reader, now that the session and
minute bar readers share a common interface.
isnull is slightly slower than checking against -1; however, n cases
where we check against illiquid trades in a tight loop, volume is
checked which is not using nan. The change here should be marginal with
regards to performance.
The last traded dt provided from the session bar reader which resamples
from minutes should provide a dt that is a session label, not one that
is at the minute frequency.
If a KeyError occurred in the adjustment logic, the exception would be
swallowed by the try block, which was intended to just check whether or
not there was an adjustment reader adjusted.
Discovered when some logic in a futures adjustment reader were failing
because of a mismatch of minute and session labels, which resulted in no
adjustments during windows when there should have been.
The minute to session sampling reading was creating two DataFrame
objects, the first to hold the minute data, and then a second returned
by the `DataFrame.groupby` to sample down to sessions.
Instead use the arrays returned by the minute readers `load_raw_arrays`
and implement sampling logic which takes advantage that the minutes
being passed start with the first minute of the first session and end
with the last minute of the last session.
On my machine this takes the tests in `test/test_continuous_futures`
from ~4.0 to about ~0.1 seconds.
