Add the ability for an algorithm to request the current contract for a
future chain via `data.current`.
e.g.:
```
data.current(ContinuousFuture('CL', offset=0, roll='calendar'),
'contract')
```
This allows optionally setting the last available dts in the DataPortal
explicitly. If these args aren't provided, we fall back to inferring
these from the underlying readers, which was the previous behavior.
- Use parameter_space instead of `parameterized.expand`.
- Use a timedelta instead of concatenating strings.
- Use a (possibly no-op) scramble function instead of reordering list
literals.
- Use `freeze_dt, unfreeze_dt, re_freeze_dt` instead of `dts[n]`.
- Rename `assert_vectorized_results` to `assert_all_restrictions`.
In favor of a new method `set_restrictions` which takes a Restrictions
object. Calls to `set_do_not_order_list` should raise a deprecation
warning and create an equivalent Restrictions object, with which
`set_restrictions` will be called. For convenience, create a
RestrictionsSet from which the "restrictions" version of a security
list can be accessed
Introducing a WithCreateBarData fixture which allows for the
creation of a BarData using only the `simulation_dt_func` and
`restrictions` params. Assumes that each suite uses the same
`data_portal`, `data_frequency` and `trading_calendar`
The SecurityList implements a non-exposed method
`current_securities(dt)` which SecurityListRestrictions calls to
determine if an asset is restricted. Deprecate the `__iter__` and
`__contains__` methods of security lists in favor of
`current_securities(dt)`
An ABC Restrictions defines a group of restrictions responsible
for returning restriction information for sids on certain dts. An
InMemoryRestrictions is a point-in-time group of such restrictions,
with all restrictions and their dates passed in upon instantiation.
A StaticRestrictedList takes a list of sids, restricting them at all
dates
MAINT: optimization - only look at assets appearing in data
TST: simplify test
DOC: add documentation for checkpoints
MAINT: explicitly cast event date field to datetime
MAINT: add back import
TST: fix indexing to remove setting wtih copy warning
TST: fix quarter normalization test
TST: change test name
BUG: remove arg
BUG: look at dict keys
TST: add test for windowing
MAINT: raise ValueError instead of asserting
TST: add assertion to check windowing
TST: parametrize test over number of quarters forward/back.
BUG: fix adjustment calculation logic for quarter crossovers.
TST: add test for previous quarter windows
BUG: fix bugs in calculating previous windows
BUG: fix missing value for datetime
TST: add test case for missing quarter
With the addition of the truncate function, there are cases where we'll
want to construct a BcolzMinuteBarWriter to call truncate, without
gathering all the metadata. This commit adds a write_metadata arg to its
init, which is True by default. If False is specified, no metadata is
written.
Requires adding logic to truncate to update end_session in metadata to
the truncate date.
`future_chain` will be replaced by the as yet to be implemented method,
`data.current_chain`
Also removing `FutureChain` which will be replaced by another version
which only supports indexing and iteration.
Pandas 0.18 doesn't like having null-ish values in categoricals. Fixing
this properly requires re-thinking the semantics for missing_value on
pipeline terms, so we're punting on that until after we've upgraded to
0.18.
Pandas 0.18 deprecated passing "null-ish" values to pd.categorical. The
expectation, instead, is that you use categorical's native support for
missing data, which means the user will always get NaN's for missing
entries of the categorical.
A follow-up to this change should probably drop support for custom
missing values entirely and to use LabelArray/categorical for integer
data.