MAINT: Updates July 5th Holiday for pandas 17

zipline/utils/calendars/exchange_calendar.py

@@ -200,14 +200,14 @@ class ExchangeCalendar(with_metaclass(ABCMeta)):
             is_scheduled_day_hook=self.is_open_on_day,
         )
 
-    def next_start_and_end(self, date):
+    def next_open_and_close(self, date):
         return next_open_and_close(
             date,
             open_and_close_hook=self.open_and_close,
             next_scheduled_day_hook=self.next_trading_day,
         )
 
-    def previous_start_and_end(self, date):
+    def previous_open_and_close(self, date):
         return previous_open_and_close(
             date,
             open_and_close_hook=self.open_and_close,

zipline/utils/calendars/nyse_exchange_calendar.py

@@ -39,6 +39,7 @@ from pandas.tseries.holiday import(
 from pandas.tseries.offsets import Day
 from pytz import timezone
 
+from zipline.utils.pandas_utils import july_5th_holiday_observance
 from .exchange_calendar import ExchangeCalendar
 from .calendar_helpers import normalize_date
 
@@ -112,7 +113,8 @@ FridayAfterIndependenceDayExcept2013 = Holiday(
     month=7,
     day=5,
     days_of_week=(FRIDAY,),
-    observance=lambda dt: None if dt.year == 2013 else dt,
+    # The 2013 observance lambda is pandas version-dependent
+    observance=july_5th_holiday_observance,
     start_date=Timestamp("1995-01-01"),
 )
 USBlackFridayBefore1993 = Holiday(

zipline/utils/pandas_utils.py

@@ -1,10 +1,10 @@
 """
 Utilities for working with pandas objects.
 """
-from itertools import product
-import operator as op
-
 import pandas as pd
+from distutils.version import StrictVersion
+
+pandas_version = StrictVersion(pd.__version__)
 
 
 def explode(df):
@@ -17,93 +17,13 @@ def explode(df):
 
 
 try:
-    # pandas 0.16 compat
-    _df_sort_values = pd.DataFrame.sort_values
-    _series_sort_values = pd.Series.sort_values
+    # This branch is hit in pandas 17
+    sort_values = pd.DataFrame.sort_values
 except AttributeError:
-    _df_sort_values = pd.DataFrame.sort
-    _series_sort_values = pd.Series.sort
+    # This branch is hit in pandas 16
+    sort_values = pd.DataFrame.sort
 
-
-def sort_values(ob, *args, **kwargs):
-    if isinstance(ob, pd.DataFrame):
-        return _df_sort_values(ob, *args, **kwargs)
-    elif isinstance(ob, pd.Series):
-        return _series_sort_values(ob, *args, **kwargs)
-    raise ValueError(
-        'sort_values expected a dataframe or series, not %s: %r' % (
-            type(ob).__name__, ob,
-        ),
-    )
-
-
-def _time_to_micros(time):
-    """Convert a time into microseconds since midnight.
-
-    Parameters
-    ----------
-    time : datetime.time
-        The time to convert.
-
-    Returns
-    -------
-    us : int
-        The number of microseconds since midnight.
-
-    Notes
-    -----
-    This does not account for leap seconds or daylight savings.
-    """
-    seconds = time.hour * 60 * 60 + time.minute * 60 + time.second
-    return 1000000 * seconds + time.microsecond
-
-
-_opmap = dict(zip(
-    product((True, False), repeat=3),
-    product((op.le, op.lt), (op.le, op.lt), (op.and_, op.or_)),
-))
-
-
-def mask_between_time(dts, start, end, include_start=True, include_end=True):
-    """Return a mask of all of the datetimes in ``dts`` that are between
-    ``start`` and ``end``.
-
-    Parameters
-    ----------
-    dts : pd.DatetimeIndex
-        The index to mask.
-    start : time
-        Mask away times less than the start.
-    end : time
-        Mask away times greater than the end.
-    include_start : bool, optional
-        Inclusive on ``start``.
-    include_end : bool, optional
-        Inclusive on ``end``.
-
-    Returns
-    -------
-    mask : np.ndarray[bool]
-        A bool array masking ``dts``.
-
-    See Also
-    --------
-    :meth:`pandas.DatetimeIndex.indexer_between_time`
-    """
-    # This function is adapted from
-    # `pandas.Datetime.Index.indexer_between_time` which was originally
-    # written by Wes McKinney, Chang She, and Grant Roch.
-    time_micros = dts._get_time_micros()
-    start_micros = _time_to_micros(start)
-    end_micros = _time_to_micros(end)
-
-    left_op, right_op, join_op = _opmap[
-        bool(include_start),
-        bool(include_end),
-        start_micros <= end_micros,
-    ]
-
-    return join_op(
-        left_op(start_micros, time_micros),
-        right_op(time_micros, end_micros),
-    )
+if pandas_version >= StrictVersion('0.17.1'):
+    july_5th_holiday_observance = lambda dtix: dtix[dtix.year != 2013]
+else:
+    july_5th_holiday_observance = lambda dt: None if dt.year == 2013 else dt