consistent output in FedIndex to DatetimeIndex for date attrs

fedcal/_date_attributes.py

@@ -25,8 +25,9 @@
 from __future__ import annotations
 
 import warnings
-from typing import ClassVar, Generator
+from typing import ClassVar
 
+import numpy as np
 import pandas as pd
 from attrs import define, field
 from numpy.typing import NDArray
@@ -68,7 +69,8 @@ def __attrs_post_init__(self) -> None:
         if not type(self).fed_business_days:
             hol_instance = FedHolidays()
             type(self).fed_business_days = CustomBusinessDay(
-                normalize=True, calendar=hol_instance.holidays
+                normalize=True,
+                holidays=hol_instance.holidays,
             )
 
     @classmethod
@@ -91,27 +93,19 @@ def get_business_days(
         dates: DatetimeIndex = ensure_datetimeindex(dates=dates)
         with warnings.catch_warnings():
             warnings.simplefilter(action="ignore")
-            next_business_days = dates + cls.fed_business_days
-            return next_business_days == dates
+            return dates.isin(values=(dates+cls.fed_business_days))
 
-    def get_prior_business_day(
-        self, date: Timestamp
-    ) -> Generator[Timestamp, None, None]:
+    def get_prior_business_day(self, date: Timestamp) -> Timestamp:
         """
         Generates next earliest business day. Primarily for finding
         next-earliest business day before a military payday that doesn't
         fall on a business day.
 
-        Yields
-        ------
+        Returns
+        -------
         next nearest business day prior to the given date
         """
-        current_day: Timestamp = date - CustomBusinessDay(
-            calendar=self.fed_business_days.calendar
-        )
-        while current_day < date:
-            yield current_day
-            current_day += CustomBusinessDay(calendar=self.fed_business_days.calendar)
+        return self.fed_business_days.rollback(dt=date)
 
 
 @define(order=True, auto_attribs=True)
@@ -218,8 +212,13 @@ def guess_proclamation_holidays(
         )
         christmas_eves = christmas_days - pd.DateOffset(normalize=True, days=1)
         filtered_dates: DatetimeIndex = dates[dates.year > 2023]
-        return christmas_days.weekday.isin(values=[1, 4]) & (
-            filtered_dates == christmas_eves
+        return (
+            None
+            if filtered_dates.empty
+            else (
+                christmas_days.weekday.isin(values=[1, 4])
+                & (filtered_dates == christmas_eves)
+            )
         )
 
 

fedcal/_dept_status.py

@@ -396,4 +396,7 @@ def get_state_for_range_generator(
                             last_known_status[department] = status_pool[
                                 (department, status_key)
                             ]
-                    yield (str(key_date), last_known_status)
+                    yield (
+                        time_utils.to_timestamp(key_date).strftime(format="%Y-%m-%d"),
+                        last_known_status,
+                    )

fedcal/_mil.py

@@ -79,40 +79,21 @@ def get_mil_paydays(
         """
 
         dates = pd.DatetimeIndex(data=self.dates if dates is None else dates)
-        bizday_instance = _date_attributes.FedBusDay()
-
-        first_or_fifteenth_mask: Series = pd.Series(
-            data=(dates.day.isin(values=[1, 15])), index=dates, dtype=bool
-        )
-
-        business_days_mask = pd.Series(
-            data=dates.isin(
-                values=bizday_instance.get_business_days(dates=dates).index
-            ),
+        bday = _date_attributes.FedBusDay()
+        bdays = pd.Series(data=(bday.get_business_days(dates=dates)), index=dates)
+        pays = pd.Series(
+            data=(dates.day.isin(values=[1, 15]) & bdays),
             index=dates,
-            dtype=bool,
+            name="mil_paydays",
         )
-
-        payday_mask: Series[bool] = first_or_fifteenth_mask & business_days_mask
-
-        non_biz_1st_15th: DatetimeIndex = dates[
-            first_or_fifteenth_mask & ~business_days_mask
-        ]
-        for non_biz_date in non_biz_1st_15th:
-            prev_days: DatetimeIndex = pd.date_range(
-                start=non_biz_date - pd.Timedelta(days=3),
-                end=non_biz_date - pd.Timedelta(days=1),
+        non_std: DatetimeIndex = dates[dates.day.isin(values=[1, 15]) & ~pays]
+        for non_std_date in non_std:
+            closest_bday: Timestamp = bday.get_prior_business_day(
+                date=non_std_date - pd.Timedelta(days=1)
             )
-            prev_business_days: bool | pd.Series[
-                bool
-            ] = bizday_instance.get_business_days(dates=prev_days)
-            prev_business_day_mask: NDArray = prev_days.isin(values=prev_business_days)
-            recent_biz_day: Timestamp = prev_days.to_series()[
-                prev_business_day_mask
-            ].max()
-            payday_mask.at[recent_biz_day] = recent_biz_day in dates
-
-        return payday_mask
+            if closest_bday in dates:
+                pays.at[closest_bday] = True
+        return pays
 
 
 @define(order=True, kw_only=True)
@@ -213,7 +194,7 @@ def get_probable_passdays(
             dates[masks["wednesday_holidays"]] + pd.DateOffset(days=1)
         )
 
-        return (fri_mask | mon_mask | thurs_mask) & masks["eligible_days"]
+        return (fri_mask | mon_mask | thurs_mask) & masks["business_days"]
 
     @staticmethod
     def _get_base_masks(
@@ -233,28 +214,20 @@ def _get_base_masks(
         A dataframe of boolean masks, and date information
         """
 
-        bizday_instance = _date_attributes.FedBusDay()
-        holidays_instance = _date_attributes.FedHolidays()
+        bday = _date_attributes.FedBusDay()
+        holiday = _date_attributes.FedHolidays()
 
         mask_frame = pd.DataFrame(index=dates)
 
         mask_frame["dates"] = dates.to_series(index=dates)
-        mask_frame["holidays"] = dates.isin(values=holidays_instance.holidays)
+        mask_frame["holidays"] = dates.isin(values=holiday.holidays)
         mask_frame["holiday_days_of_week"] = dates.dayofweek
-
-        mask_frame["business_days"] = dates.isin(
-            values=bizday_instance.get_business_days(dates=dates).index
-        )
+        mask_frame["business_days"] = bday.get_business_days(dates=dates)
 
         for day, dow in zip(
             ["monday", "tuesday", "wednesday", "thursday", "friday"], range(5)
         ):
             mask_frame[f"{day}_holidays"] = (
                 mask_frame["holiday_days_of_week"] == dow
             ) & mask_frame["holidays"]
-
-        mask_frame["eligible_days"] = (
-            mask_frame["business_days"] & ~mask_frame["holidays"]
-        )
-
         return mask_frame

fedcal/fedindex.py

@@ -819,7 +819,7 @@ def posix_day(self) -> NDArray[int64]:
     @property
     def business_days(
         self,
-    ) -> NDArray[bool]:
+    ) -> DatetimeIndex:
         """
         Determine if the dates in the index are Federal business days.
 
@@ -828,16 +828,11 @@ def business_days(
 
         Returns
         -------
-        NDArray
-            An NDArray of boolean values, where True indicates a
-            business day.
-
+        Datetimeindex
+            Datetimeindex of dates that are business days.
         """
-        bizdays: FedBusDay = _date_attributes.FedBusDay()
-        next_business_days = self.datetimeindex + bizdays.get_business_days(
-            dates=self.datetimeindex
-        )
-        return self.datetimeindex.isin(values=next_business_days)
+        bdays: FedBusDay = _date_attributes.FedBusDay()
+        return self.datetimeindex[bdays.get_business_days(dates=self.datetimeindex)]
 
     @property
     def fys(self) -> Index[int]:
@@ -957,7 +952,7 @@ def fy_end(self) -> PeriodIndex:
         return self._fiscalcal.fy_end
 
     @property
-    def holidays(self) -> NDArray[bool]:
+    def holidays(self) -> DatetimeIndex:
         """
         Identify federal holidays in the index.
 
@@ -966,15 +961,16 @@ def holidays(self) -> NDArray[bool]:
 
         Returns
         -------
-        NDArray
-            An NDArray of boolean values, where True indicates a federal
-            holiday.
+        DatetimeIndex
+            DatetimeIndex reflecting dates of holidays
         """
         self._set_holidays()
-        return self.datetimeindex.isin(values=self._holidays.holidays)
+        return self.datetimeindex[
+            self.datetimeindex.isin(values=self._holidays.holidays)
+        ]
 
     @property
-    def proclaimed_holidays(self) -> NDArray[bool]:
+    def proclaimed_holidays(self) -> DatetimeIndex:
         """
         Check for proclaimed federal holidays in the index.
 
@@ -983,39 +979,40 @@ def proclaimed_holidays(self) -> NDArray[bool]:
 
         Returns
         -------
-        NDArray
-            An NDArray of boolean values, where True indicates a proclaimed
-            federalholiday.
+        DatetimeIndex
+            DatetimeIndex reflecting dates of proclaimed holidays.
         """
         self._set_holidays()
-        return self.datetimeindex.isin(
-            values=pd.DatetimeIndex(data=self._holidays.proclaimed_holidays)
-        )
+        return self.datetimeindex[
+            self.datetimeindex.isin(
+                values=pd.DatetimeIndex(data=self._holidays.proclaimed_holidays)
+            )
+        ]
 
     @property
-    def possible_proclamation_holidays(self) -> NDArray[bool]:
+    def possible_proclamation_holidays(self) -> DatetimeIndex:
         """
         Guesses if the dates in the index are possible *future* proclamation
         federal holidays.
 
         Returns
         -------
-        NDArray
-        NDArray of boolean values indicating possible proclamation
-        holidays.
+        DatetimeIndex
+            A DatetimeIndex reflecting possible *future* dates that could see a
+            proclaimed holiday.
 
         Notes
         -----
         See notes to FedStamp.possible_proclamation_holiday.
 
         """
         self._set_holidays()
-        return self._holidays.guess_proclamation_holidays(
-            datetimeindex=self.datetimeindex
-        )
+        return self.datetimeindex[
+            self._holidays.guess_proclamation_holidays(dates=self.datetimeindex)
+        ]
 
     @property
-    def probable_mil_passdays(self) -> NDArray[bool]:
+    def probable_mil_passdays(self) -> DatetimeIndex:
         """
         Estimate military pass days within the index's date range.
 
@@ -1026,19 +1023,18 @@ def probable_mil_passdays(self) -> NDArray[bool]:
 
         Returns
         -------
-        NDArray
-            An array of boolean values, where True indicates a probable
-            military pass day.
+        DatetimeIndex
+        A datetimeindex reflecting probable dates for military passdays.
         """
 
         passdays: ProbableMilitaryPassDay = _mil.ProbableMilitaryPassDay(
             dates=self.datetimeindex
         )
-        return passdays.passdays
+        return self.datetimeindex[passdays.passdays]
 
     # Payday properties
     @property
-    def mil_paydays(self) -> NDArray[bool]:
+    def mil_paydays(self) -> DatetimeIndex:
         """
         Identify military payday dates within the index.
 
@@ -1047,11 +1043,11 @@ def mil_paydays(self) -> NDArray[bool]:
 
         Returns
         -------
-        NDArray
-            A boolean array indicating military payday dates as True.
+        DatetimeIndex
+            A datetimeindex reflecting military payday dates.
         """
         milpays: MilitaryPayDay = _mil.MilitaryPayDay(dates=self.datetimeindex)
-        return milpays.paydays
+        return self.datetimeindex[milpays.paydays]
 
     @property
     def civ_paydays(self) -> Series[bool]:
@@ -1094,10 +1090,9 @@ def departments(self) -> DataFrame:
         )
 
         dept_df: DataFrame = self.datetimeindex.to_frame(name="Departments")
+        dhs_formed: Timestamp = time_utils.to_timestamp(constants.DHS_FORMED)
         dept_df["Departments"] = dept_df.index.map(
-            mapper=lambda date: all_depts
-            if date >= constants.DHS_FORMED
-            else pre_dhs_depts
+            mapper=lambda date: all_depts if date >= dhs_formed else pre_dhs_depts
         )
         return dept_df