REF: avoid Period.freq

pandas/_libs/tslibs/period.pyi

@@ -3,6 +3,7 @@ from typing import Literal
 
 import numpy as np
 
+from pandas._libs.tslibs.dtypes import PeriodDtypeBase
 from pandas._libs.tslibs.nattype import NaTType
 from pandas._libs.tslibs.offsets import BaseOffset
 from pandas._libs.tslibs.timestamps import Timestamp
@@ -67,6 +68,7 @@ class PeriodMixin:
 class Period(PeriodMixin):
     ordinal: int  # int64_t
     freq: BaseOffset
+    _dtype: PeriodDtypeBase
 
     # error: "__new__" must return a class instance (got "Union[Period, NaTType]")
     def __new__(  # type: ignore[misc]

pandas/_libs/tslibs/period.pyx

@@ -1711,7 +1711,7 @@ cdef class _Period(PeriodMixin):
 
     def __richcmp__(self, other, op):
         if is_period_object(other):
-            if other.freq != self.freq:
+            if other._dtype != self._dtype:
                 if op == Py_EQ:
                     return False
                 elif op == Py_NE:
@@ -1781,7 +1781,7 @@ cdef class _Period(PeriodMixin):
         elif other is NaT:
             return NaT
         elif util.is_integer_object(other):
-            ordinal = self.ordinal + other * self.freq.n
+            ordinal = self.ordinal + other * self._dtype._n
             return Period(ordinal=ordinal, freq=self.freq)
 
         elif is_period_object(other):
@@ -1866,7 +1866,7 @@ cdef class _Period(PeriodMixin):
         # self.n can't be negative or 0
         end = how == "E"
         if end:
-            ordinal = self.ordinal + self.freq.n - 1
+            ordinal = self.ordinal + self._dtype._n - 1
         else:
             ordinal = self.ordinal
         ordinal = period_asfreq(ordinal, base1, base2, end)
@@ -2630,7 +2630,7 @@ class Period(_Period):
 
         elif is_period_object(value):
             other = value
-            if freq is None or freq._period_dtype_code == other.freq._period_dtype_code:
+            if freq is None or freq._period_dtype_code == other._dtype._dtype_code:
                 ordinal = other.ordinal
                 freq = other.freq
             else:

pandas/core/arrays/datetimelike.py

@@ -1309,7 +1309,7 @@ def __add__(self, other):
             if not isinstance(self.dtype, PeriodDtype):
                 raise integer_op_not_supported(self)
             obj = cast("PeriodArray", self)
-            result = obj._addsub_int_array_or_scalar(other * obj.freq.n, operator.add)
+            result = obj._addsub_int_array_or_scalar(other * obj.dtype._n, operator.add)
 
         # array-like others
         elif is_timedelta64_dtype(other_dtype):
@@ -1327,7 +1327,7 @@ def __add__(self, other):
             if not isinstance(self.dtype, PeriodDtype):
                 raise integer_op_not_supported(self)
             obj = cast("PeriodArray", self)
-            result = obj._addsub_int_array_or_scalar(other * obj.freq.n, operator.add)
+            result = obj._addsub_int_array_or_scalar(other * obj.dtype._n, operator.add)
         else:
             # Includes Categorical, other ExtensionArrays
             # For PeriodDtype, if self is a TimedeltaArray and other is a
@@ -1367,7 +1367,7 @@ def __sub__(self, other):
             if not isinstance(self.dtype, PeriodDtype):
                 raise integer_op_not_supported(self)
             obj = cast("PeriodArray", self)
-            result = obj._addsub_int_array_or_scalar(other * obj.freq.n, operator.sub)
+            result = obj._addsub_int_array_or_scalar(other * obj.dtype._n, operator.sub)
 
         elif isinstance(other, Period):
             result = self._sub_periodlike(other)
@@ -1391,7 +1391,7 @@ def __sub__(self, other):
             if not isinstance(self.dtype, PeriodDtype):
                 raise integer_op_not_supported(self)
             obj = cast("PeriodArray", self)
-            result = obj._addsub_int_array_or_scalar(other * obj.freq.n, operator.sub)
+            result = obj._addsub_int_array_or_scalar(other * obj.dtype._n, operator.sub)
         else:
             # Includes ExtensionArrays, float_dtype
             return NotImplemented

pandas/core/arrays/period.py

@@ -104,7 +104,7 @@
 
 def _field_accessor(name: str, docstring: str | None = None):
     def f(self):
-        base = self.freq._period_dtype_code
+        base = self.dtype._dtype_code
         result = get_period_field_arr(name, self.asi8, base)
         return result
 
@@ -543,7 +543,7 @@ def to_timestamp(self, freq=None, how: str = "start") -> DatetimeArray:
             diffs = libalgos.unique_deltas(self.asi8)
             if len(diffs) == 1:
                 diff = diffs[0]
-                if diff == self.freq.n:
+                if diff == self.dtype._n:
                     dta._freq = self.freq
                 elif diff == 1:
                     dta._freq = self.freq.base
@@ -614,7 +614,7 @@ def asfreq(self, freq=None, how: str = "E") -> Self:
         # self.freq.n can't be negative or 0
         end = how == "E"
         if end:
-            ordinal = asi8 + self.freq.n - 1
+            ordinal = asi8 + self.dtype._n - 1
         else:
             ordinal = asi8
 

pandas/core/indexes/period.py

@@ -435,18 +435,7 @@ def get_loc(self, key):
             raise KeyError(orig_key) from err
 
     def _disallow_mismatched_indexing(self, key: Period) -> None:
-        sfreq = self.freq
-        kfreq = key.freq
-        if not (
-            sfreq.n == kfreq.n
-            # error: "BaseOffset" has no attribute "_period_dtype_code"
-            and sfreq._period_dtype_code  # type: ignore[attr-defined]
-            # error: "BaseOffset" has no attribute "_period_dtype_code"
-            == kfreq._period_dtype_code  # type: ignore[attr-defined]
-        ):
-            # GH#42247 For the subset of DateOffsets that can be Period freqs,
-            #  checking these two attributes is sufficient to check equality,
-            #  and much more performant than `self.freq == key.freq`
+        if key._dtype != self.dtype:
             raise KeyError(key)
 
     def _cast_partial_indexing_scalar(self, label: datetime) -> Period: