PERF: concat_same_type for PeriodDtype

pandas/_libs/arrays.pyi

@@ -3,7 +3,9 @@ from typing import Sequence
 import numpy as np
 
 from pandas._typing import (
+    AxisInt,
     DtypeObj,
+    Self,
     Shape,
 )
 
@@ -32,3 +34,7 @@ class NDArrayBacked:
     def ravel(self, order=...): ...
     @property
     def T(self): ...
+    @classmethod
+    def _concat_same_type(
+        cls, to_concat: Sequence[Self], axis: AxisInt = ...
+    ) -> Self: ...

pandas/_libs/arrays.pyx

@@ -182,3 +182,10 @@ cdef class NDArrayBacked:
     def transpose(self, *axes):
         res_values = self._ndarray.transpose(*axes)
         return self._from_backing_data(res_values)
+
+    @classmethod
+    def _concat_same_type(cls, to_concat, axis=0):
+        # NB: We are assuming at this point that dtypes all match
+        new_values = [obj._ndarray for obj in to_concat]
+        new_arr = cnp.PyArray_Concatenate(new_values, axis)
+        return to_concat[0]._from_backing_data(new_arr)

pandas/core/arrays/_mixins.py

@@ -224,13 +224,11 @@ def _concat_same_type(
         to_concat: Sequence[Self],
         axis: AxisInt = 0,
     ) -> Self:
-        dtypes = {str(x.dtype) for x in to_concat}
-        if len(dtypes) != 1:
-            raise ValueError("to_concat must have the same dtype (tz)", dtypes)
+        if not lib.dtypes_all_equal([x.dtype for x in to_concat]):
+            dtypes = {str(x.dtype) for x in to_concat}
+            raise ValueError("to_concat must have the same dtype", dtypes)
 
-        new_values = [x._ndarray for x in to_concat]
-        new_arr = np.concatenate(new_values, axis=axis)
-        return to_concat[0]._from_backing_data(new_arr)
+        return super()._concat_same_type(to_concat, axis=axis)
 
     @doc(ExtensionArray.searchsorted)
     def searchsorted(

pandas/core/arrays/datetimelike.py

@@ -182,7 +182,11 @@ def new_meth(self, *args, **kwargs):
     return cast(F, new_meth)
 
 
-class DatetimeLikeArrayMixin(OpsMixin, NDArrayBackedExtensionArray):
+# error: Definition of "_concat_same_type" in base class "NDArrayBacked" is
+# incompatible with definition in base class "ExtensionArray"
+class DatetimeLikeArrayMixin(  # type: ignore[misc]
+    OpsMixin, NDArrayBackedExtensionArray
+):
     """
     Shared Base/Mixin class for DatetimeArray, TimedeltaArray, PeriodArray
 
@@ -505,42 +509,6 @@ def view(self, dtype: Dtype | None = None) -> ArrayLike:
         #  are present in this file.
         return super().view(dtype)
 
-    # ------------------------------------------------------------------
-    # ExtensionArray Interface
-
-    @classmethod
-    def _concat_same_type(
-        cls,
-        to_concat: Sequence[Self],
-        axis: AxisInt = 0,
-    ) -> Self:
-        new_obj = super()._concat_same_type(to_concat, axis)
-
-        obj = to_concat[0]
-        dtype = obj.dtype
-
-        new_freq = None
-        if isinstance(dtype, PeriodDtype):
-            new_freq = obj.freq
-        elif axis == 0:
-            # GH 3232: If the concat result is evenly spaced, we can retain the
-            # original frequency
-            to_concat = [x for x in to_concat if len(x)]
-
-            if obj.freq is not None and all(x.freq == obj.freq for x in to_concat):
-                pairs = zip(to_concat[:-1], to_concat[1:])
-                if all(pair[0][-1] + obj.freq == pair[1][0] for pair in pairs):
-                    new_freq = obj.freq
-
-        new_obj._freq = new_freq
-        return new_obj
-
-    def copy(self, order: str = "C") -> Self:
-        # error: Unexpected keyword argument "order" for "copy"
-        new_obj = super().copy(order=order)  # type: ignore[call-arg]
-        new_obj._freq = self.freq
-        return new_obj
-
     # ------------------------------------------------------------------
     # Validation Methods
     # TODO: try to de-duplicate these, ensure identical behavior
@@ -2085,6 +2053,7 @@ def _with_freq(self, freq) -> Self:
         return arr
 
     # --------------------------------------------------------------
+    # ExtensionArray Interface
 
     def factorize(
         self,
@@ -2102,6 +2071,34 @@ def factorize(
         # FIXME: shouldn't get here; we are ignoring sort
         return super().factorize(use_na_sentinel=use_na_sentinel)
 
+    @classmethod
+    def _concat_same_type(
+        cls,
+        to_concat: Sequence[Self],
+        axis: AxisInt = 0,
+    ) -> Self:
+        new_obj = super()._concat_same_type(to_concat, axis)
+
+        obj = to_concat[0]
+
+        if axis == 0:
+            # GH 3232: If the concat result is evenly spaced, we can retain the
+            # original frequency
+            to_concat = [x for x in to_concat if len(x)]
+
+            if obj.freq is not None and all(x.freq == obj.freq for x in to_concat):
+                pairs = zip(to_concat[:-1], to_concat[1:])
+                if all(pair[0][-1] + obj.freq == pair[1][0] for pair in pairs):
+                    new_freq = obj.freq
+                    new_obj._freq = new_freq
+        return new_obj
+
+    def copy(self, order: str = "C") -> Self:
+        # error: Unexpected keyword argument "order" for "copy"
+        new_obj = super().copy(order=order)  # type: ignore[call-arg]
+        new_obj._freq = self.freq
+        return new_obj
+
 
 # -------------------------------------------------------------------
 # Shared Constructor Helpers

pandas/core/arrays/datetimes.py

@@ -151,7 +151,9 @@ def f(self):
     return property(f)
 
 
-class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):
+# error: Definition of "_concat_same_type" in base class "NDArrayBacked" is
+# incompatible with definition in base class "ExtensionArray"
+class DatetimeArray(dtl.TimelikeOps, dtl.DatelikeOps):  # type: ignore[misc]
     """
     Pandas ExtensionArray for tz-naive or tz-aware datetime data.
 

pandas/core/arrays/numpy_.py

@@ -40,7 +40,9 @@
     )
 
 
-class PandasArray(
+# error: Definition of "_concat_same_type" in base class "NDArrayBacked" is
+# incompatible with definition in base class "ExtensionArray"
+class PandasArray(  # type: ignore[misc]
     OpsMixin,
     NDArrayBackedExtensionArray,
     ObjectStringArrayMixin,

pandas/core/arrays/period.py

@@ -109,7 +109,9 @@ def f(self):
     return property(f)
 
 
-class PeriodArray(dtl.DatelikeOps, libperiod.PeriodMixin):
+# error: Definition of "_concat_same_type" in base class "NDArrayBacked" is
+# incompatible with definition in base class "ExtensionArray"
+class PeriodArray(dtl.DatelikeOps, libperiod.PeriodMixin):  # type: ignore[misc]
     """
     Pandas ExtensionArray for storing Period data.
 
@@ -263,7 +265,10 @@ def _from_sequence(
             validate_dtype_freq(scalars.dtype, freq)
             if copy:
                 scalars = scalars.copy()
-            return scalars
+            # error: Incompatible return value type
+            # (got "Union[Sequence[Optional[Period]], Union[Union[ExtensionArray,
+            # ndarray[Any, Any]], Index, Series]]", expected "PeriodArray")
+            return scalars  # type: ignore[return-value]
 
         periods = np.asarray(scalars, dtype=object)
 

pandas/core/arrays/string_.py

@@ -228,7 +228,9 @@ def tolist(self):
         return list(self.to_numpy())
 
 
-class StringArray(BaseStringArray, PandasArray):
+# error: Definition of "_concat_same_type" in base class "NDArrayBacked" is
+# incompatible with definition in base class "ExtensionArray"
+class StringArray(BaseStringArray, PandasArray):  # type: ignore[misc]
     """
     Extension array for string data.
 

pandas/core/dtypes/dtypes.py

@@ -956,12 +956,9 @@ def __eq__(self, other: Any) -> bool:
         elif isinstance(other, PeriodDtype):
             # For freqs that can be held by a PeriodDtype, this check is
             # equivalent to (and much faster than) self.freq == other.freq
-            sfreq = self.freq
-            ofreq = other.freq
-            return (
-                sfreq.n == ofreq.n
-                and sfreq._period_dtype_code == ofreq._period_dtype_code
-            )
+            sfreq = self._freq
+            ofreq = other._freq
+            return sfreq.n == ofreq.n and self._dtype_code == other._dtype_code
 
         return False