PERF: cache_readonly for Block properties (#40620)

Author: jbrockmendel

pandas/core/internals/blocks.py

@@ -36,6 +36,7 @@
     Shape,
     final,
 )
+from pandas.util._decorators import cache_readonly
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
@@ -165,7 +166,7 @@ class Block(libinternals.Block, PandasObject):
     _validate_ndim = True
 
     @final
-    @property
+    @cache_readonly
     def _consolidate_key(self):
         return self._can_consolidate, self.dtype.name
 
@@ -188,7 +189,7 @@ def _can_hold_na(self) -> bool:
         return values._can_hold_na
 
     @final
-    @property
+    @cache_readonly
     def is_categorical(self) -> bool:
         warnings.warn(
             "Block.is_categorical is deprecated and will be removed in a "
@@ -217,6 +218,7 @@ def internal_values(self):
         """
         return self.values
 
+    @property
     def array_values(self) -> ExtensionArray:
         """
         The array that Series.array returns. Always an ExtensionArray.
@@ -245,7 +247,7 @@ def get_block_values_for_json(self) -> np.ndarray:
         return np.asarray(self.values).reshape(self.shape)
 
     @final
-    @property
+    @cache_readonly
     def fill_value(self):
         # Used in reindex_indexer
         return na_value_for_dtype(self.dtype, compat=False)
@@ -353,7 +355,7 @@ def shape(self) -> Shape:
         return self.values.shape
 
     @final
-    @property
+    @cache_readonly
     def dtype(self) -> DtypeObj:
         return self.values.dtype
 
@@ -378,6 +380,11 @@ def delete(self, loc) -> None:
         """
         self.values = np.delete(self.values, loc, 0)
         self.mgr_locs = self._mgr_locs.delete(loc)
+        try:
+            self._cache.clear()
+        except AttributeError:
+            # _cache not yet initialized
+            pass
 
     @final
     def apply(self, func, **kwargs) -> List[Block]:
@@ -592,7 +599,7 @@ def astype(self, dtype, copy: bool = False, errors: str = "raise"):
         """
         values = self.values
         if values.dtype.kind in ["m", "M"]:
-            values = self.array_values()
+            values = self.array_values
 
         new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
 
@@ -931,7 +938,7 @@ def setitem(self, indexer, value):
             return self.coerce_to_target_dtype(value).setitem(indexer, value)
 
         if self.dtype.kind in ["m", "M"]:
-            arr = self.array_values().T
+            arr = self.array_values.T
             arr[indexer] = value
             return self
 
@@ -1445,7 +1452,7 @@ class ExtensionBlock(Block):
 
     values: ExtensionArray
 
-    @property
+    @cache_readonly
     def shape(self) -> Shape:
         # TODO(EA2D): override unnecessary with 2D EAs
         if self.ndim == 1:
@@ -1476,6 +1483,12 @@ def set_inplace(self, locs, values):
         #  see GH#33457
         assert locs.tolist() == [0]
         self.values = values
+        try:
+            # TODO(GH33457) this can be removed
+            self._cache.clear()
+        except AttributeError:
+            # _cache not yet initialized
+            pass
 
     def putmask(self, mask, new) -> List[Block]:
         """
@@ -1500,7 +1513,7 @@ def is_view(self) -> bool:
         """Extension arrays are never treated as views."""
         return False
 
-    @property
+    @cache_readonly
     def is_numeric(self):
         return self.values.dtype._is_numeric
 
@@ -1549,6 +1562,7 @@ def get_values(self, dtype: Optional[DtypeObj] = None) -> np.ndarray:
         # TODO(EA2D): reshape not needed with 2D EAs
         return np.asarray(self.values).reshape(self.shape)
 
+    @cache_readonly
     def array_values(self) -> ExtensionArray:
         return self.values
 
@@ -1675,10 +1689,7 @@ def where(self, other, cond, errors="raise") -> List[Block]:
             # The default `other` for Series / Frame is np.nan
             # we want to replace that with the correct NA value
             # for the type
-
-            # error: Item "dtype[Any]" of "Union[dtype[Any], ExtensionDtype]" has no
-            # attribute "na_value"
-            other = self.dtype.na_value  # type: ignore[union-attr]
+            other = self.dtype.na_value
 
         if is_sparse(self.values):
             # TODO(SparseArray.__setitem__): remove this if condition
@@ -1739,10 +1750,11 @@ class HybridMixin:
     array_values: Callable
 
     def _can_hold_element(self, element: Any) -> bool:
-        values = self.array_values()
+        values = self.array_values
 
         try:
-            values._validate_setitem_value(element)
+            # error: "Callable[..., Any]" has no attribute "_validate_setitem_value"
+            values._validate_setitem_value(element)  # type: ignore[attr-defined]
             return True
         except (ValueError, TypeError):
             return False
@@ -1768,9 +1780,7 @@ def _can_hold_element(self, element: Any) -> bool:
         if isinstance(element, (IntegerArray, FloatingArray)):
             if element._mask.any():
                 return False
-        # error: Argument 1 to "can_hold_element" has incompatible type
-        # "Union[dtype[Any], ExtensionDtype]"; expected "dtype[Any]"
-        return can_hold_element(self.dtype, element)  # type: ignore[arg-type]
+        return can_hold_element(self.dtype, element)
 
 
 class NDArrayBackedExtensionBlock(HybridMixin, Block):
@@ -1780,23 +1790,25 @@ class NDArrayBackedExtensionBlock(HybridMixin, Block):
 
     def internal_values(self):
         # Override to return DatetimeArray and TimedeltaArray
-        return self.array_values()
+        return self.array_values
 
     def get_values(self, dtype: Optional[DtypeObj] = None) -> np.ndarray:
         """
         return object dtype as boxed values, such as Timestamps/Timedelta
         """
-        values = self.array_values()
+        values = self.array_values
         if is_object_dtype(dtype):
             # DTA/TDA constructor and astype can handle 2D
-            values = values.astype(object)
+            # error: "Callable[..., Any]" has no attribute "astype"
+            values = values.astype(object)  # type: ignore[attr-defined]
         # TODO(EA2D): reshape not needed with 2D EAs
         return np.asarray(values).reshape(self.shape)
 
     def iget(self, key):
         # GH#31649 we need to wrap scalars in Timestamp/Timedelta
         # TODO(EA2D): this can be removed if we ever have 2D EA
-        return self.array_values().reshape(self.shape)[key]
+        # error: "Callable[..., Any]" has no attribute "reshape"
+        return self.array_values.reshape(self.shape)[key]  # type: ignore[attr-defined]
 
     def putmask(self, mask, new) -> List[Block]:
         mask = extract_bool_array(mask)
@@ -1805,14 +1817,16 @@ def putmask(self, mask, new) -> List[Block]:
             return self.astype(object).putmask(mask, new)
 
         # TODO(EA2D): reshape unnecessary with 2D EAs
-        arr = self.array_values().reshape(self.shape)
+        # error: "Callable[..., Any]" has no attribute "reshape"
+        arr = self.array_values.reshape(self.shape)  # type: ignore[attr-defined]
         arr = cast("NDArrayBackedExtensionArray", arr)
         arr.T.putmask(mask, new)
         return [self]
 
     def where(self, other, cond, errors="raise") -> List[Block]:
         # TODO(EA2D): reshape unnecessary with 2D EAs
-        arr = self.array_values().reshape(self.shape)
+        # error: "Callable[..., Any]" has no attribute "reshape"
+        arr = self.array_values.reshape(self.shape)  # type: ignore[attr-defined]
 
         cond = extract_bool_array(cond)
 
@@ -1848,15 +1862,17 @@ def diff(self, n: int, axis: int = 0) -> List[Block]:
         by apply.
         """
         # TODO(EA2D): reshape not necessary with 2D EAs
-        values = self.array_values().reshape(self.shape)
+        # error: "Callable[..., Any]" has no attribute "reshape"
+        values = self.array_values.reshape(self.shape)  # type: ignore[attr-defined]
 
         new_values = values - values.shift(n, axis=axis)
         new_values = maybe_coerce_values(new_values)
         return [self.make_block(new_values)]
 
     def shift(self, periods: int, axis: int = 0, fill_value: Any = None) -> List[Block]:
-        # TODO(EA2D) this is unnecessary if these blocks are backed by 2D EAs
-        values = self.array_values().reshape(self.shape)
+        # TODO(EA2D) this is unnecessary if these blocks are backed by 2D EA
+        # error: "Callable[..., Any]" has no attribute "reshape"
+        values = self.array_values.reshape(self.shape)  # type: ignore[attr-defined]
         new_values = values.shift(periods, fill_value=fill_value, axis=axis)
         new_values = maybe_coerce_values(new_values)
         return [self.make_block_same_class(new_values)]
@@ -1871,9 +1887,13 @@ def fillna(
             # TODO: don't special-case td64
             return self.astype(object).fillna(value, limit, inplace, downcast)
 
-        values = self.array_values()
-        values = values if inplace else values.copy()
-        new_values = values.fillna(value=value, limit=limit)
+        values = self.array_values
+        # error: "Callable[..., Any]" has no attribute "copy"
+        values = values if inplace else values.copy()  # type: ignore[attr-defined]
+        # error: "Callable[..., Any]" has no attribute "fillna"
+        new_values = values.fillna(  # type: ignore[attr-defined]
+            value=value, limit=limit
+        )
         new_values = maybe_coerce_values(new_values)
         return [self.make_block_same_class(values=new_values)]
 
@@ -1883,6 +1903,7 @@ class DatetimeLikeBlockMixin(NDArrayBackedExtensionBlock):
 
     is_numeric = False
 
+    @cache_readonly
     def array_values(self):
         return ensure_wrapped_if_datetimelike(self.values)
 

pandas/core/internals/managers.py

@@ -1668,7 +1668,7 @@ def internal_values(self):
 
     def array_values(self):
         """The array that Series.array returns"""
-        return self._block.array_values()
+        return self._block.array_values
 
     @property
     def _can_hold_na(self) -> bool: