PERF: avoid calling .values to know the result dtype in eval()

pandas/core/computation/ops.py

@@ -146,15 +146,18 @@ def is_scalar(self) -> bool:
     @property
     def type(self):
         try:
-            # potentially very slow for large, mixed dtype frames
-            return self._value.values.dtype
+            # .values for dataframe would be slow
+            return self._value._mgr.as_array_dtype()
         except AttributeError:
             try:
-                # ndarray
-                return self._value.dtype
+                return self._value.values.dtype
             except AttributeError:
-                # scalar
-                return type(self._value)
+                try:
+                    # ndarray
+                    return self._value.dtype
+                except AttributeError:
+                    # scalar
+                    return type(self._value)
 
     return_type = type
 

pandas/core/internals/array_manager.py

@@ -1145,6 +1145,15 @@ def as_array(
 
         return result
 
+    def as_array_dtype(self):
+        """
+        The dtype of the np.ndarray when you would convert self to a numpy array
+        (i.e. calling ``mgr.as_array()`` or ``df.values``).
+        """
+        if len(self.arrays) == 0:
+            return np.dtype(float)
+        return interleaved_dtype([arr.dtype for arr in self.arrays])
+
 
 class SingleArrayManager(BaseArrayManager, SingleDataManager):
 

pandas/core/internals/managers.py

@@ -1549,6 +1549,22 @@ def as_array(
 
         return arr.transpose()
 
+    def as_array_dtype(self):
+        """
+        The dtype of the np.ndarray when you would convert self to a numpy array
+        (i.e. calling ``mgr.as_array()`` or ``df.values``).
+        """
+        if len(self.blocks) == 0:
+            return np.dtype(float)
+
+        if self.is_single_block:
+            return self.blocks[0].dtype
+
+        dtype = interleaved_dtype(  # type: ignore[assignment]
+            [blk.dtype for blk in self.blocks]
+        )
+        return dtype
+
     def _interleave(
         self,
         dtype: np.dtype | None = None,