REFACTOR-#6858: Rename _get_dimensions and change arguments

modin/core/dataframe/pandas/dataframe/dataframe.py

@@ -186,28 +186,31 @@ def row_lengths(self):
         if self._row_lengths_cache is None:
             if len(self._partitions.T) > 0:
                 row_parts = self._partitions.T[0]
-                self._row_lengths_cache = self._get_dimensions(row_parts, "length")
+                self._row_lengths_cache = self._get_lengths(row_parts, Axis.ROW_WISE)
             else:
                 self._row_lengths_cache = []
         return self._row_lengths_cache
 
     @classmethod
-    def _get_dimensions(cls, parts, dim_name):
+    def _get_lengths(cls, parts, axis):
         """
         Get list of  dimensions for all the provided parts.
 
         Parameters
         ----------
         parts : list
             List of parttions.
-        dim_name : string
-            Dimension name could be "length" or "width".
+        axis : {0, 1}
+            The axis along which to get the lengths (0 - length across rows or, 1 - width across columns).
 
         Returns
         -------
         list
         """
-        return [getattr(part, dim_name)() for part in parts]
+        if axis == Axis.ROW_WISE:
+            return [part.length() for part in parts]
+        else:
+            return [part.width() for part in parts]
 
     def __len__(self) -> int:
         """
@@ -236,7 +239,7 @@ def column_widths(self):
         if self._column_widths_cache is None:
             if len(self._partitions) > 0:
                 col_parts = self._partitions[0]
-                self._column_widths_cache = self._get_dimensions(col_parts, "width")
+                self._column_widths_cache = self._get_lengths(col_parts, Axis.COL_WISE)
             else:
                 self._column_widths_cache = []
         return self._column_widths_cache
@@ -3673,9 +3676,7 @@ def _compute_new_widths():
                     if all(
                         part._length_cache is not None for part in new_partitions.T[0]
                     ):
-                        new_lengths = self._get_dimensions(
-                            new_partitions.T[0], "length"
-                        )
+                        new_lengths = self._get_lengths(new_partitions.T[0], axis)
                     else:
                         new_lengths = None
         else:
@@ -3697,7 +3698,7 @@ def _compute_new_widths():
                 new_widths = []
                 if new_partitions.size > 0:
                     if all(part._width_cache is not None for part in new_partitions[0]):
-                        new_widths = self._get_dimensions(new_partitions[0], "width")
+                        new_widths = self._get_lengths(new_partitions[0], axis)
                     else:
                         new_widths = None
 

modin/core/dataframe/pandas/partitioning/partition_manager.py

@@ -122,7 +122,7 @@ def materialize_futures(cls, input_list):
         filtered_list = []
         filtered_idx = []
         for idx, item in enumerate(input_list):
-            if cls._execution_wrapper.check_is_future(item):
+            if cls._execution_wrapper.is_future(item):
                 filtered_idx.append(idx)
                 filtered_list.append(item)
         filtered_list = cls._execution_wrapper.materialize(filtered_list)

modin/core/execution/dask/common/engine_wrapper.py

@@ -92,7 +92,7 @@ def deploy(
         return remote_task_future
 
     @classmethod
-    def check_is_future(cls, item):
+    def is_future(cls, item):
         """
         Check if the item is a Future.
 

modin/core/execution/python/common/engine_wrapper.py

@@ -42,7 +42,7 @@ def deploy(cls, func, f_args=None, f_kwargs=None, num_returns=1):
         return func(*args, **kwargs)
 
     @classmethod
-    def check_is_future(cls, item):
+    def is_future(cls, item):
         """
         Check if the item is a Future.
 

modin/core/execution/ray/common/engine_wrapper.py

@@ -76,7 +76,7 @@ def deploy(cls, func, f_args=None, f_kwargs=None, num_returns=1):
         )
 
     @classmethod
-    def check_is_future(cls, item):
+    def is_future(cls, item):
         """
         Check if the item is a Future.
 

modin/core/execution/ray/implementations/pandas_on_ray/dataframe/dataframe.py

@@ -13,6 +13,7 @@
 
 """Module houses class that implements ``PandasDataframe`` using Ray."""
 
+from modin.core.dataframe.base.dataframe.utils import Axis
 from modin.core.dataframe.pandas.dataframe.dataframe import PandasDataframe
 
 from ..partitioning.partition_manager import PandasOnRayDataframePartitionManager
@@ -42,20 +43,24 @@ class PandasOnRayDataframe(PandasDataframe):
 
     _partition_mgr_cls = PandasOnRayDataframePartitionManager
 
-    def _get_dimensions(self, parts, dim_name):
+    def _get_lengths(self, parts, axis):
         """
         Get list of  dimensions for all the provided parts.
 
         Parameters
         ----------
         parts : list
             List of parttions.
-        dim_name : string
-            Dimension name could be "length" or "width".
+        axis : {0, 1}
+            The axis along which to get the lengths (0 - length across rows or, 1 - width across columns).
 
         Returns
         -------
         list
         """
-        dims = [getattr(part, dim_name)(False) for part in parts]
+        if axis == Axis.ROW_WISE:
+            dims = [part.length(False) for part in parts]
+        else:
+            dims = [part.width(False) for part in parts]
+
         return self._partition_mgr_cls.materialize_futures(dims)

modin/core/execution/unidist/common/engine_wrapper.py

@@ -75,7 +75,7 @@ def deploy(cls, func, f_args=None, f_kwargs=None, num_returns=1):
         )
 
     @classmethod
-    def check_is_future(cls, item):
+    def is_future(cls, item):
         """
         Check if the item is a Future.