fixed merge conflict in decimal.py

python/cudf/cudf/core/column/categorical.py

@@ -32,10 +32,10 @@
 from cudf.core.dtypes import CategoricalDtype
 from cudf.utils.dtypes import (
     is_categorical_dtype,
+    is_interval_dtype,
     is_mixed_with_object_dtype,
     min_signed_type,
     min_unsigned_type,
-    is_interval_dtype,
 )
 
 if TYPE_CHECKING:
@@ -1388,10 +1388,10 @@ def as_categorical_column(
             new_categories=dtype.categories, ordered=dtype.ordered
         )
 
-    def as_numerical_column(self, dtype: Dtype) -> NumericalColumn:
+    def as_numerical_column(self, dtype: Dtype, **kwargs) -> NumericalColumn:
         return self._get_decategorized_column().as_numerical_column(dtype)
 
-    def as_string_column(self, dtype, format=None) -> StringColumn:
+    def as_string_column(self, dtype, format=None, **kwargs) -> StringColumn:
         return self._get_decategorized_column().as_string_column(
             dtype, format=format
         )

python/cudf/cudf/core/column/column.py

@@ -879,7 +879,7 @@ def can_cast_safely(self, to_dtype: Dtype) -> bool:
 
     def astype(self, dtype: Dtype, **kwargs) -> ColumnBase:
         if _is_non_decimal_numeric_dtype(dtype):
-            return self.as_numerical_column(dtype)
+            return self.as_numerical_column(dtype, **kwargs)
         elif is_categorical_dtype(dtype):
             return self.as_categorical_column(dtype, **kwargs)
         elif pandas_dtype(dtype).type in {
@@ -903,7 +903,7 @@ def astype(self, dtype: Dtype, **kwargs) -> ColumnBase:
         elif np.issubdtype(dtype, np.timedelta64):
             return self.as_timedelta_column(dtype, **kwargs)
         else:
-            return self.as_numerical_column(dtype)
+            return self.as_numerical_column(dtype, **kwargs)
 
     def as_categorical_column(self, dtype, **kwargs) -> ColumnBase:
         if "ordered" in kwargs:
@@ -949,7 +949,7 @@ def as_categorical_column(self, dtype, **kwargs) -> ColumnBase:
         )
 
     def as_numerical_column(
-        self, dtype: Dtype
+        self, dtype: Dtype, **kwargs
     ) -> "cudf.core.column.NumericalColumn":
         raise NotImplementedError
 
@@ -969,7 +969,7 @@ def as_timedelta_column(
         raise NotImplementedError
 
     def as_string_column(
-        self, dtype: Dtype, format=None
+        self, dtype: Dtype, format=None, **kwargs
     ) -> "cudf.core.column.StringColumn":
         raise NotImplementedError
 

python/cudf/cudf/core/column/datetime.py

@@ -241,14 +241,14 @@ def as_timedelta_column(
         )
 
     def as_numerical_column(
-        self, dtype: Dtype
+        self, dtype: Dtype, **kwargs
     ) -> "cudf.core.column.NumericalColumn":
         return cast(
             "cudf.core.column.NumericalColumn", self.as_numerical.astype(dtype)
         )
 
     def as_string_column(
-        self, dtype: Dtype, format=None
+        self, dtype: Dtype, format=None, **kwargs
     ) -> "cudf.core.column.StringColumn":
         if format is None:
             format = _dtype_to_format_conversion.get(

python/cudf/cudf/core/column/decimal.py

@@ -221,12 +221,12 @@ def as_decimal_column(
         return libcudf.unary.cast(self, dtype)
 
     def as_numerical_column(
-        self, dtype: Dtype
+        self, dtype: Dtype, **kwargs
     ) -> "cudf.core.column.NumericalColumn":
         return libcudf.unary.cast(self, dtype)
 
     def as_string_column(
-        self, dtype: Dtype, format=None
+        self, dtype: Dtype, format=None, **kwargs
     ) -> "cudf.core.column.StringColumn":
         if len(self) > 0:
             return cpp_from_decimal(self)

python/cudf/cudf/core/column/numerical.py

@@ -208,7 +208,7 @@ def int2ip(self) -> "cudf.core.column.StringColumn":
         return libcudf.string_casting.int2ip(self)
 
     def as_string_column(
-        self, dtype: Dtype, format=None
+        self, dtype: Dtype, format=None, **kwargs
     ) -> "cudf.core.column.StringColumn":
         if len(self) > 0:
             return string._numeric_to_str_typecast_functions[
@@ -252,7 +252,7 @@ def as_decimal_column(
     ) -> "cudf.core.column.Decimal64Column":
         return libcudf.unary.cast(self, dtype)
 
-    def as_numerical_column(self, dtype: Dtype) -> NumericalColumn:
+    def as_numerical_column(self, dtype: Dtype, **kwargs) -> NumericalColumn:
         dtype = np.dtype(dtype)
         if dtype == self.dtype:
             return self

python/cudf/cudf/core/column/string.py

@@ -5118,7 +5118,7 @@ def str(self, parent: ParentType = None) -> StringMethods:
         return StringMethods(self, parent=parent)
 
     def as_numerical_column(
-        self, dtype: Dtype
+        self, dtype: Dtype, **kwargs
     ) -> "cudf.core.column.NumericalColumn":
         out_dtype = np.dtype(dtype)
 
@@ -5195,7 +5195,9 @@ def as_decimal_column(
     ) -> "cudf.core.column.Decimal64Column":
         return cpp_to_decimal(self, dtype)
 
-    def as_string_column(self, dtype: Dtype, format=None) -> StringColumn:
+    def as_string_column(
+        self, dtype: Dtype, format=None, **kwargs
+    ) -> StringColumn:
         return self
 
     @property

python/cudf/cudf/core/column/timedelta.py

@@ -322,7 +322,7 @@ def fillna(
             return super().fillna(method=method)
 
     def as_numerical_column(
-        self, dtype: Dtype
+        self, dtype: Dtype, **kwargs
     ) -> "cudf.core.column.NumericalColumn":
         return cast(
             "cudf.core.column.NumericalColumn", self.as_numerical.astype(dtype)
@@ -336,7 +336,7 @@ def as_datetime_column(
         )
 
     def as_string_column(
-        self, dtype: Dtype, format=None
+        self, dtype: Dtype, format=None, **kwargs
     ) -> "cudf.core.column.StringColumn":
         if format is None:
             format = _dtype_to_format_conversion.get(

python/cudf/cudf/tests/test_dataframe.py

@@ -736,6 +736,17 @@ def test_dataframe_astype(nelem):
     np.testing.assert_equal(df["a"].to_array(), df["b"].to_array())
 
 
+def test_astype_dict():
+    gdf = cudf.DataFrame({"a": [1, 2, 3], "b": ["1", "2", "3"]})
+    pdf = gdf.to_pandas()
+
+    assert_eq(pdf.astype({"a": "str"}), gdf.astype({"a": "str"}))
+    assert_eq(
+        pdf.astype({"a": "str", "b": np.int64}),
+        gdf.astype({"a": "str", "b": np.int64}),
+    )
+
+
 @pytest.mark.parametrize("nelem", [0, 100])
 def test_index_astype(nelem):
     df = cudf.DataFrame()