Drop names, dtype in Index.copy and dtype, levels, codes …

…in `MultiIndex.copy` (#12898)

This PR removes `dtype` in Index & `MultiIndex.copy`, and `names` in Index.copy

python/cudf/cudf/core/index.py

@@ -302,7 +302,7 @@ def __contains__(self, item):
         return item in range(self._start, self._stop, self._step)
 
     @_cudf_nvtx_annotate
-    def copy(self, name=None, deep=False, dtype=None, names=None):
+    def copy(self, name=None, deep=False):
         """
         Make a copy of this object.
 
@@ -311,44 +311,11 @@ def copy(self, name=None, deep=False, dtype=None, names=None):
         name : object optional (default: None), name of index
         deep : Bool (default: False)
             Ignored for RangeIndex
-        dtype : numpy dtype optional (default: None)
-            Target dtype for underlying range data
-
-            .. deprecated:: 23.02
-
-               The `dtype` parameter is deprecated and will be removed in
-               a future version of cudf. Use the `astype` method instead.
-
-        names : list-like optional (default: False)
-            Kept compatibility with MultiIndex. Should not be used.
-
-            .. deprecated:: 23.04
-
-               The parameter `names` is deprecated and will be removed in
-               a future version of cudf. Use the `name` parameter instead.
 
         Returns
         -------
-        New RangeIndex instance with same range, casted to new dtype
+        New RangeIndex instance with same range
         """
-        if dtype is not None:
-            warnings.warn(
-                "parameter dtype is deprecated and will be removed in a "
-                "future version. Use the astype method instead.",
-                FutureWarning,
-            )
-
-        if names is not None:
-            warnings.warn(
-                "parameter names is deprecated and will be removed in a "
-                "future version. Use the name parameter instead.",
-                FutureWarning,
-            )
-
-        dtype = self.dtype if dtype is None else dtype
-
-        if not np.issubdtype(dtype, np.signedinteger):
-            raise ValueError(f"Expected Signed Integer Type, Got {dtype}")
 
         name = self.name if name is None else name
 
@@ -1140,7 +1107,7 @@ def equals(self, other, **kwargs):
             return False
 
     @_cudf_nvtx_annotate
-    def copy(self, name=None, deep=False, dtype=None, names=None):
+    def copy(self, name=None, deep=False):
         """
         Make a copy of this object.
 
@@ -1151,45 +1118,17 @@ def copy(self, name=None, deep=False, dtype=None, names=None):
         deep : bool, default True
             Make a deep copy of the data.
             With ``deep=False`` the original data is used
-        dtype : numpy dtype, default None
-            Target datatype to cast into, use original dtype when None
-
-            .. deprecated:: 23.02
-
-               The `dtype` parameter is deprecated and will be removed in
-               a future version of cudf. Use the `astype` method instead.
-
-        names : list-like, default False
-            Kept compatibility with MultiIndex. Should not be used.
-
-            .. deprecated:: 23.04
-
-               The parameter `names` is deprecated and will be removed in
-               a future version of cudf. Use the `name` parameter instead.
 
         Returns
         -------
-        New index instance, casted to new dtype
+        New index instance.
         """
-        if dtype is not None:
-            warnings.warn(
-                "parameter dtype is deprecated and will be removed in a "
-                "future version. Use the astype method instead.",
-                FutureWarning,
-            )
-
-        if names is not None:
-            warnings.warn(
-                "parameter names is deprecated and will be removed in a "
-                "future version. Use the name parameter instead.",
-                FutureWarning,
-            )
 
-        dtype = self.dtype if dtype is None else dtype
         name = self.name if name is None else name
 
-        col = self._values.astype(dtype)
-        return _index_from_data({name: col.copy(True) if deep else col})
+        return _index_from_data(
+            {name: self._values.copy(True) if deep else self._values}
+        )
 
     @_cudf_nvtx_annotate
     @doc_apply(_index_astype_docstring)

python/cudf/cudf/core/multiindex.py

@@ -5,7 +5,6 @@
 import itertools
 import numbers
 import pickle
-import warnings
 from collections import abc
 from functools import cached_property
 from numbers import Integral
@@ -318,9 +317,6 @@ def name(self, value):
     def copy(
         self,
         names=None,
-        dtype=None,
-        levels=None,
-        codes=None,
         deep=False,
         name=None,
     ):
@@ -334,36 +330,12 @@ def copy(
         ----------
         names : sequence of objects, optional (default None)
             Names for each of the index levels.
-        dtype : object, optional (default None)
-            MultiIndex dtype, only supports None or object type
-
-            .. deprecated:: 23.02
-
-               The `dtype` parameter is deprecated and will be removed in
-               a future version of cudf. Use the `astype` method instead.
-
-        levels : sequence of arrays, optional (default None)
-            The unique labels for each level. Original values used if None.
-
-            .. deprecated:: 23.02
-
-               The `levels` parameter is deprecated and will be removed in
-               a future version of cudf.
-
-        codes : sequence of arrays, optional (default None)
-            Integers for each level designating which label at each location.
-            Original values used if None.
-
-            .. deprecated:: 23.02
-
-               The `codes` parameter is deprecated and will be removed in
-               a future version of cudf.
-
         deep : Bool (default False)
             If True, `._data`, `._levels`, `._codes` will be copied. Ignored if
             `levels` or `codes` are specified.
         name : object, optional (default None)
-            To keep consistent with `Index.copy`, should not be used.
+            Kept for compatibility with 1-dimensional Index. Should not
+            be used.
 
         Returns
         -------
@@ -401,46 +373,6 @@ def copy(
 
         """
 
-        # TODO: Update message when set_levels is implemented.
-        # https://github.com/rapidsai/cudf/issues/12307
-        if levels is not None:
-            warnings.warn(
-                "parameter levels is deprecated and will be removed in a "
-                "future version.",
-                FutureWarning,
-            )
-
-        # TODO: Update message when set_codes is implemented.
-        # https://github.com/rapidsai/cudf/issues/12308
-        if codes is not None:
-            warnings.warn(
-                "parameter codes is deprecated and will be removed in a "
-                "future version.",
-                FutureWarning,
-            )
-
-        if dtype is not None:
-            warnings.warn(
-                "parameter dtype is deprecated and will be removed in a "
-                "future version. Use the astype method instead.",
-                FutureWarning,
-            )
-
-        dtype = object if dtype is None else dtype
-        if not pd.core.dtypes.common.is_object_dtype(dtype):
-            raise TypeError("Dtype for MultiIndex only supports object type.")
-
-        # ._data needs to be rebuilt
-        if levels is not None or codes is not None:
-            if self._levels is None or self._codes is None:
-                self._compute_levels_and_codes()
-            levels = self._levels if levels is None else levels
-            codes = self._codes if codes is None else codes
-            names = self.names if names is None else names
-
-            mi = MultiIndex(levels=levels, codes=codes, names=names, copy=deep)
-            return mi
-
         mi = MultiIndex._from_data(self._data.copy(deep=deep))
         if self._levels is not None:
             mi._levels = [s.copy(deep) for s in self._levels]

python/cudf/cudf/tests/test_index.py

@@ -25,7 +25,6 @@
     NUMERIC_TYPES,
     OTHER_TYPES,
     SIGNED_INTEGER_TYPES,
-    SIGNED_TYPES,
     UNSIGNED_TYPES,
     _create_pandas_series,
     assert_column_memory_eq,
@@ -307,90 +306,69 @@ def test_set_index_as_property():
 
 
 @pytest.mark.parametrize("name", ["x"])
-@pytest.mark.parametrize("dtype", SIGNED_INTEGER_TYPES)
-def test_index_copy_range(name, dtype, deep=True):
+def test_index_copy_range(name, deep=True):
     cidx = cudf.RangeIndex(1, 5)
     pidx = cidx.to_pandas()
 
-    with pytest.warns(FutureWarning):
-        pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
-    with pytest.warns(FutureWarning):
-        cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
+    pidx_copy = pidx.copy(name=name, deep=deep)
+    cidx_copy = cidx.copy(name=name, deep=deep)
 
     assert_eq(pidx_copy, cidx_copy)
 
 
 @pytest.mark.parametrize("name", ["x"])
-@pytest.mark.parametrize("dtype,", ["datetime64[ns]", "int64"])
-def test_index_copy_datetime(name, dtype, deep=True):
+def test_index_copy_datetime(name, deep=True):
     cidx = cudf.DatetimeIndex(["2001", "2002", "2003"])
     pidx = cidx.to_pandas()
 
-    with pytest.warns(FutureWarning):
-        pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
-    with pytest.warns(FutureWarning):
-        cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
+    pidx_copy = pidx.copy(name=name, deep=deep)
+    cidx_copy = cidx.copy(name=name, deep=deep)
 
     assert_eq(pidx_copy, cidx_copy)
 
 
 @pytest.mark.parametrize("name", ["x"])
-@pytest.mark.parametrize("dtype", ["category", "object"])
-def test_index_copy_string(name, dtype, deep=True):
+def test_index_copy_string(name, deep=True):
     cidx = cudf.StringIndex(["a", "b", "c"])
     pidx = cidx.to_pandas()
 
-    with pytest.warns(FutureWarning):
-        pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
-    with pytest.warns(FutureWarning):
-        cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
+    pidx_copy = pidx.copy(name=name, deep=deep)
+    cidx_copy = cidx.copy(name=name, deep=deep)
 
     assert_eq(pidx_copy, cidx_copy)
 
 
 @pytest.mark.parametrize("name", ["x"])
-@pytest.mark.parametrize(
-    "dtype",
-    NUMERIC_TYPES + ["datetime64[ns]", "timedelta64[ns]"] + OTHER_TYPES,
-)
-def test_index_copy_integer(name, dtype, deep=True):
+def test_index_copy_integer(name, deep=True):
     """Test for NumericIndex Copy Casts"""
     cidx = cudf.Index([1, 2, 3])
     pidx = cidx.to_pandas()
 
-    with pytest.warns(FutureWarning):
-        pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
-    with pytest.warns(FutureWarning):
-        cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
+    pidx_copy = pidx.copy(name=name, deep=deep)
+    cidx_copy = cidx.copy(name=name, deep=deep)
 
     assert_eq(pidx_copy, cidx_copy)
 
 
 @pytest.mark.parametrize("name", ["x"])
-@pytest.mark.parametrize("dtype", SIGNED_TYPES)
-def test_index_copy_float(name, dtype, deep=True):
+def test_index_copy_float(name, deep=True):
     """Test for NumericIndex Copy Casts"""
     cidx = cudf.Index([1.0, 2.0, 3.0])
     pidx = cidx.to_pandas()
 
-    with pytest.warns(FutureWarning):
-        pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
-    with pytest.warns(FutureWarning):
-        cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
+    pidx_copy = pidx.copy(name=name, deep=deep)
+    cidx_copy = cidx.copy(name=name, deep=deep)
 
     assert_eq(pidx_copy, cidx_copy)
 
 
 @pytest.mark.parametrize("name", ["x"])
-@pytest.mark.parametrize("dtype", NUMERIC_TYPES + ["category"])
-def test_index_copy_category(name, dtype, deep=True):
+def test_index_copy_category(name, deep=True):
     cidx = cudf.core.index.CategoricalIndex([1, 2, 3])
     pidx = cidx.to_pandas()
 
-    with pytest.warns(FutureWarning):
-        pidx_copy = pidx.copy(name=name, deep=deep, dtype=dtype)
-    with pytest.warns(FutureWarning):
-        cidx_copy = cidx.copy(name=name, deep=deep, dtype=dtype)
+    pidx_copy = pidx.copy(name=name, deep=deep)
+    cidx_copy = cidx.copy(name=name, deep=deep)
 
     assert_column_memory_ne(cidx._values, cidx_copy._values)
     assert_eq(pidx_copy, cidx_copy)

python/cudf/cudf/tests/test_multiindex.py

@@ -700,15 +700,8 @@ def test_multiindex_equals():
         }
     ],
 )
-@pytest.mark.parametrize(
-    "levels",
-    [[["2000-01-01", "2000-01-02", "2000-01-03"], ["A", "B", "C"]], None],
-)
-@pytest.mark.parametrize(
-    "codes", [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], None]
-)
 @pytest.mark.parametrize("names", [["X", "Y"]])
-def test_multiindex_copy_sem(data, levels, codes, names):
+def test_multiindex_copy_sem(data, names):
     """Test semantic equality for MultiIndex.copy"""
     gdf = cudf.DataFrame(data)
     pdf = gdf.to_pandas()
@@ -717,12 +710,10 @@ def test_multiindex_copy_sem(data, levels, codes, names):
     pdf = pdf.groupby(["Date", "Symbol"], sort=True).mean()
 
     gmi = gdf.index
-    with expect_warning_if(levels is not None or codes is not None):
-        gmi_copy = gmi.copy(levels=levels, codes=codes, names=names)
+    gmi_copy = gmi.copy(names=names)
 
     pmi = pdf.index
-    with expect_warning_if(levels is not None or codes is not None):
-        pmi_copy = pmi.copy(levels=levels, codes=codes, names=names)
+    pmi_copy = pmi.copy(names=names)
 
     for glv, plv in zip(gmi_copy.levels, pmi_copy.levels):
         assert all(glv.values_host == plv.values)