TST: base test for ExtensionArray.astype to its own type + copy keyword (#35116)

Co-authored-by: Joris Van den Bossche <[email protected]>

Author: tomaszps

doc/source/whatsnew/v1.2.0.rst

@@ -366,6 +366,7 @@ ExtensionArray
 ^^^^^^^^^^^^^^
 
 - Fixed Bug where :class:`DataFrame` column set to scalar extension type via a dict instantion was considered an object type rather than the extension type (:issue:`35965`)
+- Fixed bug where ``astype()`` with equal dtype and ``copy=False`` would return a new object (:issue:`284881`)
 -
 
 

pandas/core/arrays/base.py

@@ -457,6 +457,11 @@ def astype(self, dtype, copy=True):
         from pandas.core.arrays.string_ import StringDtype
 
         dtype = pandas_dtype(dtype)
+        if is_dtype_equal(dtype, self.dtype):
+            if not copy:
+                return self
+            elif copy:
+                return self.copy()
         if isinstance(dtype, StringDtype):  # allow conversion to StringArrays
             return dtype.construct_array_type()._from_sequence(self, copy=False)
 

pandas/core/arrays/boolean.py

@@ -375,7 +375,10 @@ def astype(self, dtype, copy: bool = True) -> ArrayLike:
 
         if isinstance(dtype, BooleanDtype):
             values, mask = coerce_to_array(self, copy=copy)
-            return BooleanArray(values, mask, copy=False)
+            if not copy:
+                return self
+            else:
+                return BooleanArray(values, mask, copy=False)
         elif isinstance(dtype, StringDtype):
             return dtype.construct_array_type()._from_sequence(self, copy=False)
 

pandas/core/arrays/period.py

@@ -33,6 +33,7 @@
     TD64NS_DTYPE,
     ensure_object,
     is_datetime64_dtype,
+    is_dtype_equal,
     is_float_dtype,
     is_period_dtype,
     pandas_dtype,
@@ -582,7 +583,11 @@ def astype(self, dtype, copy: bool = True):
         # We handle Period[T] -> Period[U]
         # Our parent handles everything else.
         dtype = pandas_dtype(dtype)
-
+        if is_dtype_equal(dtype, self._dtype):
+            if not copy:
+                return self
+            elif copy:
+                return self.copy()
         if is_period_dtype(dtype):
             return self.asfreq(dtype.freq)
         return super().astype(dtype, copy=copy)

pandas/core/arrays/sparse/array.py

@@ -1063,6 +1063,11 @@ def astype(self, dtype=None, copy=True):
         IntIndex
         Indices: array([2, 3], dtype=int32)
         """
+        if is_dtype_equal(dtype, self._dtype):
+            if not copy:
+                return self
+            elif copy:
+                return self.copy()
         dtype = self.dtype.update_dtype(dtype)
         subtype = dtype._subtype_with_str
         # TODO copy=False is broken for astype_nansafe with int -> float, so cannot

pandas/tests/extension/base/casting.py

@@ -1,4 +1,5 @@
 import numpy as np
+import pytest
 
 import pandas as pd
 from pandas.core.internals import ObjectBlock
@@ -56,3 +57,11 @@ def test_astype_empty_dataframe(self, dtype):
         df = pd.DataFrame()
         result = df.astype(dtype)
         self.assert_frame_equal(result, df)
+
+    @pytest.mark.parametrize("copy", [True, False])
+    def test_astype_own_type(self, data, copy):
+        # ensure that astype returns the original object for equal dtype and copy=False
+        # https://github.com/pandas-dev/pandas/issues/28488
+        result = data.astype(data.dtype, copy=copy)
+        assert (result is data) is (not copy)
+        self.assert_extension_array_equal(result, data)

pandas/tests/extension/decimal/array.py

@@ -7,7 +7,7 @@
 import numpy as np
 
 from pandas.core.dtypes.base import ExtensionDtype
-from pandas.core.dtypes.common import pandas_dtype
+from pandas.core.dtypes.common import is_dtype_equal, pandas_dtype
 
 import pandas as pd
 from pandas.api.extensions import no_default, register_extension_dtype
@@ -131,9 +131,12 @@ def copy(self):
         return type(self)(self._data.copy())
 
     def astype(self, dtype, copy=True):
+        if is_dtype_equal(dtype, self._dtype):
+            if not copy:
+                return self
         dtype = pandas_dtype(dtype)
         if isinstance(dtype, type(self.dtype)):
-            return type(self)(self._data, context=dtype.context)
+            return type(self)(self._data, copy=copy, context=dtype.context)
 
         return super().astype(dtype, copy=copy)
 

pandas/tests/extension/test_numpy.py

@@ -177,7 +177,7 @@ def test_take_series(self, data):
 
     def test_loc_iloc_frame_single_dtype(self, data, request):
         npdtype = data.dtype.numpy_dtype
-        if npdtype == object or npdtype == np.float64:
+        if npdtype == object:
             # GH#33125
             mark = pytest.mark.xfail(
                 reason="GH#33125 astype doesn't recognize data.dtype"
@@ -191,14 +191,6 @@ class TestGroupby(BaseNumPyTests, base.BaseGroupbyTests):
     def test_groupby_extension_apply(
         self, data_for_grouping, groupby_apply_op, request
     ):
-        # ValueError: Names should be list-like for a MultiIndex
-        a = "a"
-        is_identity = groupby_apply_op(a) is a
-        if data_for_grouping.dtype.numpy_dtype == np.float64 and is_identity:
-            mark = pytest.mark.xfail(
-                reason="GH#33125 astype doesn't recognize data.dtype"
-            )
-            request.node.add_marker(mark)
         super().test_groupby_extension_apply(data_for_grouping, groupby_apply_op)
 
 
@@ -306,11 +298,7 @@ def test_arith_series_with_array(self, data, all_arithmetic_operators):
 
 
 class TestPrinting(BaseNumPyTests, base.BasePrintingTests):
-    @pytest.mark.xfail(
-        reason="GH#33125 PandasArray.astype does not recognize PandasDtype"
-    )
-    def test_series_repr(self, data):
-        super().test_series_repr(data)
+    pass
 
 
 @skip_nested