seperate file

pandas/tests/extension/numpy_/conftest.py

@@ -1,55 +1,38 @@
+import numpy as np
 import pytest
 
-# A set of Base EA tests that are know to not work for
-# the object-dtype PandasArray holding nested data.
-skips = {
-    'TestCasting.test_astype_str',
-    'TestConstructors.test_array_from_scalars',
-    # tuple isn't instance of np.object
-    'TestGetitem.test_getitem_scalar',
-    # Can't pass tuples to _from_sequence
-    'TestGetitem.test_take_series',
-    # np.array shape inference
-    'TestInterface.test_array_interface',
-    # Can't construct expected.
-    'TestMethods.test_unique',
-    'TestMethods.test_combine_add',
-    'TestMethods.test_shift_fill_value',
-    'TestMethods.test_where_series',
-    'TestMethods.test_repeat',
-    # Can't hash ndarray[tuple]
-    'TestMethods.test_hash_pandas_object_works',
-    # Can't construct expected.
-    'TestReshaping.test_merge',
-    'TestReshaping.test_merge_on_extension_array',
-    'TestReshaping.test_merge_on_extension_array_duplicates',
-
-    # ndarray setting
-    'TestSetitem.test_setitem_scalar_series',
-    'TestSetitem.test_setitem_sequence',
-    'TestSetitem.test_setitem_sequence_mismatched_length_raises',
-    'TestSetitem.test_setitem_sequence_broadcasts',
-    'TestSetitem.test_setitem_sequence_broadcasts',
-    'TestSetitem.test_setitem_loc_scalar_mixed',
-    'TestSetitem.test_setitem_iloc_scalar_mixed',
-    'TestSetitem.test_setitem_loc_scalar_multiple_homogoneous',
-    'TestSetitem.test_setitem_iloc_scalar_multiple_homogoneous',
-    'TestSetitem.test_setitem_mask_broadcast',
-    'TestSetitem.test_setitem_scalar_key_sequence_raise',
-
-    # parsing differs.
-    'TestParsing.test_EA_types',
-}
-
-
-def pytest_collection_modifyitems(config, items):
-    skip = pytest.mark.skip(reason="Skipping for nested data.")
-    for item in items:
-        # TODO: See if pytest has a better way to resolve the *value*
-        # supplied to a fixture. Right now .keywords gets things
-        # like 'object' or 'data-object'.
-        parts = item.name.split("[")
-        qualname = item.parent.obj.__class__.__name__ + '.' + item.obj.__name__
-        if (len(parts) > 1 and 'object' in item.name.split('[')[1]
-                and qualname in skips):
-            item.add_marker(skip)
+from pandas.core.arrays.numpy_ import PandasArray
+
+
+@pytest.fixture
+def allow_in_pandas(monkeypatch):
+    """
+    A monkeypatch to tells pandas to let us in.
+
+    By default, passing a PandasArray to an index / series / frame
+    constructor will unbox that PandasArray to an ndarray, and treat
+    it as a non-EA column. We don't want people using EAs without
+    reason.
+
+    The mechanism for this is a check against ABCPandasArray
+    in each constructor.
+
+    But, for testing, we need to allow them in pandas. So we patch
+    the _typ of PandasArray, so that we evade the ABCPandasArray
+    check.
+    """
+    with monkeypatch.context() as m:
+        m.setattr(PandasArray, '_typ', 'extension')
+        yield
+
+
+@pytest.fixture
+def na_value():
+    return np.nan
+
+
+@pytest.fixture
+def na_cmp():
+    def cmp(a, b):
+        return np.isnan(a) and np.isnan(b)
+    return cmp

pandas/tests/extension/numpy_/test_numpy.py

@@ -9,37 +9,13 @@
 from .. import base
 
 
-@pytest.fixture(params=['float', 'object'])
-def dtype(request):
-    return PandasDtype(np.dtype(request.param))
-
-
 @pytest.fixture
-def allow_in_pandas(monkeypatch):
-    """
-    A monkeypatch to tells pandas to let us in.
-
-    By default, passing a PandasArray to an index / series / frame
-    constructor will unbox that PandasArray to an ndarray, and treat
-    it as a non-EA column. We don't want people using EAs without
-    reason.
-
-    The mechanism for this is a check against ABCPandasArray
-    in each constructor.
-
-    But, for testing, we need to allow them in pandas. So we patch
-    the _typ of PandasArray, so that we evade the ABCPandasArray
-    check.
-    """
-    with monkeypatch.context() as m:
-        m.setattr(PandasArray, '_typ', 'extension')
-        yield
+def dtype():
+    return PandasDtype(np.dtype('float'))
 
 
 @pytest.fixture
 def data(allow_in_pandas, dtype):
-    if dtype.numpy_dtype == 'object':
-        return pd.Series([(i,) for i in range(100)]).array
     return PandasArray(np.arange(1, 101, dtype=dtype._dtype))
 
 
@@ -48,18 +24,6 @@ def data_missing(allow_in_pandas):
     return PandasArray(np.array([np.nan, 1.0]))
 
 
-@pytest.fixture
-def na_value():
-    return np.nan
-
-
-@pytest.fixture
-def na_cmp():
-    def cmp(a, b):
-        return np.isnan(a) and np.isnan(b)
-    return cmp
-
-
 @pytest.fixture
 def data_for_sorting(allow_in_pandas):
     """Length-3 array with a known sort order.
@@ -152,19 +116,6 @@ class TestArithmetics(BaseNumPyTests, base.BaseArithmeticOpsTests):
     frame_scalar_exc = None
     series_array_exc = None
 
-    def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
-        if s.dtype == 'object':
-            raise pytest.skip("Skipping for object dtype.")
-        super(TestArithmetics, self)._check_op(s, op, other, op_name, exc)
-
-    def _check_divmod_op(self, s, op, other, exc=Exception):
-        if isinstance(s, pd.Series) and s.dtype == 'object':
-            raise pytest.skip("Skipping for object dtype.")
-        elif isinstance(other, pd.Series) and other.dtype == 'object':
-            raise pytest.skip("Skipping for object dtype.")
-
-        super(TestArithmetics, self)._check_divmod_op(s, op, other, exc)
-
     def test_divmod_series_array(self, data):
         s = pd.Series(data)
         self._check_divmod_op(s, divmod, data, exc=None)
@@ -201,24 +152,17 @@ class TestPrinting(BaseNumPyTests, base.BasePrintingTests):
 class TestNumericReduce(BaseNumPyTests, base.BaseNumericReduceTests):
 
     def check_reduce(self, s, op_name, skipna):
-        if s.dtype == 'object':
-            raise pytest.skip("Skipping for object dtype.")
         result = getattr(s, op_name)(skipna=skipna)
         # avoid coercing int -> float. Just cast to the actual numpy type.
         expected = getattr(s.astype(s.dtype._dtype), op_name)(skipna=skipna)
         tm.assert_almost_equal(result, expected)
 
 
 class TestBooleanReduce(BaseNumPyTests, base.BaseBooleanReduceTests):
-
-    def check_reduce(self, s, op_name, skipna):
-        if s.dtype == 'object':
-            raise pytest.skip("Skipping for object dtype.")
-
-        super(TestBooleanReduce, self).check_reduce(s, op_name, skipna)
+    pass
 
 
-class TestMissing(BaseNumPyTests, base.BaseMissingTests):
+class TestMising(BaseNumPyTests, base.BaseMissingTests):
     pass