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.venv/Lib/site-packages/pandas/tests/extension/test_integer.py

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+"""
+This file contains a minimal set of tests for compliance with the extension
+array interface test suite, and should contain no other tests.
+The test suite for the full functionality of the array is located in
+`pandas/tests/arrays/`.
+
+The tests in this file are inherited from the BaseExtensionTests, and only
+minimal tweaks should be applied to get the tests passing (by overwriting a
+parent method).
+
+Additional tests should either be added to one of the BaseExtensionTests
+classes (if they are relevant for the extension interface for all dtypes), or
+be added to the array-specific tests in `pandas/tests/arrays/`.
+
+"""
+import numpy as np
+import pytest
+
+import pandas as pd
+import pandas._testing as tm
+from pandas.api.types import (
+    is_extension_array_dtype,
+    is_integer_dtype,
+)
+from pandas.core.arrays.integer import (
+    Int8Dtype,
+    Int16Dtype,
+    Int32Dtype,
+    Int64Dtype,
+    UInt8Dtype,
+    UInt16Dtype,
+    UInt32Dtype,
+    UInt64Dtype,
+)
+from pandas.tests.extension import base
+
+
+def make_data():
+    return list(range(1, 9)) + [pd.NA] + list(range(10, 98)) + [pd.NA] + [99, 100]
+
+
+@pytest.fixture(
+    params=[
+        Int8Dtype,
+        Int16Dtype,
+        Int32Dtype,
+        Int64Dtype,
+        UInt8Dtype,
+        UInt16Dtype,
+        UInt32Dtype,
+        UInt64Dtype,
+    ]
+)
+def dtype(request):
+    return request.param()
+
+
+@pytest.fixture
+def data(dtype):
+    return pd.array(make_data(), dtype=dtype)
+
+
+@pytest.fixture
+def data_for_twos(dtype):
+    return pd.array(np.ones(100) * 2, dtype=dtype)
+
+
+@pytest.fixture
+def data_missing(dtype):
+    return pd.array([pd.NA, 1], dtype=dtype)
+
+
+@pytest.fixture
+def data_for_sorting(dtype):
+    return pd.array([1, 2, 0], dtype=dtype)
+
+
+@pytest.fixture
+def data_missing_for_sorting(dtype):
+    return pd.array([1, pd.NA, 0], dtype=dtype)
+
+
+@pytest.fixture
+def na_cmp():
+    # we are pd.NA
+    return lambda x, y: x is pd.NA and y is pd.NA
+
+
+@pytest.fixture
+def na_value():
+    return pd.NA
+
+
+@pytest.fixture
+def data_for_grouping(dtype):
+    b = 1
+    a = 0
+    c = 2
+    na = pd.NA
+    return pd.array([b, b, na, na, a, a, b, c], dtype=dtype)
+
+
+class TestDtype(base.BaseDtypeTests):
+    pass
+
+
+class TestArithmeticOps(base.BaseArithmeticOpsTests):
+    def check_opname(self, s, op_name, other, exc=None):
+        # overwriting to indicate ops don't raise an error
+        super().check_opname(s, op_name, other, exc=None)
+
+    def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
+        if exc is None:
+            sdtype = tm.get_dtype(s)
+
+            if (
+                hasattr(other, "dtype")
+                and not is_extension_array_dtype(other.dtype)
+                and is_integer_dtype(other.dtype)
+                and sdtype.is_unsigned_integer
+            ):
+                # TODO: comment below is inaccurate; other can be int8, int16, ...
+                #  and the trouble is that e.g. if s is UInt8 and other is int8,
+                #  then result is UInt16
+                # other is np.int64 and would therefore always result in
+                # upcasting, so keeping other as same numpy_dtype
+                other = other.astype(sdtype.numpy_dtype)
+
+            result = op(s, other)
+            expected = self._combine(s, other, op)
+
+            if op_name in ("__rtruediv__", "__truediv__", "__div__"):
+                expected = expected.fillna(np.nan).astype("Float64")
+            else:
+                # combine method result in 'biggest' (int64) dtype
+                expected = expected.astype(sdtype)
+
+            self.assert_equal(result, expected)
+        else:
+            with pytest.raises(exc):
+                op(s, other)
+
+    def _check_divmod_op(self, s, op, other, exc=None):
+        super()._check_divmod_op(s, op, other, None)
+
+
+class TestComparisonOps(base.BaseComparisonOpsTests):
+    def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
+        if exc is None:
+            result = op(s, other)
+            # Override to do the astype to boolean
+            expected = s.combine(other, op).astype("boolean")
+            self.assert_series_equal(result, expected)
+        else:
+            with pytest.raises(exc):
+                op(s, other)
+
+    def check_opname(self, s, op_name, other, exc=None):
+        super().check_opname(s, op_name, other, exc=None)
+
+    def _compare_other(self, s, data, op, other):
+        op_name = f"__{op.__name__}__"
+        self.check_opname(s, op_name, other)
+
+
+class TestInterface(base.BaseInterfaceTests):
+    pass
+
+
+class TestConstructors(base.BaseConstructorsTests):
+    pass
+
+
+class TestReshaping(base.BaseReshapingTests):
+    pass
+
+    # for test_concat_mixed_dtypes test
+    # concat of an Integer and Int coerces to object dtype
+    # TODO(jreback) once integrated this would
+
+
+class TestGetitem(base.BaseGetitemTests):
+    pass
+
+
+class TestSetitem(base.BaseSetitemTests):
+    pass
+
+
+class TestIndex(base.BaseIndexTests):
+    pass
+
+
+class TestMissing(base.BaseMissingTests):
+    pass
+
+
+class TestMethods(base.BaseMethodsTests):
+    @pytest.mark.parametrize("dropna", [True, False])
+    def test_value_counts(self, all_data, dropna):
+        all_data = all_data[:10]
+        if dropna:
+            other = np.array(all_data[~all_data.isna()])
+        else:
+            other = all_data
+
+        result = pd.Series(all_data).value_counts(dropna=dropna).sort_index()
+        expected = pd.Series(other).value_counts(dropna=dropna).sort_index()
+        expected = expected.astype("Int64")
+        expected.index = expected.index.astype(all_data.dtype)
+
+        self.assert_series_equal(result, expected)
+
+    @pytest.mark.xfail(reason="uses nullable integer")
+    def test_value_counts_with_normalize(self, data):
+        super().test_value_counts_with_normalize(data)
+
+
+class TestCasting(base.BaseCastingTests):
+    pass
+
+
+class TestGroupby(base.BaseGroupbyTests):
+    pass
+
+
+class TestNumericReduce(base.BaseNumericReduceTests):
+    def check_reduce(self, s, op_name, skipna):
+        # overwrite to ensure pd.NA is tested instead of np.nan
+        # https://github.com/pandas-dev/pandas/issues/30958
+        result = getattr(s, op_name)(skipna=skipna)
+        if not skipna and s.isna().any():
+            expected = pd.NA
+        else:
+            expected = getattr(s.dropna().astype("int64"), op_name)(skipna=skipna)
+        tm.assert_almost_equal(result, expected)
+
+
+@pytest.mark.skip(reason="Tested in tests/reductions/test_reductions.py")
+class TestBooleanReduce(base.BaseBooleanReduceTests):
+    pass
+
+
+class TestPrinting(base.BasePrintingTests):
+    pass
+
+
+class TestParsing(base.BaseParsingTests):
+    pass
+
+
+class Test2DCompat(base.Dim2CompatTests):
+    pass