import numpy as np from pandas.core.dtypes.common import is_extension_array_dtype from pandas.core.dtypes.dtypes import ExtensionDtype import pandas as pd import pandas._testing as tm from .base import BaseExtensionTests class BaseInterfaceTests(BaseExtensionTests): """Tests that the basic interface is satisfied.""" # ------------------------------------------------------------------------ # Interface # ------------------------------------------------------------------------ def test_len(self, data): assert len(data) == 100 def test_ndim(self, data): assert data.ndim == 1 def test_can_hold_na_valid(self, data): # GH-20761 assert data._can_hold_na is True def test_memory_usage(self, data): s = pd.Series(data) result = s.memory_usage(index=False) assert result == s.nbytes def test_array_interface(self, data): result = np.array(data) assert result[0] == data[0] result = np.array(data, dtype=object) expected = np.array(list(data), dtype=object) tm.assert_numpy_array_equal(result, expected) def test_is_extension_array_dtype(self, data): assert is_extension_array_dtype(data) assert is_extension_array_dtype(data.dtype) assert is_extension_array_dtype(pd.Series(data)) assert isinstance(data.dtype, ExtensionDtype) def test_no_values_attribute(self, data): # GH-20735: EA's with .values attribute give problems with internal # code, disallowing this for now until solved assert not hasattr(data, "values") assert not hasattr(data, "_values") def test_is_numeric_honored(self, data): result = pd.Series(data) assert result._data.blocks[0].is_numeric is data.dtype._is_numeric def test_isna_extension_array(self, data_missing): # If your `isna` returns an ExtensionArray, you must also implement # _reduce. At the *very* least, you must implement any and all na = data_missing.isna() if is_extension_array_dtype(na): assert na._reduce("any") assert na.any() assert not na._reduce("all") assert not na.all() assert na.dtype._is_boolean def test_copy(self, data): # GH#27083 removing deep keyword from EA.copy assert data[0] != data[1] result = data.copy() data[1] = data[0] assert result[1] != result[0] def test_view(self, data): # view with no dtype should return a shallow copy, *not* the same # object assert data[1] != data[0] result = data.view() assert result is not data assert type(result) == type(data) result[1] = result[0] assert data[1] == data[0] # check specifically that the `dtype` kwarg is accepted data.view(dtype=None)