import operator import numpy as np import pytest import pandas as pd import pandas._testing as tm @pytest.fixture def data(): """Fixture returning boolean array with valid and missing values.""" return pd.array( [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False], dtype="boolean", ) @pytest.fixture def left_array(): """Fixture returning boolean array with valid and missing values.""" return pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean") @pytest.fixture def right_array(): """Fixture returning boolean array with valid and missing values.""" return pd.array([True, False, None] * 3, dtype="boolean") # Basic test for the arithmetic array ops # ----------------------------------------------------------------------------- @pytest.mark.parametrize( "opname, exp", [ ("add", [True, True, None, True, False, None, None, None, None]), ("mul", [True, False, None, False, False, None, None, None, None]), ], ids=["add", "mul"], ) def test_add_mul(left_array, right_array, opname, exp): op = getattr(operator, opname) result = op(left_array, right_array) expected = pd.array(exp, dtype="boolean") tm.assert_extension_array_equal(result, expected) def test_sub(left_array, right_array): msg = ( r"numpy boolean subtract, the `-` operator, is (?:deprecated|not supported), " r"use the bitwise_xor, the `\^` operator, or the logical_xor function instead\." ) with pytest.raises(TypeError, match=msg): left_array - right_array def test_div(left_array, right_array): msg = "operator '.*' not implemented for bool dtypes" with pytest.raises(NotImplementedError, match=msg): # check that we are matching the non-masked Series behavior pd.Series(left_array._data) / pd.Series(right_array._data) with pytest.raises(NotImplementedError, match=msg): left_array / right_array @pytest.mark.parametrize( "opname", [ "floordiv", "mod", "pow", ], ) def test_op_int8(left_array, right_array, opname): op = getattr(operator, opname) if opname != "mod": msg = "operator '.*' not implemented for bool dtypes" with pytest.raises(NotImplementedError, match=msg): result = op(left_array, right_array) return result = op(left_array, right_array) expected = op(left_array.astype("Int8"), right_array.astype("Int8")) tm.assert_extension_array_equal(result, expected) # Test generic characteristics / errors # ----------------------------------------------------------------------------- def test_error_invalid_values(data, all_arithmetic_operators, using_infer_string): # invalid ops if using_infer_string: import pyarrow as pa err = (TypeError, pa.lib.ArrowNotImplementedError, NotImplementedError) else: err = TypeError op = all_arithmetic_operators s = pd.Series(data) ops = getattr(s, op) # invalid scalars msg = ( "did not contain a loop with signature matching types|" "BooleanArray cannot perform the operation|" "not supported for the input types, and the inputs could not be safely coerced " "to any supported types according to the casting rule ''safe''" ) with pytest.raises(TypeError, match=msg): ops("foo") msg = "|".join( [ r"unsupported operand type\(s\) for", "Concatenation operation is not implemented for NumPy arrays", "has no kernel", ] ) with pytest.raises(err, match=msg): ops(pd.Timestamp("20180101")) # invalid array-likes if op not in ("__mul__", "__rmul__"): # TODO(extension) numpy's mul with object array sees booleans as numbers msg = "|".join( [ r"unsupported operand type\(s\) for", "can only concatenate str", "not all arguments converted during string formatting", "has no kernel", "not implemented", ] ) with pytest.raises(err, match=msg): ops(pd.Series("foo", index=s.index))