import operator

import numpy as np
import pytest

import pandas as pd
import pandas._testing as tm


@pytest.fixture
def data():
    return pd.array(
        [True, False] * 4 + [np.nan] + [True, False] * 44 + [np.nan] + [True, False],
        dtype="boolean",
    )


@pytest.fixture
def left_array():
    return pd.array([True] * 3 + [False] * 3 + [None] * 3, dtype="boolean")


@pytest.fixture
def right_array():
    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):
    with pytest.raises(TypeError):
        # numpy points to ^ operator or logical_xor function instead
        left_array - right_array


def test_div(left_array, right_array):
    # for now division gives a float numpy array
    result = left_array / right_array
    expected = np.array(
        [1.0, np.inf, np.nan, 0.0, np.nan, np.nan, np.nan, np.nan, np.nan],
        dtype="float64",
    )
    tm.assert_numpy_array_equal(result, expected)


@pytest.mark.parametrize(
    "opname",
    [
        "floordiv",
        "mod",
        pytest.param(
            "pow", marks=pytest.mark.xfail(reason="TODO follow int8 behaviour? GH34686")
        ),
    ],
)
def test_op_int8(left_array, right_array, opname):
    op = getattr(operator, opname)
    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):
    # invalid ops

    op = all_arithmetic_operators
    s = pd.Series(data)
    ops = getattr(s, op)

    # invalid scalars
    with pytest.raises(TypeError):
        ops("foo")
    with pytest.raises(TypeError):
        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
        with pytest.raises(TypeError):
            ops(pd.Series("foo", index=s.index))
