# Copyright 2025 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import pandas as pd
import pytest

import bigframes.pandas as bpd

pytest.importorskip("pytest_snapshot")


def test_and_op(scalar_types_df: bpd.DataFrame, snapshot):
    bf_df = scalar_types_df[["bool_col", "int64_col"]]

    bf_df["int_and_int"] = bf_df["int64_col"] & bf_df["int64_col"]
    bf_df["bool_and_bool"] = bf_df["bool_col"] & bf_df["bool_col"]
    bf_df["bool_and_null"] = bf_df["bool_col"] & pd.NA  # type: ignore
    snapshot.assert_match(bf_df.sql, "out.sql")


def test_or_op(scalar_types_df: bpd.DataFrame, snapshot):
    bf_df = scalar_types_df[["bool_col", "int64_col"]]

    bf_df["int_and_int"] = bf_df["int64_col"] | bf_df["int64_col"]
    bf_df["bool_and_bool"] = bf_df["bool_col"] | bf_df["bool_col"]
    bf_df["bool_and_null"] = bf_df["bool_col"] | pd.NA  # type: ignore
    snapshot.assert_match(bf_df.sql, "out.sql")


def test_xor_op(scalar_types_df: bpd.DataFrame, snapshot):
    bf_df = scalar_types_df[["bool_col", "int64_col"]]

    bf_df["int_and_int"] = bf_df["int64_col"] ^ bf_df["int64_col"]
    bf_df["bool_and_bool"] = bf_df["bool_col"] ^ bf_df["bool_col"]
    bf_df["bool_and_null"] = bf_df["bool_col"] ^ pd.NA  # type: ignore
    snapshot.assert_match(bf_df.sql, "out.sql")
