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# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you 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 io
from typing import Any

import pandas as pd

from superset.utils.core import GenericDataType


def df_to_excel(df: pd.DataFrame, **kwargs: Any) -> Any:
    output = io.BytesIO()

    # pylint: disable=abstract-class-instantiated
    with pd.ExcelWriter(output, engine="xlsxwriter") as writer:
        df.to_excel(writer, **kwargs)

    return output.getvalue()


def apply_column_types(
    df: pd.DataFrame, column_types: list[GenericDataType]
) -> pd.DataFrame:
    for column, column_type in zip(df.columns, column_types):
        if column_type == GenericDataType.NUMERIC:
            try:
                df[column] = pd.to_numeric(df[column])
            except ValueError:
                df[column] = df[column].astype(str)
        elif pd.api.types.is_datetime64tz_dtype(df[column]):
            # timezones are not supported
            df[column] = df[column].astype(str)
    return df