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superset/dataframe.py

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# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# 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.
"""Superset utilities for pandas.DataFrame."""

import logging
from typing import Any

import pandas as pd

from superset.utils.core import JS_MAX_INTEGER

logger = logging.getLogger(__name__)


def _convert_big_integers(val: Any) -> Any:
    """
    Cast integers larger than ``JS_MAX_INTEGER`` to strings.

    :param val: the value to process
    :returns: the same value but recast as a string if it was an integer over
        ``JS_MAX_INTEGER``
    """
    return str(val) if isinstance(val, int) and abs(val) > JS_MAX_INTEGER else val


def df_to_records(dframe: pd.DataFrame) -> list[dict[str, Any]]:
    """
    Convert a DataFrame to a set of records.

    :param dframe: the DataFrame to convert
    :returns: a list of dictionaries reflecting each single row of the DataFrame
    """
    if not dframe.columns.is_unique:
        logger.warning(
            "DataFrame columns are not unique, some columns will be omitted."
        )
    records = dframe.to_dict(orient="records")

    for record in records:
        for key in record:
            record[key] = _convert_big_integers(record[key])

    return records