Source code for pain001.db.validate_db_data

# Copyright (C) 2023-2026 Pain001. All rights reserved.
# SPDX-License-Identifier: Apache-2.0 OR MIT
#
# Licensed under either of the Apache License, Version 2.0 or the MIT
# License, at your option. You may not use this file except in
# compliance with one of those licences. Copies are provided in
# LICENSE-APACHE and LICENSE-MIT.
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the Licences is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
# implied. See the applicable Licence for the specific language
# governing permissions and limitations.

"""Validate SQLite payment data against required-field rules."""

import logging
from typing import Any

from pain001.csv.validate_csv_data import _validate_field_type
from pain001.schemas.required_columns import required_columns

logger = logging.getLogger(__name__)




def validate_db_data(
    data: list[dict[str, Any]], message_type: str | None = None
) -> bool:
    """
    Validate the data from a database.

    The columns and types come from :func:`required_columns`, the same
    contract the CSV validator enforces.

    Args:
        data: The rows to validate, one dictionary per row.
        message_type: The target message type, e.g. ``pain.001.001.09``,
            or ``None`` when it is not yet known.

    Returns:
        bool: True if the data is valid, False otherwise.
    """
    required = required_columns(message_type)
    for row in data:
        for column, data_type in required.items():
            if column not in row or row[column] is None or row[column] == "":
                logger.error(
                    "Error: Missing value for required column '%s' in row: %s",
                    column,
                    row,
                )
                return False
            value = str(row[column]).strip()
            if not _validate_field_type(value, data_type):
                logger.error(
                    "Error: Invalid %s value for column '%s' in row: %s",
                    data_type.__name__,
                    column,
                    row,
                )
                return False
    return True