Source code for pain001.db.validate_db_data
# Copyright (C) 2023-2026 Pain001. All rights reserved.
#
# 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.
"""Validate SQLite payment data against required-field rules."""
import logging
from datetime import datetime
from typing import Any
from pain001.csv.validate_csv_data import _validate_field_type
logger = logging.getLogger(__name__)
# Core required fields with expected types — kept in type parity with
# the CSV validator so a row passes or fails identically regardless of
# the data source it was loaded from.
REQUIRED_COLUMNS: dict[str, type] = {
"id": int,
"date": datetime,
"nb_of_txs": int,
"initiator_name": str,
"payment_information_id": str,
"payment_method": str,
"debtor_name": str,
"debtor_account_IBAN": str,
"payment_amount": float,
"currency": str,
"creditor_name": str,
"creditor_account_IBAN": str,
}
[docs]
def validate_db_data(data: list[dict[str, Any]]) -> bool:
"""
Validate the data from a database.
Args:
data: The rows to validate, one dictionary per row.
Returns:
bool: True if the data is valid, False otherwise.
"""
for row in data:
for column, data_type in REQUIRED_COLUMNS.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