This section of the script processes an invoice table to remove any lines where both the quantity and the total amount are zero or not provided.
Check for INVOICE_TABLE: It starts by checking if the INVOICE_TABLE key exists in the tables_dict dictionary.
Iterate Over Rows: For each row in the table, the script initializes flags and variables to determine if the TOTAL_AMOUNT and QUANTITY columns exist and to capture their values.
Check Column Names: As it iterates through each column in a row, it looks for columns named TOTAL_AMOUNT and QUANTITY.
If TOTAL_AMOUNT is found, it captures the value. If this value is non-zero, it converts it to a float.
Similarly for QUANTITY, capturing and converting the value if it is non-zero.
Mark Row for Deletion: After checking both columns in a row, if both the total amount and quantity are effectively zero (either by being zero or not existing), the row is marked for deletion by setting row['is_deleted'] to True.
This section calculates the total amount from all lines in an invoice and compares it to the invoice’s reported total to validate their consistency.
Initialize Line Total: Starts by setting a variable lines_total to 0.0 to accumulate the total amount from all lines.
Sum Line Amounts: Iterates over each row in the INVOICE_TABLE, extracting the TOTAL_AMOUNT from each and adding it to lines_total.
Retrieve and Convert Invoice Total: Fetches the total invoice amount using a helper function get_field_value and converts it to a float.
Compare Totals: Finally, it checks if the absolute difference between the calculated line total (lines_total) and the reported invoice total (total_amount) exceeds a threshold of 0.05. If so, it marks the invoice total field as invalid using another helper function set_field_as_invalid, citing a mismatch.
The script effectively ensures data integrity by:
Removing data rows that do not contribute to the invoice’s financial total due to lacking quantities or amounts.
Validating the consistency between the sum of individual line amounts and the overall invoice total, highlighting discrepancies for further action.
This automation helps maintain accurate financial records and can be crucial for systems like ERP that require precise data for accounting and financial reporting.