gpc-generator/paynl_aviza.py

import csv
import pandas as pd
import chardet
from datetime import datetime
from gpc import Data, Header, TransactionCode, CURRENCIES_GPC
from utils import extract_order_number, extract_numbers, parse_date


def load_bank_transactions(csv_file):
    """
    Loads the bank transactions CSV file into a DataFrame and returns it.

    :param csv_file: Path to the bank transactions CSV file.
    :return: A pandas DataFrame containing the transactions.
    """
    df = pd.read_csv(csv_file, delimiter=';', dtype=str)

    # Ensure the required column exists
    if 'Zpráva pro příjemce' not in df.columns:
        raise ValueError("The CSV file does not contain the required column 'Zpráva pro příjemce'.")

    return df

def search_bank_transaction(df, search_string):
    """
    Searches for a given string in the 'Zpráva pro příjemce' column of the loaded DataFrame.

    :param df: Pandas DataFrame containing bank transactions.
    :param search_string: String to search for in the 'Zpráva pro příjemce' column.
    :return: The first matching row as a dictionary or None if not found.
    """
    matching_row = df[df['Zpráva pro příjemce'].str.contains(search_string, na=False, case=False)]

    return matching_row.iloc[0].to_dict() if not matching_row.empty else None


def convert_csv_to_gpc(csv_file_path, gpc_file_path, account_number, currency, mapping):
    gpc_lines = []
    global transactions_df


    if mapping['forced_encoding'] is not None:
        detected_encoding = mapping['forced_encoding']
        print(f"Forced encoding: {detected_encoding}")
    else:
        with open(csv_file_path, 'rb') as f:
            rawdata = f.read(1024)  # Read a small part of the file
            result = chardet.detect(rawdata)
            detected_encoding = result['encoding']
            print(f"Detected encoding: {detected_encoding}")


    with open(csv_file_path, mode='r', encoding=detected_encoding) as csv_file:
        reader = csv.DictReader(csv_file, delimiter=mapping['delimiter']) if mapping['is_dict_mapping'] else csv.reader(csv_file, delimiter=mapping['delimiter'])

        if not mapping['is_dict_mapping']:
            next(reader)

        total_payout = 0.0
        first = True
        clearing_id = ""
        for row in reader:

            if first:
                clearing_id = row[mapping['CLEARING_ID']]
                first = False
            reference = extract_order_number(row[mapping['reference']])
            transaction_id = extract_numbers(row[mapping['transaction_id']]) if mapping['use_transaction_id'] else reference
            direction = row[mapping['direction']].lower() if mapping['direction'] is not None else None
            source_name = row[mapping['source_name']].replace("Nazwa nadawcy: ", "")[:20].ljust(20) if mapping['use_source_name'] else ""
            payer_account = extract_numbers(row[mapping['payer_account']].replace("Rachunek nadawcy: ", "").replace(" ", ""))[:16].ljust(16) if mapping['payer_number_exists'] else 0
            if payer_account != 0:
                if payer_account.strip() == "":
                    payer_account = 0
            source_amount = float(row[mapping['source_amount']].replace(',', '.')) * 100  # Convert to cents
            created_on = parse_date(row[mapping['created_on']])

            # Determine transaction type
            if(direction is None):
                if source_amount > 0:
                    transaction_code = TransactionCode.CREDIT
                else:
                    transaction_code = TransactionCode.DEBET
            else:
                if direction == "out":
                    transaction_code = TransactionCode.DEBET
                else:
                    transaction_code = TransactionCode.CREDIT

            # Convert currency
            currency_code = CURRENCIES_GPC.get("CZK", "0000")

            # Create GPC Data object
            gpc_data = Data(
                account=account_number,
                payer_account=payer_account,
                no=transaction_id,
                balance=source_amount,
                code=transaction_code,
                variable=int(reference) if reference.isdigit() else 0,
                constant_symbol=0,
                bank_code=0,
                specific_symbol=0,
                client_name=source_name,
                currency=currency_code,
                date=created_on
            )

            gpc_lines.append(gpc_data.to_string())
            total_payout += source_amount

    # add fees
    # fees_data = Data(
    #     account=account_number,
    #     payer_account=0,
    #     no=0,
    #     balance=total_fees,
    #     code=transaction_code,
    #     variable=0,
    #     constant_symbol=0,
    #     bank_code=0,
    #     specific_symbol=0,
    #     client_name="",
    #     currency=CURRENCIES_GPC.get("CZK", "0000"),
    #     date=created_on
    # )
    #
    # gpc_lines.append(gpc_data.to_string())

    corresponding_transaction = search_bank_transaction(transactions_df, clearing_id)

    # vyuctovani row
    payout_data = Data(
        account=account_number,
        payer_account=0,
        no=0,
        balance=total_payout,
        code=TransactionCode.DEBET,
        variable=666111222,
        # variable=corresponding_transaction['Zpráva pro příjemce'].split(',')[-1].strip(),
        constant_symbol=0,
        bank_code=0,
        specific_symbol=0,
        client_name="",
        currency=CURRENCIES_GPC.get("CZK", "0000"),
        date=parse_date(corresponding_transaction['Datum'])
    )

    gpc_lines.append(payout_data.to_string())

    # Create and add the header
    header = Header(
        account=account_number,
        account_name=currency.ljust(20),
        old_date=datetime.strptime("01-03-20", "%d-%m-%y"),
        old_balance=0,
        old_sign='+',
        new_balance=0,
        new_sign='+',
        turnover_debet=total_payout,
        turnover_debet_sign='0',
        turnover_credit=total_payout,
        turnover_credit_sign='0',
        transaction_list_no=3,
        date=datetime.now()
    )
    gpc_lines.insert(0, header.to_string())

    with open(gpc_file_path, mode='w', encoding='utf-8') as gpc_file:
        gpc_file.writelines(gpc_lines)

    print(f"GPC file successfully created: {gpc_file_path}")

# Example mappings
mapping_paynl = {
    'transaction_id': 'PAYMENT_SESSION_ID',
    'reference': 'EXTRA_1',
    'direction': None,
    'source_name': 'CONSUMER_NAME',
    'source_amount': 'TURNOVER_TOTAL',
    'source_currency': '',
    'payer_account': 'PAYMENT_SESSION_ID',
    'created_on': 'TRANSACTION_DATE',
    'CLEARING_ID': 'CLEARING_ID',
    'fees': 'COSTS',
    'delimiter': ";",
    'is_dict_mapping': True,
    'use_transaction_id': True,
    'payer_number_exists': False,
    'use_source_name': False,
    'forced_encoding': None
}


transactions_df = load_bank_transactions("bank_statement.csv")
# Example usage:
convert_csv_to_gpc("Specification clearing 2024-05-10.csv", "avizo_paynl_test.gpc", account_number=2801379531, currency="EUR", mapping=mapping_paynl)
# convert_csv_to_gpc("pko_input.csv", "pko_output.gpc", account_number=95102013900000630206821286, currency="PLN", mapping=mapping_pko)
# convert_csv_to_gpc("sparkasse_input.csv", "sparkasse_output.gpc", account_number=95850503000221267034, currency="EUR", mapping=mapping_sparkasse)