import csv import pandas as pd import chardet import os import io import zipfile import shutil from datetime import datetime, date from gpc import Data, Header, TransactionCode, CURRENCIES_GPC from utils import extract_order_number, extract_numbers, parse_date from decimal import Decimal, ROUND_HALF_UP from aviza.helpers import write_output_gpc_to_zip 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(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. """ global transactions_df matching_row = transactions_df[transactions_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 extract_and_process_zip_przelewy24_auto(zip_file_path, bank_statement_file_path, output_file, account_number, currency, mapping): global transactions_df transactions_df = load_bank_transactions(bank_statement_file_path) all_transformed_data = [] # Create a temporary folder for extraction base_dir = os.path.dirname(zip_file_path) extract_folder = os.path.join(base_dir, "extracted_temp") os.makedirs(extract_folder, exist_ok=True) # Extract the provided outer zip file with zipfile.ZipFile(zip_file_path, 'r') as zip_ref: zip_ref.extractall(extract_folder) for files in os.walk(extract_folder): for file in files: try: if file.endswith(".csv"): transformed_data = convert_csv_to_gpc_przelewy24_auto(file, account_number, currency, mapping) all_transformed_data.append(transformed_data) except: continue # Clean up the outer extraction folder shutil.rmtree(extract_folder) print(f"Processed and cleaned up: {zip_file_path}") # Return a ZIP archive (in memory) containing all the output CSV files. return write_output_gpc_to_zip(output_file, all_transformed_data) def convert_csv_to_gpc_przelewy24_auto(csv_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: # Skip the first 3 rows for _ in range(3): next(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 total_payout_debet = 0.0 total_payout_credit = 0.0 total_payout_abs = 0.0 first = True clearing_id = "" created_on = None 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 created_on = parse_date(row[mapping['created_on']]) # Convert the value using Decimal instead of float source_str = row[mapping['source_amount']].replace(',', '.') source_amount = Decimal(source_str) # Quantize to 2 decimal places (rounding if necessary) source_amount = source_amount.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP) # Multiply by 100 to get cents (if that's what you need) and convert to integer source_amount_cents = int(source_amount * 100) # Determine transaction type if(direction is None): if source_amount_cents > 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 = "100" + str(transaction_code.value) # Create GPC Data object gpc_data = Data( account=account_number, payer_account=payer_account, no=transaction_id, balance=source_amount_cents, code=transaction_code, variable=int(reference) if reference.isdigit() else 0, constant_symbol=0, bank_code=0, specific_symbol=0, client_name="CG ABCD-EFGH-IJKL" if transaction_code == TransactionCode.CREDIT else "CG refundace", currency=currency_code, date=created_on ) gpc_lines.append(gpc_data.to_string()) total_payout += source_amount_cents total_payout_abs += abs(source_amount_cents) total_payout_debet += abs(source_amount_cents) if transaction_code == TransactionCode.DEBET else 0 total_payout_credit += abs(source_amount_cents) if transaction_code == TransactionCode.CREDIT else 0 # break # 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(clearing_id) # vyuctovani row payout_data = Data( account=account_number, payer_account=95102013900000630206821286, no=int(total_payout), balance=total_payout, code=TransactionCode.DEBET, variable=int(total_payout), # variable=corresponding_transaction['Zpráva pro příjemce'].split(',')[-1].strip(), constant_symbol=0, bank_code=0, specific_symbol=0, client_name="CG vyúčtování", currency="1001", date=created_on ) total_payout_credit += abs(total_payout) total_payout_abs += abs(total_payout) 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='+', turnover_credit=total_payout, turnover_credit_sign='+', transaction_list_no=int(date.today().strftime("%j")), date=datetime.now() ) gpc_lines.insert(0, header.to_string()) file_content = "".join(gpc_lines) print(f"GPC file content successfully created") return file_content.encode("windows-1250") mapping_przelewy_avizo = { 'transaction_id': 'Transaction id', 'reference': 'Title', 'direction': None, 'source_name': 'Payment method name', 'source_amount': 'Amount', 'source_currency': '', 'payer_account': 'Session id', 'created_on': 'Creation date', 'CLEARING_ID': 'CLEARING_ID', 'fees': 'Commission', 'delimiter': ",", 'is_dict_mapping': True, 'use_transaction_id': True, 'payer_number_exists': False, 'use_source_name': False, 'forced_encoding': "UTF-8" } # Example usage: # convert_csv_to_gpc("../Specification clearing 2024-05-10.csv", "avizo_przelewy24_test.gpc", account_number=3498710000999117, currency="EUR", mapping=mapping_przelewy24_avizo) # 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)