139 lines
5.9 KiB
Python
139 lines
5.9 KiB
Python
import pandas as pd
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import csv
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import sys
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import os
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import io
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import zipfile
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import shutil
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from datetime import datetime
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from aviza.helpers import write_output_csv_to_zip
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transactions_df = None
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def load_bank_transactions(csv_file):
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"""
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Loads the bank transactions CSV file into a DataFrame and returns it.
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:param csv_file: Path to the bank transactions CSV file.
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:return: A pandas DataFrame containing the transactions.
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"""
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df = pd.read_csv(csv_file, delimiter=';', dtype=str)
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# Ensure the required column exists
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if 'Zpráva pro příjemce' not in df.columns:
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raise ValueError("The CSV file does not contain the required column 'Zpráva pro příjemce'.")
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return df
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def search_bank_transaction(search_string):
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global transactions_df
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"""
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Searches for a given string in the 'Zpráva pro příjemce' column of the loaded DataFrame.
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:param df: Pandas DataFrame containing bank transactions.
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:param search_string: String to search for in the 'Zpráva pro příjemce' column.
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:return: The first matching row as a dictionary or None if not found.
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"""
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matching_row = transactions_df[transactions_df['Zpráva pro příjemce'].str.contains(search_string, na=False, case=False)]
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return matching_row.iloc[0].to_dict() if not matching_row.empty else None
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def extract_and_process_zip_paynl_single(zip_file_path, bank_statement_file_path, output_file):
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global transactions_df
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transactions_df = load_bank_transactions(bank_statement_file_path)
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all_transformed_data = []
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# Create a temporary folder for extraction
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base_dir = os.path.dirname(zip_file_path)
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extract_folder = os.path.join(base_dir, "extracted_temp")
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os.makedirs(extract_folder, exist_ok=True)
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# Extract the provided outer zip file
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with zipfile.ZipFile(zip_file_path, 'r') as zip_ref:
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zip_ref.extractall(extract_folder)
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# Check if a top-level "Transactions" folder exists
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transactions_folder = os.path.join(extract_folder, "Transactions")
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if os.path.exists(transactions_folder):
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# Look for a CSV file inside the Transactions folder
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csv_filename = next(
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(f for f in os.listdir(transactions_folder)
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if f.startswith("Specification clearing") and f.endswith(".csv")),
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None
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)
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if csv_filename:
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csv_path = os.path.join(transactions_folder, csv_filename)
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transformed_data = transform_csv(csv_path)
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all_transformed_data.append(transformed_data)
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else:
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# Otherwise, look for inner zip files named "Specification clearing*.zip"
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for root, dirs, files in os.walk(extract_folder):
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for file in files:
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if file.startswith("Specification clearing") and file.endswith(".zip"):
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inner_zip_path = os.path.join(root, file)
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# Create a temporary folder for the inner zip extraction
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inner_extract_folder = os.path.join(root, "inner_extracted")
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os.makedirs(inner_extract_folder, exist_ok=True)
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with zipfile.ZipFile(inner_zip_path, 'r') as inner_zip:
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inner_zip.extractall(inner_extract_folder)
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# Expect the inner zip to contain a "Transactions" folder with the CSV
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inner_transactions_folder = os.path.join(inner_extract_folder, "Transactions")
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if os.path.exists(inner_transactions_folder):
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inner_csv_filename = next(
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(f for f in os.listdir(inner_transactions_folder)
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if f.startswith("Specification clearing") and f.endswith(".csv")),
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None
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)
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if inner_csv_filename:
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inner_csv_path = os.path.join(inner_transactions_folder, inner_csv_filename)
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transformed_data = transform_csv(inner_csv_path)
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all_transformed_data.append(transformed_data)
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# Clean up inner extraction folder
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shutil.rmtree(inner_extract_folder)
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# Clean up the outer extraction folder
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shutil.rmtree(extract_folder)
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print(f"Processed and cleaned up: {zip_file_path}")
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# Return a ZIP archive (in memory) containing all the output CSV files.
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return write_output_csv_to_zip(output_file, all_transformed_data)
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def transform_csv(input_file):
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global transactions_df
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df = pd.read_csv(input_file, delimiter=";", dtype=str)
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df.iloc[:, 12] = pd.to_numeric(df.iloc[:, 12].str.replace(',', '.'), errors='coerce').fillna(0)
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df['Zůstatek na účtu'] = df.iloc[:, 12].cumsum().astype(float).round(2)
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transformed_data = []
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total_rows = len(df)
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clearing_id = df['CLEARING_ID'].iloc[0] if 'CLEARING_ID' in df.columns else None
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for index, row in df.iterrows():
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amount = row.iloc[12]
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typ_operace = "t" if amount >= 0 else "c"
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transformed_row = [
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typ_operace, row.iloc[1], row.iloc[15], amount, row['Zůstatek na účtu'], "TRUE", row.iloc[15],
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f"Dobirka za FA s VS {row.iloc[15]}", "", "", "", "", row.iloc[6], row.iloc[6], row.iloc[4], 0, "EUR"
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]
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transformed_data.append(transformed_row)
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progress = (index + 1) / total_rows * 100
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sys.stdout.write(f"\rProcessing: {progress:.2f}%")
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sys.stdout.flush()
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total_sum = round(df.iloc[:, 12].sum(), 2)
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corresponding_transaction = search_bank_transaction(clearing_id)
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final_row = ["w", datetime.strptime(corresponding_transaction['Datum'], "%d.%m.%Y").strftime("%Y-%m-%d"), corresponding_transaction['Zpráva pro příjemce'].split(',')[-1].strip(), -total_sum, 0, "TRUE", "", "Vyrovnání zůstatku", corresponding_transaction['Číslo účtu'] + "/2010", "", "", "", "", "", "NEWLINE BREAK", "", "EUR"]
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transformed_data.append(final_row)
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return transformed_data
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# extract_and_process_zip(zip_folder, output_csv)
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