#!/usr/bin/env python3

import csv
import glob
import os
from collections import defaultdict

def categorize_transaction(description):
    description = description.lower()
    
    if "pocket withdrawal" in description:
        return "Ignore"

    # Savings
    if "to pocket eur épargne" in description:
        return "Savings (Revolut Pocket)"

    # Groceries
    grocery_keywords = ['intermarché', 'carrefour', 'lidl', 'auchan', 'monoprix', 'e.leclerc', 'vival', 'super u', 'naturalia']
    if any(keyword in description for keyword in grocery_keywords):
        return "Groceries"

    # Transport
    transport_keywords = ['ratp', 'sncf', 'rhônexpress', 'tam', 'spl', 'transavia']
    if any(keyword in description for keyword in transport_keywords):
        return "Transport"

    # Travel
    travel_keywords = ['hotel', 'ote inn', 'fred 2 cow']
    if any(keyword in description for keyword in travel_keywords):
        return "Travel"

    # Restaurants / Food
    food_keywords = [
        "mcdonald's", "starbucks", "kfc", "o'tacos", "domino's", 'burger', 'sushi', 
        'pizza', 'restaurant', 'café', 'bar', 'boulangerie', 'patisserie', 
        'columbus café', 'la rotisserie', 'le petit marcel', 'maison besnier',
        'pokawa', 'liban sibon', 'le paradis du fruit', 'la station', 'amorino'
    ]
    if any(keyword in description for keyword in food_keywords):
        return "Restaurants/Food"

    # Shopping
    shopping_keywords = ['amazon', 'fnac', 'decathlon', 'intersport', 'celio', 'jd paris velize 2', 'normal', 'rituals', 'bricorama']
    if any(keyword in description for keyword in shopping_keywords):
        return "Shopping"

    # Entertainment / Leisure
    entertainment_keywords = [
        'ugc ciné', 'viva technology', 'pathe', 'gaumont', 'disneyland', 'parc asterix', 
        'spotify', 'netflix', 'bizouk', 'club', 'bar', 'yoyo', 'le loft metropolis', 'western union'
    ]
    if any(keyword in description for keyword in entertainment_keywords):
        return "Entertainment/Leisure"

    # Utilities / Bills
    utilities_keywords = ['mint', 'air medias', 'basic-fit', 'crossfit louvre']
    if any(keyword in description for keyword in utilities_keywords):
        return "Utilities/Bills"

    # Health
    health_keywords = ['pharmacie', 'doctolib']
    if any(keyword in description for keyword in health_keywords):
        return "Health"

    # Cash Withdrawals
    if 'cash withdrawal' in description:
        return "Cash Withdrawals"

    # Services
    services_keywords = ['barber', 'coiffeur', 'sensei barber', 'rnf lavage aut']
    if any(keyword in description for keyword in services_keywords):
        return "Services"
        
    # Transfers (Outgoing)
    if description.startswith('to ') or 'cynthia sophie carvigant' in description:
        return 'Transfers Out'

    # Crypto / Investing
    if 'digital assets' in description or 'investment account' in description:
        return 'Investing/Crypto'
        
    return "Other"

def process_revolut_data(output_csv=False, output_dir='../../output/csv'):
    expense_summary = defaultdict(float)
    total_expenses = 0
    other_descriptions = []
    all_transactions = []

    # We'll analyze the full year of 2025
    csv_files = glob.glob('/home/acid/Downloads/comptabilite/revolut/account-statement_2025-*.csv')

    for file in csv_files:
        with open(file, 'r', encoding='utf-8') as f:
            reader = csv.DictReader(f)
            for row in reader:
                try:
                    amount = float(row['Amount'])
                    currency = row['Currency']

                    if currency == 'EUR' and amount < 0:
                        description = row['Description']
                        category = categorize_transaction(description)

                        if category == "Ignore":
                            continue

                        # We only add the expense amount (absolute value)
                        expense_summary[category] += abs(amount)
                        total_expenses += abs(amount)
                        
                        # Store transaction for CSV output
                        all_transactions.append({
                            'Date': row['Completed Date'],
                            'Description': description,
                            'Category': category,
                            'Amount': abs(amount),
                            'Source': os.path.basename(file)
                        })
                        
                        if category == "Other":
                            other_descriptions.append((description, abs(amount)))

                except (ValueError, KeyError):
                    # Ignore rows with invalid amount or missing columns
                    continue
    
    # Output CSV if requested
    if output_csv and all_transactions:
        csv_file = os.path.join(output_dir, 'revolut_all_transactions.csv')
        os.makedirs(output_dir, exist_ok=True)
        with open(csv_file, 'w', newline='', encoding='utf-8') as csvfile:
            fieldnames = ['Date', 'Description', 'Category', 'Amount', 'Source']
            writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
            writer.writeheader()
            writer.writerows(all_transactions)
        print(f"\nTransaction data saved to {csv_file}")

    # Print Summary
    print("--- Revolut Expense Summary for 2025 (Corrected) ---")
    print(f"Total Expenses Analyzed: €{total_expenses:,.2f}")
    print("\n--- Spending by Category ---")

    # Sort categories by amount for better readability
    sorted_expenses = sorted(expense_summary.items(), key=lambda item: item[1], reverse=True)

    for category, total in sorted_expenses:
        percentage = (total / total_expenses) * 100
        print(f"{category:<25} €{total:9,.2f} ({percentage:5.2f}%)")
        
    print("\n--- Top 20 Uncategorized ('Other') Transactions (Post-Correction) ---")
    other_descriptions.sort(key=lambda x: x[1], reverse=True)
    for desc, amount in other_descriptions[:20]:
        print(f"€{amount:8.2f} - {desc}")
    
    return all_transactions

if __name__ == "__main__":
    import argparse
    
    parser = argparse.ArgumentParser(description='Process Revolut statements')
    parser.add_argument('--csv-dir', default='../data/raw_csv', 
                       help='Directory containing Revolut CSV files')
    parser.add_argument('--output-dir', default='../../output/csv', 
                       help='Directory to save CSV output files')
    parser.add_argument('--csv', action='store_true', 
                       help='Output transaction data to CSV file')
    args = parser.parse_args()
    
    # Process all CSV files in the directory
    process_revolut_data(args.csv, args.output_dir)