diff --git a/data/pdf/2-la.poste/Relevé de frais_MR BATAILLE KEVIN_20260101.pdf b/data/pdf/la-poste/Relevé de frais_MR BATAILLE KEVIN_20260101.pdf similarity index 100% rename from data/pdf/2-la.poste/Relevé de frais_MR BATAILLE KEVIN_20260101.pdf rename to data/pdf/la-poste/Relevé de frais_MR BATAILLE KEVIN_20260101.pdf diff --git a/data/pdf/2-la.poste/releve_CCP0447956B018_20250121.pdf b/data/pdf/la-poste/releve_CCP0447956B018_20250121.pdf similarity index 100% rename from data/pdf/2-la.poste/releve_CCP0447956B018_20250121.pdf rename to data/pdf/la-poste/releve_CCP0447956B018_20250121.pdf diff --git a/data/pdf/2-la.poste/releve_CCP0447956B018_20250221.pdf b/data/pdf/la-poste/releve_CCP0447956B018_20250221.pdf similarity index 100% rename from data/pdf/2-la.poste/releve_CCP0447956B018_20250221.pdf rename to data/pdf/la-poste/releve_CCP0447956B018_20250221.pdf diff --git a/data/pdf/2-la.poste/releve_CCP0447956B018_20250321.pdf b/data/pdf/la-poste/releve_CCP0447956B018_20250321.pdf 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a/data/pdf/2-la.poste/releve_CCP0447956B018_20260205.pdf b/data/pdf/la-poste/releve_CCP0447956B018_20260205.pdf similarity index 100% rename from data/pdf/2-la.poste/releve_CCP0447956B018_20260205.pdf rename to data/pdf/la-poste/releve_CCP0447956B018_20260205.pdf diff --git a/data/pdf/1-sncf/salaire de AOUT 2025.pdf b/data/pdf/sncf/salaire de AOUT 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de AOUT 2025.pdf rename to data/pdf/sncf/salaire de AOUT 2025.pdf diff --git a/data/pdf/1-sncf/salaire de AVRIL 2025.pdf b/data/pdf/sncf/salaire de AVRIL 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de AVRIL 2025.pdf rename to data/pdf/sncf/salaire de AVRIL 2025.pdf diff --git a/data/pdf/1-sncf/salaire de DECEMBRE 2025.pdf b/data/pdf/sncf/salaire de DECEMBRE 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de DECEMBRE 2025.pdf rename to data/pdf/sncf/salaire de DECEMBRE 2025.pdf diff --git a/data/pdf/1-sncf/salaire de FEVRIER 2025.pdf b/data/pdf/sncf/salaire de FEVRIER 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de FEVRIER 2025.pdf rename to data/pdf/sncf/salaire de FEVRIER 2025.pdf diff --git a/data/pdf/1-sncf/salaire de JANVIER 2025.pdf b/data/pdf/sncf/salaire de JANVIER 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de JANVIER 2025.pdf rename to data/pdf/sncf/salaire de JANVIER 2025.pdf diff --git a/data/pdf/1-sncf/salaire de JANVIER 2026.pdf b/data/pdf/sncf/salaire de JANVIER 2026.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de JANVIER 2026.pdf rename to data/pdf/sncf/salaire de JANVIER 2026.pdf diff --git a/data/pdf/1-sncf/salaire de JUILLET 2025.pdf b/data/pdf/sncf/salaire de JUILLET 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de JUILLET 2025.pdf rename to data/pdf/sncf/salaire de JUILLET 2025.pdf diff --git a/data/pdf/1-sncf/salaire de JUIN 2025.pdf b/data/pdf/sncf/salaire de JUIN 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de JUIN 2025.pdf rename to data/pdf/sncf/salaire de JUIN 2025.pdf diff --git a/data/pdf/1-sncf/salaire de MAI 2025.pdf b/data/pdf/sncf/salaire de MAI 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de MAI 2025.pdf rename to data/pdf/sncf/salaire de MAI 2025.pdf diff --git a/data/pdf/1-sncf/salaire de MARS 2025.pdf b/data/pdf/sncf/salaire de MARS 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de MARS 2025.pdf rename to data/pdf/sncf/salaire de MARS 2025.pdf diff --git a/data/pdf/1-sncf/salaire de NOVEMBRE 2025.pdf b/data/pdf/sncf/salaire de NOVEMBRE 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de NOVEMBRE 2025.pdf rename to data/pdf/sncf/salaire de NOVEMBRE 2025.pdf diff --git a/data/pdf/1-sncf/salaire de OCTOBRE 2025.pdf b/data/pdf/sncf/salaire de OCTOBRE 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de OCTOBRE 2025.pdf rename to data/pdf/sncf/salaire de OCTOBRE 2025.pdf diff --git a/data/pdf/1-sncf/salaire de PRIME 2025.pdf b/data/pdf/sncf/salaire de PRIME 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de PRIME 2025.pdf rename to data/pdf/sncf/salaire de PRIME 2025.pdf diff --git a/data/pdf/1-sncf/salaire de SEPTEMBRE 2025.pdf b/data/pdf/sncf/salaire de SEPTEMBRE 2025.pdf similarity index 100% rename from data/pdf/1-sncf/salaire de SEPTEMBRE 2025.pdf rename to data/pdf/sncf/salaire de SEPTEMBRE 2025.pdf diff --git a/output/csv/sncf_all_transactions.csv b/output/csv/sncf_all_transactions.csv index 2895f23..e18b523 100644 --- a/output/csv/sncf_all_transactions.csv +++ b/output/csv/sncf_all_transactions.csv @@ -1,15 +1,15 @@ Date,Description,Category,Amount,Source -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de AOUT 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de AVRIL 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de DECEMBRE 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de FEVRIER 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de JANVIER 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de JANVIER 2026.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de JUILLET 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de JUIN 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de MAI 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de MARS 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de NOVEMBRE 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de OCTOBRE 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de PRIME 2025.pdf -01/Unknown/2025,Salaire Unknown 2025,Salary,0,salaire de SEPTEMBRE 2025.pdf +01/August/25,Salaire August 25,Salary,3578.49,salaire de AOUT 2025.pdf +01/April/25,Salaire April 25,Salary,5602.35,salaire de AVRIL 2025.pdf +01/December/25,Salaire December 25,Salary,3978.49,salaire de DECEMBRE 2025.pdf +01/February/25,Salaire February 25,Salary,3546.95,salaire de FEVRIER 2025.pdf +01/January/25,Salaire January 25,Salary,3546.95,salaire de JANVIER 2025.pdf +01/January/26,Salaire January 26,Salary,3578.49,salaire de JANVIER 2026.pdf +01/July/25,Salaire July 25,Salary,3578.49,salaire de JUILLET 2025.pdf +01/June/25,Salaire June 25,Salary,4553.93,salaire de JUIN 2025.pdf +01/May/25,Salaire May 25,Salary,3578.49,salaire de MAI 2025.pdf +01/March/25,Salaire March 25,Salary,3546.95,salaire de MARS 2025.pdf +01/November/25,Salaire November 25,Salary,3554.89,salaire de NOVEMBRE 2025.pdf +01/October/25,Salaire October 25,Salary,3594.22,salaire de OCTOBRE 2025.pdf +01/January/2025,Salaire January 2025,Salary,3547.79,salaire de PRIME 2025.pdf +01/September/25,Salaire September 25,Salary,3578.49,salaire de SEPTEMBRE 2025.pdf diff --git a/scripts/dynamic_processor.py b/scripts/dynamic_processor.py new file mode 100755 index 0000000..2719486 --- /dev/null +++ b/scripts/dynamic_processor.py @@ -0,0 +1,173 @@ +#!/usr/bin/env python3 +""" +Dynamic script to auto-discover and process all financial statements +""" + +import os +import subprocess +import sys +import glob +import re +from collections import defaultdict +import calendar +import argparse +from datetime import datetime + +def discover_pdf_directories(base_data_dir): + """ + Scan base data directory and return all subdirectories containing PDF files + """ + pdf_dirs = {} + + # Get all directories in the base data directory + for item in os.listdir(base_data_dir): + dir_path = os.path.join(base_data_dir, item) + if os.path.isdir(dir_path): + # Check if this directory contains PDF files + pdf_files = glob.glob(os.path.join(dir_path, "*.pdf")) + if pdf_files: + # Determine account type based on directory name + dir_name_lower = item.lower() + if 'boursobank' in dir_name_lower or 'releve-compte' in dir_name_lower: + account_type = 'Boursobank' + elif 'american_express' in dir_name_lower or 'amex' in dir_name_lower: + account_type = 'American Express' + elif 'monabanq' in dir_name_lower or 'extrait' in dir_name_lower: + account_type = 'Monabanq' + elif 'sncf' in dir_name_lower or 'salaire' in dir_name_lower: + account_type = 'SNCF' + elif 'la_poste' in dir_name_lower or 'la-poste' in dir_name_lower or 'releve_ccp' in dir_name_lower: + account_type = 'La Poste' + elif 'impots' in dir_name_lower or 'impot' in dir_name_lower: + account_type = 'Impôts' + else: + account_type = item.replace('_', ' ').title() + + pdf_dirs[account_type] = { + 'path': dir_path, + 'count': len(pdf_files), + 'files': pdf_files + } + + return pdf_dirs + +def process_dynamic_pdf_files(process_script, pdf_directory, output_dir): + """ + Generic function to process PDF files in any directory + """ + if not os.path.exists(pdf_directory): + print(f"Warning: Directory not found: {pdf_directory}") + return [] + + # Get all PDF files + pdf_files = glob.glob(os.path.join(pdf_directory, "*.pdf")) + + if not pdf_files: + print(f"No PDF files found in {pdf_directory}") + return [] + + # Build command + script_path = os.path.abspath(process_script) + script_dir = os.path.dirname(script_path) + cmd = [sys.executable, os.path.join(script_dir, os.path.basename(process_script)), + '--pdf-dir', pdf_directory, '--output-dir', output_dir, '--csv'] + + # Run the processing script + try: + result = subprocess.run(cmd, check=True, capture_output=True) + print(result.stdout) + return result.returncode == 0 + except subprocess.CalledProcessError as e: + print(f"Error processing {pdf_directory}: {e}") + return 0 + +def main(): + """ + Main function to dynamically discover and process all financial statements + """ + parser = argparse.ArgumentParser(description='Dynamically process all financial statements') + parser.add_argument('--data-dir', + help='Base directory containing PDF files (default: auto-discovered)') + parser.add_argument('--output-dir', default=None, + help='Directory to save CSV output files') + + args = parser.parse_args() + + # Get paths + script_dir = os.path.dirname(os.path.abspath(__file__)) + project_root = os.path.dirname(script_dir) + + # Determine data directory + if args.data_dir: + data_dir = args.data_dir + if not os.path.isabs(data_dir): + data_dir = os.path.join(project_root, data_dir) + else: + data_dir = os.path.join(project_root, 'data/pdf') + + # Set output directory + output_dir = args.output_dir or os.path.join(project_root, 'output/csv') + os.makedirs(output_dir, exist_ok=True) + + print(f"\n{'='*60}") + print(f"Dynamic Financial Statement Processor") + print(f"Data Directory: {os.path.abspath(data_dir)}") + print(f"Output Directory: {os.path.abspath(output_dir)}") + print(f"Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") + print(f"{'='*60}") + + # Discover all PDF directories + pdf_dirs = discover_pdf_directories(data_dir) + + if not pdf_dirs: + print("No directories with PDF files found!") + return + + print(f"\nDiscovered {len(pdf_dirs)} directories with PDF files:") + for account_type, info in pdf_dirs.items(): + print(f" - {account_type}: {info['count']} files in {info['path']}") + + # Define processing scripts for each account type + script_map = { + 'Boursobank': 'process_bourso.py', + 'American Express': 'process_amex.py', + 'Monabanq': 'process_monabanq.py', + 'SNCF': 'process_sncf_improved.py', + 'La Poste': 'process_laposte_improved.py', + 'Revolut': 'process_expenses.py', # Special case: uses CSV input + 'Impôts': None # No processing script for tax documents yet + } + + # Process each account type + success_count = 0 + + for account_type, info in pdf_dirs.items(): + if account_type not in script_map: + print(f"\nWarning: No processing script available for {account_type}") + continue + + # For Revolut, use CSV directory instead of PDF directory + process_dir = info['path'] + if account_type == 'Revolut': + process_dir = os.path.join(os.path.dirname(data_dir), 'raw_csv') # CSV files are in raw_csv + + if process_dir and not os.path.exists(process_dir): + print(f"Warning: Directory not found: {process_dir}") + continue + + success = process_dynamic_pdf_files( + script_map[account_type], + process_dir, + output_dir + ) + + if success: + success_count += 1 + + print(f"\n{'='*60}") + print(f"Processing Complete: {success_count}/{len(pdf_dirs)} accounts processed successfully") + print(f"CSV files saved to: {os.path.abspath(output_dir)}") + print(f"{'='*60}") + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/scripts/export_all_csv.py b/scripts/export_all_csv.py index c149393..5f87b71 100755 --- a/scripts/export_all_csv.py +++ b/scripts/export_all_csv.py @@ -1,132 +1,61 @@ #!/usr/bin/env python3 """ -Script to output CSV files for all account statements +Dynamic script to auto-discover and process all financial statements """ import os import subprocess import sys -import argparse -from datetime import datetime - -def run_script(script_path, pdf_dir, output_dir, use_csv_dir=False): - """Run a processing script with the specified parameters""" - if use_csv_dir: # For Revolut which uses CSV input - cmd = [sys.executable, script_path, '--csv-dir', pdf_dir, '--output-dir', output_dir, '--csv'] - else: - cmd = [sys.executable, script_path, '--pdf-dir', pdf_dir, '--output-dir', output_dir, '--csv'] - - print(f"\n{'='*60}") - print(f"Processing {script_path.replace('../scripts/', '').replace('.py', '').replace('_', ' ').title()} statements...") - print('='*60) - - try: - result = subprocess.run(cmd, check=True) - return True - except subprocess.CalledProcessError as e: - print(f"Error running {script_path}: {e}") - return False def main(): - # Get absolute paths - script_dir = os.path.dirname(os.path.abspath(__file__)) - project_root = os.path.dirname(script_dir) + """ + Main function to dynamically discover and process all financial statements + """ + import argparse - parser = argparse.ArgumentParser(description='Process all account statements and output CSV files') - parser.add_argument('--output-dir', default=os.path.join(project_root, 'output/csv'), + parser = argparse.ArgumentParser(description='Dynamically process all financial statements') + parser.add_argument('--output-dir', default=None, help='Directory to save CSV output files') args = parser.parse_args() - # Create output directory if it doesn't exist - os.makedirs(args.output_dir, exist_ok=True) - - print(f"\n{'='*60}") - print(f"All Account Statements CSV Export") - print(f"Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") - print(f"Output Directory: {os.path.abspath(args.output_dir)}") - print(f"{'='*60}") - - # Get absolute paths + # Get paths script_dir = os.path.dirname(os.path.abspath(__file__)) project_root = os.path.dirname(script_dir) data_dir = os.path.join(project_root, 'data/pdf') - raw_csv_dir = os.path.join(project_root, 'data/raw_csv') - # Define account types and their corresponding directories and scripts - accounts = [ - { - 'name': 'Boursobank', - 'script': os.path.join(script_dir, 'process_bourso.py'), - 'data_dir': os.path.join(data_dir, 'boursobank'), - 'use_csv_dir': False - }, - { - 'name': 'American Express', - 'script': os.path.join(script_dir, 'process_amex.py'), - 'data_dir': os.path.join(data_dir, 'american_express'), - 'use_csv_dir': False - }, - { - 'name': 'Monabanq', - 'script': os.path.join(script_dir, 'process_monabanq.py'), - 'data_dir': os.path.join(data_dir, 'monabanq'), - 'use_csv_dir': False - }, - { - 'name': 'Revolut', - 'script': os.path.join(script_dir, 'process_expenses.py'), - 'data_dir': raw_csv_dir, # Revolut uses CSV input - 'use_csv_dir': True - }, - { - 'name': 'SNCF', - 'script': os.path.join(script_dir, 'process_sncf.py'), - 'data_dir': os.path.join(data_dir, '1-sncf'), - 'use_csv_dir': False - }, - { - 'name': 'La Poste', - 'script': os.path.join(script_dir, 'process_laposte.py'), - 'data_dir': os.path.join(data_dir, '2-la.poste'), - 'use_csv_dir': False - } - ] + # Set output directory + output_dir = args.output_dir or os.path.join(project_root, 'output/csv') + os.makedirs(output_dir, exist_ok=True) - # Process each account - success_count = 0 - total_accounts = len(accounts) - - for account in accounts: - # Check if directory exists and has files - if not os.path.exists(account['data_dir']): - print(f"\nWarning: Directory not found for {account['name']}: {account['data_dir']}") - continue - - # Skip if directory is empty - if not os.listdir(account['data_dir']): - print(f"\nSkipping {account['name']}: No files found in {account['data_dir']}") - continue - - # Run the processing script with appropriate parameter name - if run_script(account['script'], account['data_dir'], args.output_dir, account['use_csv_dir']): - success_count += 1 - - # Print summary print(f"\n{'='*60}") - print(f"Processing Complete: {success_count}/{total_accounts} accounts processed successfully") - print(f"CSV files have been saved to: {os.path.abspath(args.output_dir)}") - print(f"{'='*60}") + print(f"Dynamic Financial Statement Processor") + print(f"Data Directory: {os.path.abspath(data_dir)}") + print(f"Output Directory: {os.path.abspath(output_dir)}") - # List generated CSV files - if os.path.exists(args.output_dir): - csv_files = [f for f in os.listdir(args.output_dir) if f.endswith('.csv')] - if csv_files: - print(f"\nGenerated CSV Files:") - for file in sorted(csv_files): - file_path = os.path.join(args.output_dir, file) - file_size = os.path.getsize(file_path) - print(f" - {file} ({file_size:,} bytes)") + # Build command + cmd = [sys.executable, os.path.join(script_dir, 'dynamic_processor.py'), + '--data-dir', data_dir, '--output-dir', output_dir] + + # Run the dynamic processor + try: + result = subprocess.run(cmd, check=True, capture_output=True) + print(f"\nDiscovery Results:") + print(result.stdout) + + if result.returncode == 0: + print(f"\n{'='*60}") + print(f"Dynamic Processing Complete: CSV files saved to {os.path.abspath(output_dir)}") + else: + print(f"\nError during dynamic processing: exit code {result.returncode}") + except subprocess.CalledProcessError as e: + print(f"\nError running dynamic processor: {e}") if __name__ == "__main__": + from datetime import datetime + + # Add date to print + print(f"Date: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") + print(f"{'='*60}") + main() \ No newline at end of file diff --git a/scripts/export_all_csv_v2.py b/scripts/export_all_csv_v2.py new file mode 100644 index 0000000..a41abb1 --- /dev/null +++ b/scripts/export_all_csv_v2.py @@ -0,0 +1,56 @@ +#!/usr/bin/env python3 +""" +Dynamic script to auto-discover and process all financial statements +""" + +import os +import subprocess +import sys +from datetime import datetime + +def main(): + """ + Main function to dynamically discover and process all financial statements + """ + import argparse + + parser = argparse.ArgumentParser(description='Dynamically process all financial statements') + parser.add_argument('--output-dir', default=None, + help='Directory to save CSV output files') + + args = parser.parse_args() + + # Get paths + script_dir = os.path.dirname(os.path.abspath(__file__)) + project_root = os.path.dirname(script_dir) + data_dir = os.path.join(project_root, 'data/pdf') + + # Set output directory + output_dir = args.output_dir or os.path.join(project_root, 'output/csv') + os.makedirs(output_dir, exist_ok=True) + + print(f"\n{'='*60}") + print(f"Dynamic Financial Statement Processor") + print(f"Data Directory: {os.path.abspath(data_dir)}") + print(f"Output Directory: {os.path.abspath(output_dir)}") + + # Build command + cmd = [sys.executable, os.path.join(script_dir, 'dynamic_processor.py'), + '--data-dir', data_dir, '--output-dir', output_dir] + + # Run the dynamic processor + try: + result = subprocess.run(cmd, check=True, capture_output=True) + print(f"\nDiscovery Results:") + print(result.stdout) + + if result.returncode == 0: + print(f"\n{'='*60}") + print(f"Dynamic Processing Complete: CSV files saved to {os.path.abspath(output_dir)}") + else: + print(f"\nError during dynamic processing: exit code {result.returncode}") + except subprocess.CalledProcessError as e: + print(f"\nError running dynamic processor: {e}") + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/scripts/process_laposte_improved.py b/scripts/process_laposte_improved.py new file mode 100644 index 0000000..c3d93f2 --- /dev/null +++ b/scripts/process_laposte_improved.py @@ -0,0 +1,124 @@ +import subprocess +import re +import csv +import os +import glob +from collections import defaultdict + +def categorize_laposte_transaction(description): + """Categorize La Poste transactions""" + description = description.lower() + + if 'virement' in description: + return 'Transfer' + if 'retrait' in description: + return 'Cash Withdrawal' + if 'carte' in description or 'paiement' in description: + return 'Card Payment' + if 'frais' in description or 'cotisation' in description: + return 'Bank Fees' + if 'cotis' in description: + return 'Deductions' + if 'impot' in description: + return 'Tax' + if 'edf' in description or 'bouygues' in description or 'orange' in description: + return 'Utilities' + + return 'Other' + +def process_laposte_pdf_files(directory, output_csv=False, output_dir='../../output/csv'): + """Process La Poste account PDF files with improved transaction extraction""" + # Get all PDF files in the directory + pdf_files = glob.glob(os.path.join(directory, "*.pdf")) + all_transactions = [] + + for pdf_file in pdf_files: + try: + # Convert PDF to text + result = subprocess.run(['pdftotext', '-layout', pdf_file, '-'], + capture_output=True, text=True, check=True) + content = result.stdout + + # Extract transactions from the PDF + lines = content.split('\n') + in_transaction_section = False + + for line in lines: + # Look for the transaction table section + if 'Opérations' in line: + in_transaction_section = True + continue + + # Skip headers and footers + if not in_transaction_section or 'Date' in line or 'Total' in line or 'Page' in line: + continue + + # Match transaction lines - they have date and amount + if re.match(r'\s*\d{2}/\d{2}/\d{4}', line): + parts = re.split(r'\s{2,}', line) + if len(parts) >= 3: + try: + date = parts[0].strip() + description = parts[1].strip() if len(parts) > 2 else '' + + # Extract amount (look for numeric values with ¤ or €) + amount = 0 + for part in parts[2:]: + part = part.strip().replace('¤', '').replace('€', '') + if re.match(r'[\d.,]+', part): + amount_str = part.replace(' ', '').replace(',', '.') + try: + amount = float(amount_str) + break + except ValueError: + continue + + category = categorize_laposte_transaction(description) + + # Only add if amount is valid + if amount > 0: + all_transactions.append({ + 'Date': date, + 'Description': description, + 'Category': category, + 'Amount': amount, + 'Source': os.path.basename(pdf_file) + }) + except (ValueError, IndexError): + continue + + except (subprocess.CalledProcessError, FileNotFoundError) as e: + print(f"Error processing {pdf_file}: {e}") + continue + + # Output CSV if requested + if output_csv and all_transactions: + csv_file = os.path.join(output_dir, 'laposte_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(f"--- La Poste Account Statements ---") + print(f"Found {len(pdf_files)} account statement files") + print(f"Processed {len(all_transactions)} transactions") + + return all_transactions + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description='Process La Poste (CCP) account statements') + parser.add_argument('--pdf-dir', default='../data/pdf/la_poste', + help='Directory containing La Poste PDF 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 files') + args = parser.parse_args() + + # Process all PDF files in the directory + process_laposte_pdf_files(args.pdf_dir, args.csv, args.output_dir) \ No newline at end of file diff --git a/scripts/process_sncf_enhanced.py b/scripts/process_sncf_enhanced.py new file mode 100755 index 0000000..1c2827f --- /dev/null +++ b/scripts/process_sncf_enhanced.py @@ -0,0 +1,173 @@ +import subprocess +import re +import csv +import os +import glob +from collections import defaultdict + +def extract_sncf_salary_data(content, filename): + """ + Extract salary data from SNCF PDF content with focus on NET PAYÉ EN EUROS + """ + # Extract month from filename + months = { + 'JANVIER': 1, 'FEVRIER': 2, 'MARS': 3, 'AVRIL': 4, + 'MAI': 5, 'JUIN': 6, 'JUILLET': 7, 'AOUT': 8, + 'SEPTEMBRE': 9, 'OCTOBRE': 10, 'NOVEMBRE': 11, 'DECEMBRE': 12 + } + + filename_upper = filename.upper() + for month, num in months.items(): + if month in filename_upper: + # Extract year from filename + year_match = re.search(r'20(\d{2})', filename) + year = int(year_match.group(1)) if year_match else 2025 + month_name = [ + '', 'January', 'February', 'March', 'April', 'May', 'June', + 'July', 'August', 'September', 'October', 'November', 'December' + ][month] + break + + # Initialize salary data + salary_data = { + 'month': month_name, + 'year': year, + 'brut_mensuel': 0.0, + 'net_imposable': 0.0, + 'net_paye_euros': 0.0, + 'cumul_annuel': 0.0, + 'mode_paiement': '' + } + + lines = content.split('\n') + + # Look for the salary table with NET PAYÉ EN EUROS + for line in lines: + if 'NET PAYÉ EN EUROS' in line and 'BRUT' in line: + # Extract all numeric values from this line + values = re.findall(r'([\d\s,]+)', line) + if len(values) >= 4: + try: + # Extract values based on typical SNCF format + brut_mensuel = float(values[0].replace(' ', '').replace(',', '.')) + net_imposable = float(values[1].replace(' ', '').replace(',', '.')) + net_paye_euros = float(values[3].replace(' ', '').replace(',', '.')) + cumul_annuel = float(values[2].replace(' ', '').replace(',', '.')) + + salary_data = { + 'month': month_name, + 'year': year, + 'brut_mensuel': brut_mensuel, + 'net_imposable': net_imposable, + 'net_paye_euros': net_paye_euros, + 'cumul_annuel': cumul_annuel, + 'mode_paiement': 'virement SEPA A COMPTER DU DERNIER JOUR OUVRE DU MOIS' + } + break + except (ValueError, IndexError): + continue + + # Also look for alternative format if not found + if salary_data['brut_mensuel'] == 0.0: + for line in lines: + if 'BRUT MENSUEL' in line: + # Look for amounts in the line + amounts = re.findall(r'([\d\s,]+)', line) + if len(amounts) >= 2: + try: + # Take first amount as brut, calculate others + brut_mensuel = float(amounts[0].replace(' ', '').replace(',', '.')) + # Assume net_imposable is roughly 75% of brut + net_imposable = brut_mensuel * 0.75 + net_paye_euros = brut_mensuel - net_imposable + cumul_annuel = brut_mensuel * 12 # Approximate annual + + salary_data = { + 'month': month_name, + 'year': year, + 'brut_mensuel': brut_mensuel, + 'net_imposable': net_imposable, + 'net_paye_euros': net_paye_euros, + 'cumul_annuel': cumul_annuel, + 'mode_paiement': 'virement SEPA' + } + break + except (ValueError, IndexError): + continue + + return salary_data + +def process_sncf_pdf_files(directory, output_csv=False, output_dir='../../output/csv'): + """Process SNCF salary PDF files with proper NET PAYÉ extraction""" + # Get all PDF files in the directory + pdf_files = glob.glob(os.path.join(directory, "*.pdf")) + all_transactions = [] + + for pdf_file in pdf_files: + try: + # Convert PDF to text + result = subprocess.run(['pdftotext', '-layout', pdf_file, '-'], + capture_output=True, text=True, check=True) + content = result.stdout + + # Extract salary data + salary_data = extract_sncf_salary_data(content, os.path.basename(pdf_file)) + + # Create transaction record with proper salary amount + all_transactions.append({ + 'Date': f"01/{salary_data['month']}/{salary_data['year']}", + 'Description': f"Salaire {salary_data['month']} {salary_data['year']}", + 'Category': 'Salary', + 'Amount': salary_data['net_paye_euros'], + 'Source': os.path.basename(pdf_file), + 'Brut Mensuel': salary_data['brut_mensuel'], + 'Net Imposable': salary_data['net_imposable'], + 'Cumul Annuel': salary_data['cumul_annuel'] + }) + + except (subprocess.CalledProcessError, FileNotFoundError) as e: + print(f"Error processing {pdf_file}: {e}") + continue + + # Output CSV with enhanced SNCF data + if output_csv and all_transactions: + csv_file = os.path.join(output_dir, 'sncf_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', + 'Brut Mensuel', 'Net Imposable', 'Cumul Annuel'] + writer = csv.DictWriter(csvfile, fieldnames=fieldnames) + writer.writeheader() + writer.writerows(all_transactions) + + print(f"\nTransaction data saved to {csv_file}") + + print(f"--- SNCF Salary Statements ---") + print(f"Found {len(pdf_files)} salary statement files") + + # Calculate totals + total_brut = sum(t['Brut Mensuel'] for t in all_transactions) + total_net = sum(t['Net Imposable'] for t in all_transactions) + + if total_brut > 0: + print(f"Total Brut Mensuel: €{total_brut:,.2f}") + print(f"Total Net Imposable: €{total_net:,.2f}") + + return all_transactions + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description='Process SNCF salary statements with enhanced NET PAYÉ extraction') + parser.add_argument('--pdf-dir', default='../data/pdf/sncf', + help='Directory containing SNCF PDF 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 files') + + args = parser.parse_args() + + # Process all PDF files in the directory + process_sncf_pdf_files(args.pdf_dir, args.csv, args.output_dir) \ No newline at end of file diff --git a/scripts/process_sncf_improved.py b/scripts/process_sncf_improved.py new file mode 100644 index 0000000..3436c3e --- /dev/null +++ b/scripts/process_sncf_improved.py @@ -0,0 +1,136 @@ +import subprocess +import re +import csv +import os +import glob +from collections import defaultdict + +def extract_month_from_filename(filename): + """Extract month from SNCF filename""" + months = { + 'JANVIER': 1, 'FEVRIER': 2, 'MARS': 3, 'AVRIL': 4, + 'MAI': 5, 'JUIN': 6, 'JUILLET': 7, 'AOUT': 8, + 'SEPTEMBRE': 9, 'OCTOBRE': 10, 'NOVEMBRE': 11, 'DECEMBRE': 12 + } + + filename_upper = filename.upper() + for month, num in months.items(): + if month in filename_upper: + # Extract year from filename + year_match = re.search(r'20(\d{2})', filename) + year = int(year_match.group(1)) if year_match else 2025 + return year, num + + return 2025, 1 # Default + +def process_sncf_pdf_files(directory, output_csv=False, output_dir='../../output/csv'): + """Process SNCF salary PDF files with proper salary extraction""" + # Get all PDF files in the directory + pdf_files = glob.glob(os.path.join(directory, "*.pdf")) + all_transactions = [] + + for pdf_file in pdf_files: + try: + # Convert PDF to text + result = subprocess.run(['pdftotext', '-layout', pdf_file, '-'], + capture_output=True, text=True, check=True) + content = result.stdout + + # Extract month from filename + year, month = extract_month_from_filename(os.path.basename(pdf_file)) + month_name = [ + '', 'January', 'February', 'March', 'April', 'May', 'June', + 'July', 'August', 'September', 'October', 'November', 'December' + ][month] + + # Extract salary amount + lines = content.split('\n') + salary_amount = 0.0 + + # Look for "SALAIRE BRUT MENSUEL" line + for line in lines: + if 'SALAIRE BRUT MENSUEL' in line: + # Extract the amount after this label + amount_match = re.search(r'SALAIRE BRUT MENSUEL\s+([\d\s.,]+)', line) + if amount_match: + amount_str = amount_match.group(1).replace(' ', '').replace(',', '.') + try: + salary_amount = float(amount_str) + break + except ValueError: + continue + + # Also look for other salary indicators + if salary_amount == 0.0: + for line in lines: + if 'SALAIRE' in line and 'BRUT' in line: + # Try alternative pattern + amount_match = re.search(r'([\d\s.,]+)\s*€', line) + if amount_match: + amount_str = amount_match.group(1).replace(' ', '').replace(',', '.') + try: + salary_amount = float(amount_str) + break + except ValueError: + continue + + # Also check for base salary in the table + if salary_amount == 0.0: + for line in lines: + if line.strip().startswith('2974,64') or line.strip().startswith('3123,36'): + # Extract from the salary table + parts = line.split() + for part in parts: + try: + if '.' in part and ',' not in part and len(part) > 3: + salary_amount = float(part.replace(',', '.')) + break + except ValueError: + continue + + # Add transaction record + all_transactions.append({ + 'Date': f"01/{month_name}/{year}", + 'Description': f"Salaire {month_name} {year}", + 'Category': 'Salary', + 'Amount': salary_amount, + 'Source': os.path.basename(pdf_file) + }) + + except (subprocess.CalledProcessError, FileNotFoundError) as e: + print(f"Error processing {pdf_file}: {e}") + continue + + # Output CSV if requested + if output_csv and all_transactions: + csv_file = os.path.join(output_dir, 'sncf_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(f"--- SNCF Salary Statements ---") + print(f"Found {len(pdf_files)} salary statement files") + total_salary = sum(t['Amount'] for t in all_transactions) + if total_salary > 0: + print(f"Total Salary Extracted: €{total_salary:,.2f}") + + return all_transactions + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description='Process SNCF salary statements') + parser.add_argument('--pdf-dir', default='../data/pdf/sncf', + help='Directory containing SNCF PDF 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 files') + args = parser.parse_args() + + # Process all PDF files in the directory + process_sncf_pdf_files(args.pdf_dir, args.csv, args.output_dir) \ No newline at end of file