CSV Editor

#!/usr/bin/env python3 """Example showing auto-save that overwrites the original file.""" import asyncio import tempfile import os import pandas as pd from pathlib import Path # Setup path for imports import sys sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) from src.csv_editor.models.csv_session import CSVSession from src.csv_editor.models.auto_save import AutoSaveConfig, AutoSaveMode, AutoSaveStrategy from src.csv_editor.models.data_models import OperationType async def overwrite_same_file_example(): """Demonstrate auto-save that updates the same file.""" print("=" * 60) print("Auto-Save: Overwrite Same File Example") print("=" * 60) # Create a temporary CSV file temp_dir = tempfile.mkdtemp() original_file = os.path.join(temp_dir, "data.csv") # Create initial data initial_data = pd.DataFrame({ 'product': ['Laptop', 'Mouse', 'Keyboard'], 'price': [999.99, 29.99, 79.99], 'stock': [50, 200, 150] }) # Save initial data to file initial_data.to_csv(original_file, index=False) print(f"\n✓ Created file: {original_file}") print(f"Initial content:\n{initial_data}") # Configure auto-save to OVERWRITE the same file config = AutoSaveConfig( enabled=True, mode=AutoSaveMode.AFTER_OPERATION, # Save after each operation strategy=AutoSaveStrategy.OVERWRITE, # Overwrite the original file ) # Create session with auto-save config session = CSVSession(auto_save_config=config) # Load the CSV file df = pd.read_csv(original_file) session.load_data(df, file_path=original_file) # Pass the original file path print(f"\n✓ Loaded data into session from: {original_file}") # Modify the data print("\n--- Making changes to the data ---") # Change 1: Increase all prices by 10% session.df['price'] = session.df['price'] * 1.1 session.record_operation(OperationType.TRANSFORM, {"operation": "price_increase_10%"}) await session.trigger_auto_save_if_needed() print("✓ Increased prices by 10% and auto-saved to same file") # Verify the file was updated df_check1 = pd.read_csv(original_file) print(f"File content after price increase:\n{df_check1}") # Change 2: Add a new product new_row = pd.DataFrame({ 'product': ['Monitor'], 'price': [329.989], # Will be rounded when saved 'stock': [75] }) session.df = pd.concat([session.df, new_row], ignore_index=True) session.record_operation(OperationType.ADD_COLUMN, {"operation": "add_monitor"}) await session.trigger_auto_save_if_needed() print("\n✓ Added new product and auto-saved to same file") # Verify the file was updated again df_check2 = pd.read_csv(original_file) print(f"File content after adding product:\n{df_check2}") # Change 3: Filter out low stock items (this removes data) session.df = session.df[session.df['stock'] >= 100] session.record_operation(OperationType.FILTER, {"condition": "stock >= 100"}) await session.trigger_auto_save_if_needed() print("\n✓ Filtered low stock items and auto-saved to same file") # Final verification df_final = pd.read_csv(original_file) print(f"Final file content:\n{df_final}") print("\n" + "=" * 60) print("Summary:") print("=" * 60) print(f"✓ Original file: {original_file}") print("✓ Same file was overwritten after each operation") print("✓ No backup copies were created") print(f"✓ Final file has {len(df_final)} rows (started with {len(initial_data)})") # Show that only one file exists (no backups) files_in_dir = list(Path(temp_dir).glob("*.csv")) print(f"\nFiles in directory: {[f.name for f in files_in_dir]}") print(f"Total CSV files: {len(files_in_dir)} (only the original, no backups)") return original_file async def hybrid_example_with_overwrite(): """Example showing overwrite with periodic saves.""" print("\n" + "=" * 60) print("Hybrid Mode with Overwrite Example") print("=" * 60) # Create a temporary CSV file temp_dir = tempfile.mkdtemp() original_file = os.path.join(temp_dir, "periodic_data.csv") # Create initial data data = pd.DataFrame({ 'id': [1, 2, 3], 'value': [100, 200, 300] }) data.to_csv(original_file, index=False) print(f"\n✓ Created file: {original_file}") # Configure hybrid mode with overwrite config = AutoSaveConfig( enabled=True, mode=AutoSaveMode.HYBRID, # Both periodic and after-operation strategy=AutoSaveStrategy.OVERWRITE, interval_seconds=2 # Save every 2 seconds ) session = CSVSession(auto_save_config=config) df = pd.read_csv(original_file) session.load_data(df, file_path=original_file) # Start periodic saves await session.auto_save_manager.start_periodic_save(session._save_callback) print("✓ Started periodic auto-save (every 2 seconds)") # Make some changes print("\nMaking gradual changes...") # Change 1 session.df['value'] = session.df['value'] + 10 print(" Added 10 to all values") # Wait for periodic save await asyncio.sleep(2.5) # Change 2 session.df['value'] = session.df['value'] * 2 session.record_operation(OperationType.TRANSFORM, {"operation": "double_values"}) await session.trigger_auto_save_if_needed() print(" Doubled all values (triggered immediate save)") # Wait for another periodic save await asyncio.sleep(2.5) # Stop periodic saves await session.auto_save_manager.stop_periodic_save() print("\n✓ Stopped periodic saves") # Check final file df_final = pd.read_csv(original_file) print(f"\nFinal file content:\n{df_final}") return original_file async def main(): """Run all examples.""" # Example 1: Simple overwrite file1 = await overwrite_same_file_example() # Example 2: Hybrid mode with overwrite file2 = await hybrid_example_with_overwrite() print("\n" + "=" * 60) print("✅ All examples completed!") print("=" * 60) print("\nKey Takeaways:") print("• Use strategy='overwrite' to update the same file") print("• Original file path must be provided when loading data") print("• No backup copies are created with overwrite strategy") print("• Works with all modes: after_operation, periodic, hybrid") print("\nFor production use, consider:") print("• Backup strategy for safety (creates copies)") print("• Overwrite strategy for direct updates") print("• Hybrid mode for maximum protection") if __name__ == "__main__": asyncio.run(main())