mirror of
https://github.com/DRYTRIX/TimeTracker.git
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350d7105a2
Implement a complete audit logging system to track all changes made to tracked entities, providing full compliance and accountability capabilities. Features: - Automatic tracking of create, update, and delete operations on 25+ models - Detailed field-level change tracking with old/new value comparison - User attribution with IP address, user agent, and request path logging - Web UI for viewing and filtering audit logs with pagination - REST API endpoints for programmatic access - Entity-specific history views - Comprehensive test coverage (unit, model, route, and smoke tests) Core Components: - AuditLog model with JSON-encoded value storage and decoding helpers - SQLAlchemy event listeners for automatic change detection - Audit utility module with defensive programming for table existence checks - Blueprint routes for audit log viewing and API access - Jinja2 templates for audit log list, detail, and entity history views - Database migration (044) creating audit_logs table with proper indexes Technical Implementation: - Uses SQLAlchemy 'after_flush' event listener to capture changes - Tracks 25+ models including Projects, Tasks, TimeEntries, Invoices, Clients, Users, etc. - Excludes sensitive fields (passwords) and system fields (id, timestamps) - Implements lazy import pattern to avoid circular dependencies - Graceful error handling to prevent audit logging from breaking core functionality - Transaction-safe logging that integrates with main application transactions Fixes: - Resolved login errors caused by premature transaction commits - Fixed circular import issues with lazy model loading - Added table existence checks to prevent errors before migrations - Improved error handling with debug-level logging for non-critical failures UI/UX: - Added "Audit Logs" link to admin dropdown menu - Organized admin menu into logical sections for better usability - Filterable audit log views by entity type, user, action, and date range - Color-coded action badges and side-by-side old/new value display - Pagination support for large audit log datasets Documentation: - Added comprehensive feature documentation - Included troubleshooting guide and data examples - Created diagnostic scripts for verifying audit log setup Testing: - Unit tests for AuditLog model and value encoding/decoding - Route tests for all audit log endpoints - Integration tests for audit logging functionality - Smoke tests for end-to-end audit trail verification This implementation provides a robust foundation for compliance tracking and change accountability without impacting application performance or requiring code changes in existing routes/models.
78 lines
2.9 KiB
Python
78 lines
2.9 KiB
Python
#!/usr/bin/env python
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"""Script to check and verify audit_logs table setup"""
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import sys
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import os
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# Add the parent directory to the path so we can import app
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sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
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from app import create_app, db
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from app.models.audit_log import AuditLog
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from sqlalchemy import inspect as sqlalchemy_inspect
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def check_audit_table():
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"""Check if audit_logs table exists and show status"""
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app = create_app()
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with app.app_context():
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print("=" * 60)
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print("Audit Logs Table Check")
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print("=" * 60)
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# Check if table exists
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try:
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inspector = sqlalchemy_inspect(db.engine)
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tables = inspector.get_table_names()
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if 'audit_logs' in tables:
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print("✓ audit_logs table EXISTS")
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# Check table structure
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columns = inspector.get_columns('audit_logs')
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print(f"\nTable has {len(columns)} columns:")
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for col in columns:
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print(f" - {col['name']} ({col['type']})")
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# Check indexes
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indexes = inspector.get_indexes('audit_logs')
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print(f"\nTable has {len(indexes)} indexes:")
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for idx in indexes:
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print(f" - {idx['name']}: {', '.join(idx['column_names'])}")
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# Count existing audit logs
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try:
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count = AuditLog.query.count()
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print(f"\n✓ Current audit log entries: {count}")
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if count > 0:
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# Show recent entries
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recent = AuditLog.query.order_by(AuditLog.created_at.desc()).limit(5).all()
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print("\nRecent audit log entries:")
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for log in recent:
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print(f" - {log.created_at}: {log.action} {log.entity_type}#{log.entity_id} by user#{log.user_id}")
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except Exception as e:
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print(f"\n⚠ Could not query audit logs: {e}")
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print(" This might indicate a schema mismatch.")
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else:
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print("✗ audit_logs table DOES NOT EXIST")
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print("\nTo create the table, run:")
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print(" flask db upgrade")
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print("\nOr manually apply migration:")
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print(" migrations/versions/044_add_audit_logs_table.py")
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except Exception as e:
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print(f"✗ Error checking table: {e}")
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import traceback
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traceback.print_exc()
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return False
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print("\n" + "=" * 60)
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return True
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if __name__ == '__main__':
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success = check_audit_table()
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sys.exit(0 if success else 1)
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