"""
Script to fix InfluxDB schema collision by recreating measurements with consistent data types
"""

from influxdb_client import InfluxDBClient, Point, WritePrecision
from datetime import datetime, timedelta
import time

def fix_influxdb_schema():
    # InfluxDB configuration
    url = "http://localhost:8086"
    token = "kNFfXEpPQoWrk5Tteowda21Dzv6xD3jY7QHSHHQHb5oYW6VH6mkAgX9ZMjQJkaHHa8FwzmyVFqDG7qqzxN09uQ=="
    org = "smart-intersection-org"
    bucket = "traffic_monitoring"
    
    try:
        print("Connecting to InfluxDB...")
        client = InfluxDBClient(url=url, token=token, org=org)
        write_api = client.write_api()
        
        print("Clearing potentially problematic measurements...")
        
        # Delete recent traffic_light_status and violation_events data to fix schema collision
        delete_api = client.delete_api()
        
        # Delete traffic light data from last 24 hours
        start = datetime.utcnow() - timedelta(days=1)
        stop = datetime.utcnow()
        
        try:
            delete_api.delete(start, stop, '_measurement="traffic_light_status"', bucket=bucket, org=org)
            print("✅ Cleared traffic_light_status measurement")
        except Exception as e:
            print(f"Note: {e}")
        
        try:
            delete_api.delete(start, stop, '_measurement="violation_events"', bucket=bucket, org=org)
            print("✅ Cleared violation_events measurement")
        except Exception as e:
            print(f"Note: {e}")
        
        try:
            delete_api.delete(start, stop, '_measurement="device_info"', bucket=bucket, org=org)
            print("✅ Cleared device_info measurement")
        except Exception as e:
            print(f"Note: {e}")
        
        print("\nWaiting 3 seconds for deletions to process...")
        time.sleep(3)
        
        print("Creating new measurements with consistent data types...")
        
        # Device info with consistent types
        device_point = Point("device_info") \
            .tag("device_id", "smart_intersection_001") \
            .tag("camera_id", "camera_001") \
            .field("status", "online") \
            .field("location", "Main Intersection") \
            .field("version", "1.0.0") \
            .field("uptime_seconds", 3600.0) \
            .time(datetime.utcnow())
        
        # Traffic light status with consistent types
        traffic_light_point = Point("traffic_light_status") \
            .tag("device_id", "smart_intersection_001") \
            .tag("camera_id", "camera_001") \
            .tag("color", "red") \
            .field("color_numeric", 1) \
            .field("confidence", 0.85) \
            .time(datetime.utcnow())
        
        # Violation event with consistent types
        violation_point = Point("violation_events") \
            .tag("device_id", "smart_intersection_001") \
            .tag("camera_id", "camera_001") \
            .tag("violation_type", "red_light_violation") \
            .field("vehicle_id", "test_vehicle_001") \
            .field("count", 1) \
            .field("confidence", 0.95) \
            .time(datetime.utcnow())
        
        # Write all points
        points = [device_point, traffic_light_point, violation_point]
        write_api.write(bucket=bucket, org=org, record=points)
        
        print("✅ New measurements created with consistent data types")
        print("✅ Schema collision should now be resolved")
        print("\nPlease check your Grafana dashboard now!")
        
    except Exception as e:
        print(f"❌ Error fixing schema: {e}")
    finally:
        if 'client' in locals():
            client.close()

if __name__ == "__main__":
    fix_influxdb_schema()