"""
VIMS Core — Database Manager

Hanterar databas per instans/ämne.
"""

import sqlite3
import json
from pathlib import Path
from typing import List, Dict, Optional
from datetime import datetime


class VIMSDatabase:
    """
    Databas-hanterare för VIMS-instanser.
    
    Usage:
        db = VIMSDatabase("atm-monitoring")
        db.create_schema()
        db.add_detection(atm_id="ATM-001", anomaly_type="skimming", confidence=0.94)
    """
    
    def __init__(self, topic: str, db_dir: str = "data"):
        self.topic = topic
        self.table_prefix = topic.replace("-", "_")
        self.db_path = Path(db_dir) / f"{topic}.db"
        self.db_path.parent.mkdir(parents=True, exist_ok=True)
    
    def _connect(self):
        """Skapa databas-anslutning."""
        conn = sqlite3.connect(str(self.db_path))
        conn.row_factory = sqlite3.Row
        return conn
    
    def create_schema(self, anomaly_classes: List[str]):
        """
        Skapa databas-schema för ämne.
        
        Args:
            anomaly_classes: Lista med anomaliklasser
        """
        conn = self._connect()
        cursor = conn.cursor()
        
        # Huvudtabell för detektioner
        cursor.execute(f"""
            CREATE TABLE IF NOT EXISTS {self.table_prefix}_detections (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                asset_id TEXT NOT NULL,
                image_path TEXT,
                anomaly_type TEXT NOT NULL,
                confidence REAL,
                severity INTEGER,
                bbox TEXT,
                detected_at DATETIME DEFAULT CURRENT_TIMESTAMP,
                verified BOOLEAN DEFAULT FALSE,
                status TEXT DEFAULT 'open',
                metadata TEXT
            )
        """)
        
        # Assets-tabell
        cursor.execute(f"""
            CREATE TABLE IF NOT EXISTS {self.table_prefix}_assets (
                id TEXT PRIMARY KEY,
                name TEXT,
                location TEXT,
                status TEXT DEFAULT 'active',
                last_check DATETIME,
                created_at DATETIME DEFAULT CURRENT_TIMESTAMP
            )
        """)
        
        # Alerts-tabell
        cursor.execute(f"""
            CREATE TABLE IF NOT EXISTS {self.table_prefix}_alerts (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                detection_id INTEGER,
                severity INTEGER,
                message TEXT,
                sent_at DATETIME,
                status TEXT DEFAULT 'pending',
                FOREIGN KEY (detection_id) REFERENCES {self.table_prefix}_detections(id)
            )
        """)
        
        # Index
        cursor.execute(f"""
            CREATE INDEX IF NOT EXISTS idx_{self.table_prefix}_detections_asset 
            ON {self.table_prefix}_detections(asset_id)
        """)
        cursor.execute(f"""
            CREATE INDEX IF NOT EXISTS idx_{self.table_prefix}_detections_type 
            ON {self.table_prefix}_detections(anomaly_type)
        """)
        cursor.execute(f"""
            CREATE INDEX IF NOT EXISTS idx_{self.table_prefix}_detections_status 
            ON {self.table_prefix}_detections(status)
        """)
        
        conn.commit()
        conn.close()
        
        print(f"Schema created for {self.topic}")
    
    def add_detection(
        self,
        asset_id: str,
        anomaly_type: str,
        confidence: float,
        severity: int,
        image_path: Optional[str] = None,
        bbox: Optional[List[float]] = None,
        metadata: Optional[Dict] = None
    ) -> int:
        """
        Lägg till ny detektion.
        
        Returns:
            ID för insatt rad
        """
        conn = self._connect()
        cursor = conn.cursor()
        
        cursor.execute(f"""
            INSERT INTO {self.table_prefix}_detections 
            (asset_id, image_path, anomaly_type, confidence, severity, bbox, metadata)
            VALUES (?, ?, ?, ?, ?, ?, ?)
        """, (
            asset_id,
            image_path,
            anomaly_type,
            confidence,
            severity,
            json.dumps(bbox) if bbox else None,
            json.dumps(metadata) if metadata else None
        ))
        
        detection_id = cursor.lastrowid
        
        # Skapa alert om severity >= 4
        if severity >= 4:
            cursor.execute(f"""
                INSERT INTO {self.table_prefix}_alerts 
                (detection_id, severity, message)
                VALUES (?, ?, ?)
            """, (
                detection_id,
                severity,
                f"Critical {anomaly_type} detected on {asset_id}"
            ))
        
        conn.commit()
        conn.close()
        
        return detection_id
    
    def get_detections(
        self,
        asset_id: Optional[str] = None,
        status: Optional[str] = None,
        limit: int = 100
    ) -> List[Dict]:
        """Hämta detektioner med filter."""
        conn = self._connect()
        cursor = conn.cursor()
        
        query = f"SELECT * FROM {self.table_prefix}_detections WHERE 1=1"
        params = []
        
        if asset_id:
            query += " AND asset_id = ?"
            params.append(asset_id)
        if status:
            query += " AND status = ?"
            params.append(status)
        
        query += " ORDER BY detected_at DESC LIMIT ?"
        params.append(limit)
        
        cursor.execute(query, params)
        rows = cursor.fetchall()
        
        conn.close()
        
        return [dict(row) for row in rows]
    
    def get_stats(self) -> Dict:
        """Hämta statistik för ämne."""
        conn = self._connect()
        cursor = conn.cursor()
        
        cursor.execute(f"""
            SELECT 
                COUNT(*) as total_detections,
                COUNT(DISTINCT asset_id) as assets_monitored,
                COUNT(CASE WHEN status = 'open' THEN 1 END) as open_anomalies,
                MAX(severity) as max_severity
            FROM {self.table_prefix}_detections
        """)
        
        row = cursor.fetchone()
        conn.close()
        
        return dict(row) if row else {}
    
    def verify_detection(self, detection_id: int, verdict: str, notes: str = ""):
        """Verifiera detektion manuellt."""
        conn = self._connect()
        cursor = conn.cursor()
        
        cursor.execute(f"""
            UPDATE {self.table_prefix}_detections 
            SET verified = TRUE, status = ?
            WHERE id = ?
        """, (verdict, detection_id))
        
        conn.commit()
        conn.close()