#!/usr/bin/env python3
"""
Script para enriquecer datos técnicos de motores
1. Parsea nombres de motor para extraer: cilindrada, cilindros, tipo combustible
2. Opcionalmente usa NHTSA API para datos adicionales
"""

import sqlite3
import re
import json
import urllib.request
import time
from pathlib import Path

DB_PATH = Path(__file__).parent.parent / 'vehicle_database.db'

def parse_engine_name(name):
    """
    Extrae datos técnicos del nombre del motor.
    Ejemplos:
        "2.5L 4-Cylinder" -> displacement_cc=2500, cylinders=4
        "3.5L V6 DOHC" -> displacement_cc=3500, cylinders=6
        "1.5L Turbo I4" -> displacement_cc=1500, cylinders=4, turbo=True
        "5.0L V8 Supercharged" -> displacement_cc=5000, cylinders=8
    """
    result = {
        'displacement_cc': None,
        'cylinders': None,
        'fuel_type': None,
        'is_turbo': False,
        'is_supercharged': False,
        'engine_config': None
    }

    if not name:
        return result

    name_upper = name.upper()

    # Extract displacement (e.g., "2.5L", "2500cc", "2.5 L", "2.5-liter")
    displacement_patterns = [
        r'(\d+\.?\d*)\s*L(?:ITER)?(?:\s|$|-)',  # 2.5L, 2.5 L, 2.5-liter
        r'(\d+\.?\d*)\s*-?\s*L(?:ITER)?',        # 2.5L, 2.5-L
        r'(\d{3,4})\s*CC',                        # 2500cc
    ]

    for pattern in displacement_patterns:
        match = re.search(pattern, name_upper)
        if match:
            value = float(match.group(1))
            if value < 20:  # It's in liters
                result['displacement_cc'] = int(value * 1000)
            else:  # It's in cc
                result['displacement_cc'] = int(value)
            break

    # Extract cylinders
    cylinder_patterns = [
        r'(\d+)\s*-?\s*CYL(?:INDER)?',           # 4-Cylinder, 4 Cyl
        r'V\s*-?\s*(\d+)',                        # V6, V-8
        r'I\s*-?\s*(\d+)',                        # I4, I-4
        r'INLINE\s*-?\s*(\d+)',                   # Inline-4
        r'FLAT\s*-?\s*(\d+)',                     # Flat-6
        r'H\s*-?\s*(\d+)',                        # H4 (boxer)
        r'W\s*-?\s*(\d+)',                        # W12
    ]

    for pattern in cylinder_patterns:
        match = re.search(pattern, name_upper)
        if match:
            result['cylinders'] = int(match.group(1))
            break

    # Detect engine configuration
    if 'V6' in name_upper or 'V8' in name_upper or 'V10' in name_upper or 'V12' in name_upper:
        match = re.search(r'V(\d+)', name_upper)
        if match:
            result['engine_config'] = f'V{match.group(1)}'
    elif re.search(r'I[- ]?\d|INLINE', name_upper):
        result['engine_config'] = 'Inline'
    elif 'FLAT' in name_upper or re.search(r'H[- ]?\d', name_upper):
        result['engine_config'] = 'Flat/Boxer'
    elif 'W12' in name_upper or 'W16' in name_upper:
        result['engine_config'] = 'W'
    elif 'ROTARY' in name_upper:
        result['engine_config'] = 'Rotary'

    # Detect turbo/supercharger
    if 'TURBO' in name_upper or 'T-GDI' in name_upper or 'TFSI' in name_upper or 'TSI' in name_upper:
        result['is_turbo'] = True
    if 'SUPERCHARGE' in name_upper or 'KOMPRESSOR' in name_upper:
        result['is_supercharged'] = True

    # Detect fuel type
    if 'DIESEL' in name_upper or 'TDI' in name_upper or 'CDI' in name_upper or 'HDI' in name_upper:
        result['fuel_type'] = 'diesel'
    elif 'ELECTRIC' in name_upper or 'EV' in name_upper or 'BATTERY' in name_upper:
        result['fuel_type'] = 'electric'
    elif 'HYBRID' in name_upper or 'HEV' in name_upper or 'PHEV' in name_upper:
        result['fuel_type'] = 'hybrid'
    elif 'FLEX' in name_upper or 'E85' in name_upper:
        result['fuel_type'] = 'other'  # Flex fuel
    else:
        # Default to gasoline for most engines
        if result['displacement_cc'] or result['cylinders']:
            result['fuel_type'] = 'gasoline'

    return result


def estimate_power(displacement_cc, cylinders, is_turbo, fuel_type):
    """
    Estima potencia aproximada basada en características del motor.
    Estos son valores aproximados típicos.
    """
    if not displacement_cc:
        return None

    # Base HP per liter (naturally aspirated gasoline)
    hp_per_liter = 70  # Average modern engine

    # Adjustments
    if fuel_type == 'diesel':
        hp_per_liter = 50
    elif fuel_type == 'electric':
        return None  # Can't estimate electric motor power this way

    if is_turbo:
        hp_per_liter *= 1.35  # Turbo adds ~35% power

    # Calculate base power
    liters = displacement_cc / 1000
    estimated_hp = int(liters * hp_per_liter)

    # Round to nearest 5
    return round(estimated_hp / 5) * 5


def estimate_torque(displacement_cc, power_hp, is_turbo, fuel_type):
    """
    Estima torque aproximado basada en potencia y tipo de motor.
    """
    if not power_hp:
        return None

    # Torque/HP ratio varies by engine type
    if fuel_type == 'diesel':
        ratio = 2.0  # Diesel engines have higher torque per HP
    elif is_turbo:
        ratio = 1.2  # Turbo engines have good torque
    else:
        ratio = 1.0  # NA gasoline

    # Estimate torque in lb-ft, then convert to Nm
    torque_lb_ft = power_hp * ratio
    torque_nm = int(torque_lb_ft * 1.3558)

    # Round to nearest 5
    return round(torque_nm / 5) * 5


def update_engines_from_parsing():
    """
    Actualiza la tabla engines parseando los nombres.
    """
    conn = sqlite3.connect(DB_PATH)
    conn.row_factory = sqlite3.Row
    cursor = conn.cursor()

    # Get all engines that need updating
    cursor.execute("""
        SELECT id, name, displacement_cc, cylinders, fuel_type, power_hp, torque_nm
        FROM engines
        WHERE (displacement_cc IS NULL OR cylinders IS NULL OR fuel_type IS NULL)
    """)

    engines = cursor.fetchall()
    print(f"Found {len(engines)} engines to process...")

    updated = 0
    for engine in engines:
        parsed = parse_engine_name(engine['name'])

        # Only update if we found new data
        updates = []
        params = []

        if parsed['displacement_cc'] and not engine['displacement_cc']:
            updates.append('displacement_cc = ?')
            params.append(parsed['displacement_cc'])

        if parsed['cylinders'] and not engine['cylinders']:
            updates.append('cylinders = ?')
            params.append(parsed['cylinders'])

        if parsed['fuel_type'] and not engine['fuel_type']:
            updates.append('fuel_type = ?')
            params.append(parsed['fuel_type'])

        # Estimate power and torque if we have enough data
        displacement = parsed['displacement_cc'] or engine['displacement_cc']
        cylinders = parsed['cylinders'] or engine['cylinders']
        fuel_type = parsed['fuel_type'] or engine['fuel_type']

        if displacement and not engine['power_hp']:
            estimated_hp = estimate_power(displacement, cylinders, parsed['is_turbo'], fuel_type)
            if estimated_hp:
                updates.append('power_hp = ?')
                params.append(estimated_hp)

                # Also estimate torque
                if not engine['torque_nm']:
                    estimated_torque = estimate_torque(displacement, estimated_hp, parsed['is_turbo'], fuel_type)
                    if estimated_torque:
                        updates.append('torque_nm = ?')
                        params.append(estimated_torque)

        if updates:
            params.append(engine['id'])
            cursor.execute(f"""
                UPDATE engines SET {', '.join(updates)} WHERE id = ?
            """, params)
            updated += 1

            if updated % 1000 == 0:
                print(f"  Updated {updated} engines...")
                conn.commit()

    conn.commit()
    print(f"\nTotal updated: {updated} engines")

    # Show sample results
    print("\n=== Sample Results ===")
    cursor.execute("""
        SELECT name, displacement_cc, cylinders, fuel_type, power_hp, torque_nm
        FROM engines
        WHERE displacement_cc IS NOT NULL
        LIMIT 10
    """)
    for row in cursor.fetchall():
        print(f"  {row['name']}: {row['displacement_cc']}cc, {row['cylinders']} cyl, "
              f"{row['fuel_type']}, {row['power_hp']}HP, {row['torque_nm']}Nm")

    conn.close()
    return updated


def get_stats():
    """Muestra estadísticas de cobertura de datos."""
    conn = sqlite3.connect(DB_PATH)
    cursor = conn.cursor()

    print("\n=== Data Coverage Statistics ===")

    cursor.execute("SELECT COUNT(*) FROM engines")
    total = cursor.fetchone()[0]
    print(f"Total engines: {total}")

    fields = ['displacement_cc', 'cylinders', 'fuel_type', 'power_hp', 'torque_nm']
    for field in fields:
        cursor.execute(f"SELECT COUNT(*) FROM engines WHERE {field} IS NOT NULL")
        count = cursor.fetchone()[0]
        pct = (count / total * 100) if total > 0 else 0
        print(f"  {field}: {count} ({pct:.1f}%)")

    conn.close()


if __name__ == '__main__':
    import sys

    print("=" * 50)
    print("Engine Data Enrichment Script")
    print("=" * 50)

    # Show current stats
    get_stats()

    if len(sys.argv) > 1 and sys.argv[1] == '--dry-run':
        print("\n=== Dry Run - Testing Parser ===")
        test_names = [
            "2.5L 4-Cylinder",
            "3.5L V6 DOHC",
            "1.5L Turbo I4",
            "5.0L V8 Supercharged",
            "2.0L TDI Diesel",
            "Electric Motor",
            "1.8T TSI",
            "3.0L Twin Turbo V6",
            "6.2L V8 HEMI",
            "2.4L DOHC 16-Valve",
        ]
        for name in test_names:
            result = parse_engine_name(name)
            hp = estimate_power(result['displacement_cc'], result['cylinders'],
                               result['is_turbo'], result['fuel_type'])
            print(f"\n  '{name}':")
            print(f"    -> {result['displacement_cc']}cc, {result['cylinders']} cyl, "
                  f"{result['fuel_type']}, turbo={result['is_turbo']}, est. {hp}HP")
    else:
        print("\n" + "=" * 50)
        print("Updating engines from name parsing...")
        print("=" * 50)

        update_engines_from_parsing()

        # Show final stats
        get_stats()