models/property_specs.py

# models/property_specs.py

from datetime import datetime
from .logging_config import logger

def verify_property_specs(data):
    """
    Verify property specifications for reasonableness and consistency.
    This function checks if the provided property details are within reasonable ranges
    for the Indian real estate market.
    """
    specs_verification = {
        'is_valid': True,
        'bedrooms_reasonable': True,
        'bathrooms_reasonable': True,
        'total_rooms_reasonable': True,
        'year_built_reasonable': True,
        'parking_reasonable': True,
        'sq_ft_reasonable': True,
        'market_value_reasonable': True,
        'issues': []
    }

    try:
        # Helper function to safely convert values
        def safe_float_convert(value, default=0.0):
            try:
                if value is None:
                    return default
                if isinstance(value, (int, float)):
                    return float(value)
                if isinstance(value, str):
                    return float(value.replace(',', '').replace('₹', '').strip())
                return default
            except (ValueError, TypeError) as e:
                logger.warning(f"safe_float_convert error: {str(e)}")
                return default

        def safe_int_convert(value, default=0):
            try:
                if value is None:
                    return default
                if isinstance(value, (int, float)):
                    return int(value)
                if isinstance(value, str):
                    return int(float(value.replace(',', '').strip()))
                return default
            except (ValueError, TypeError) as e:
                logger.warning(f"safe_int_convert error: {str(e)}")
                return default

        # Validate property type
        valid_property_types = [
            'Apartment', 'House', 'Villa', 'Independent House', 'Independent Villa',
            'Studio', 'Commercial', 'Office', 'Shop', 'Warehouse', 'Industrial'
        ]

        property_type = str(data.get('property_type', '')).strip()
        if not property_type or property_type not in valid_property_types:
            specs_verification['is_valid'] = False
            specs_verification['issues'].append(f"Invalid property type: {property_type if property_type else 'Not specified'}")

        # Validate bedrooms
        if 'bedrooms' in data:
            bedrooms = safe_int_convert(data['bedrooms'])
            if property_type in ['Apartment', 'Studio']:
                if bedrooms > 5 or bedrooms < 0:
                    specs_verification['bedrooms_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid number of bedrooms for {property_type}: {bedrooms}. Should be between 0 and 5.")
            elif property_type in ['House', 'Villa', 'Independent House', 'Independent Villa']:
                if bedrooms > 8 or bedrooms < 0:
                    specs_verification['bedrooms_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid number of bedrooms for {property_type}: {bedrooms}. Should be between 0 and 8.")
            elif property_type in ['Commercial', 'Office', 'Shop', 'Warehouse', 'Industrial']:
                if bedrooms > 0:
                    specs_verification['bedrooms_reasonable'] = False
                    specs_verification['issues'].append(f"Commercial properties typically don't have bedrooms: {bedrooms}")

        # Validate bathrooms
        if 'bathrooms' in data:
            bathrooms = safe_float_convert(data['bathrooms'])
            if property_type in ['Apartment', 'Studio']:
                if bathrooms > 4 or bathrooms < 0:
                    specs_verification['bathrooms_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid number of bathrooms for {property_type}: {bathrooms}. Should be between 0 and 4.")
            elif property_type in ['House', 'Villa', 'Independent House', 'Independent Villa']:
                if bathrooms > 6 or bathrooms < 0:
                    specs_verification['bathrooms_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid number of bathrooms for {property_type}: {bathrooms}. Should be between 0 and 6.")
            elif property_type in ['Commercial', 'Office', 'Shop', 'Warehouse', 'Industrial']:
                if bathrooms > 0:
                    specs_verification['bathrooms_reasonable'] = False
                    specs_verification['issues'].append(f"Commercial properties typically don't have bathrooms: {bathrooms}")

        # Validate total rooms
        if 'total_rooms' in data:
            try:
                total_rooms = safe_int_convert(data['total_rooms'])
                if total_rooms < 0:
                    specs_verification['total_rooms_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid total rooms: {total_rooms}. Cannot be negative.")
                elif 'bedrooms' in data and 'bathrooms' in data:
                    bedrooms = safe_int_convert(data['bedrooms'])
                    bathrooms = safe_int_convert(data['bathrooms'])
                    if total_rooms < (bedrooms + bathrooms):
                        specs_verification['total_rooms_reasonable'] = False
                        specs_verification['issues'].append(f"Total rooms ({total_rooms}) is less than bedrooms + bathrooms ({bedrooms + bathrooms})")
            except Exception as e:
                logger.warning(f"Error validating total rooms: {str(e)}")
                specs_verification['total_rooms_reasonable'] = False
                specs_verification['issues'].append(f"Invalid total rooms data: must be a number ({str(e)})")

        # Validate parking
        if 'parking' in data:
            try:
                parking = safe_int_convert(data['parking'])
                if property_type in ['Apartment', 'Studio']:
                    if parking > 2 or parking < 0:
                        specs_verification['parking_reasonable'] = False
                        specs_verification['issues'].append(f"Invalid parking spaces for {property_type}: {parking}. Should be between 0 and 2.")
                elif property_type in ['House', 'Villa', 'Independent House', 'Independent Villa']:
                    if parking > 4 or parking < 0:
                        specs_verification['parking_reasonable'] = False
                        specs_verification['issues'].append(f"Invalid parking spaces for {property_type}: {parking}. Should be between 0 and 4.")
                elif property_type in ['Commercial', 'Office', 'Shop', 'Warehouse', 'Industrial']:
                    if parking < 0:
                        specs_verification['parking_reasonable'] = False
                        specs_verification['issues'].append(f"Invalid parking spaces: {parking}. Cannot be negative.")
            except Exception as e:
                logger.warning(f"Error validating parking: {str(e)}")
                specs_verification['parking_reasonable'] = False
                specs_verification['issues'].append(f"Invalid parking data: must be a number ({str(e)})")

        # Validate square footage
        if 'sq_ft' in data:
            try:
                sq_ft = safe_float_convert(data['sq_ft'])
                if sq_ft <= 0:
                    specs_verification['sq_ft_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid square footage: {sq_ft}. Must be greater than 0.")
                else:
                    if property_type in ['Apartment', 'Studio']:
                        if sq_ft > 5000:
                            specs_verification['sq_ft_reasonable'] = False
                            specs_verification['issues'].append(f"Square footage ({sq_ft}) seems unreasonably high for {property_type}")
                        elif sq_ft < 200:
                            specs_verification['sq_ft_reasonable'] = False
                            specs_verification['issues'].append(f"Square footage ({sq_ft}) seems unreasonably low for {property_type}")
                    elif property_type in ['House', 'Villa', 'Independent House', 'Independent Villa']:
                        if sq_ft > 10000:
                            specs_verification['sq_ft_reasonable'] = False
                            specs_verification['issues'].append(f"Square footage ({sq_ft}) seems unreasonably high for {property_type}")
                        elif sq_ft < 500:
                            specs_verification['sq_ft_reasonable'] = False
                            specs_verification['issues'].append(f"Square footage ({sq_ft}) seems unreasonably low for {property_type}")
            except Exception as e:
                logger.warning(f"Error validating square footage: {str(e)}")
                specs_verification['sq_ft_reasonable'] = False
                specs_verification['issues'].append(f"Invalid square footage data: must be a number ({str(e)})")

        # Validate market value
        if 'market_value' in data:
            try:
                market_value = safe_float_convert(data['market_value'])
                if market_value <= 0:
                    specs_verification['market_value_reasonable'] = False
                    specs_verification['issues'].append(f"Invalid market value: {market_value}. Must be greater than 0.")
                else:
                    if property_type in ['Apartment', 'Studio']:
                        if market_value > 500000000:  # 5 crore limit for apartments
                            specs_verification['market_value_reasonable'] = False
                            specs_verification['issues'].append(f"Market value (₹{market_value:,.2f}) seems unreasonably high for {property_type}")
                        elif market_value < 500000:  # 5 lakh minimum
                            specs_verification['market_value_reasonable'] = False
                            specs_verification['issues'].append(f"Market value (₹{market_value:,.2f}) seems unreasonably low for {property_type}")
                    elif property_type in ['House', 'Villa', 'Independent House', 'Independent Villa']:
                        if market_value > 2000000000:  # 20 crore limit for houses
                            specs_verification['market_value_reasonable'] = False
                            specs_verification['issues'].append(f"Market value (₹{market_value:,.2f}) seems unreasonably high for {property_type}")
                        elif market_value < 1000000:  # 10 lakh minimum
                            specs_verification['market_value_reasonable'] = False
                            specs_verification['issues'].append(f"Market value (₹{market_value:,.2f}) seems unreasonably low for {property_type}")
                    elif property_type in ['Commercial', 'Office', 'Shop']:
                        if market_value < 2000000:  # 20 lakh minimum
                            specs_verification['market_value_reasonable'] = False
                            specs_verification['issues'].append(f"Market value (₹{market_value:,.2f}) seems unreasonably low for {property_type}")
                    elif property_type in ['Warehouse', 'Industrial']:
                        if market_value < 5000000:  # 50 lakh minimum
                            specs_verification['market_value_reasonable'] = False
                            specs_verification['issues'].append(f"Market value (₹{market_value:,.2f}) seems unreasonably low for {property_type}")

                    # Check price per square foot
                    if 'sq_ft' in data and safe_float_convert(data['sq_ft']) > 0:
                        try:
                            sq_ft = safe_float_convert(data['sq_ft'])
                            price_per_sqft = market_value / sq_ft

                            if property_type in ['Apartment', 'Studio']:
                                if price_per_sqft < 1000:  # Less than ₹1000 per sq ft
                                    specs_verification['market_value_reasonable'] = False
                                    specs_verification['issues'].append(f"Price per sq ft (₹{price_per_sqft:,.2f}) seems unreasonably low for {property_type}")
                                elif price_per_sqft > 50000:  # More than ₹50k per sq ft
                                    specs_verification['market_value_reasonable'] = False
                                    specs_verification['issues'].append(f"Price per sq ft (₹{price_per_sqft:,.2f}) seems unreasonably high for {property_type}")
                            elif property_type in ['House', 'Villa', 'Independent House', 'Independent Villa']:
                                if price_per_sqft < 500:  # Less than ₹500 per sq ft
                                    specs_verification['market_value_reasonable'] = False
                                    specs_verification['issues'].append(f"Price per sq ft (₹{price_per_sqft:,.2f}) seems unreasonably low for {property_type}")
                                elif price_per_sqft > 100000:  # More than ₹1 lakh per sq ft
                                    specs_verification['market_value_reasonable'] = False
                                    specs_verification['issues'].append(f"Price per sq ft (₹{price_per_sqft:,.2f}) seems unreasonably high for {property_type}")
                        except Exception as e:
                            logger.warning(f"Error validating price per sq ft: {str(e)}")
            except Exception as e:
                logger.warning(f"Error validating market value: {str(e)}")
                specs_verification['market_value_reasonable'] = False
                specs_verification['issues'].append(f"Invalid market value data: must be a number ({str(e)})")

        # Calculate verification score
        try:
            valid_checks = sum([
                specs_verification['bedrooms_reasonable'],
                specs_verification['bathrooms_reasonable'],
                specs_verification['total_rooms_reasonable'],
                specs_verification['year_built_reasonable'],
                specs_verification['parking_reasonable'],
                specs_verification['sq_ft_reasonable'],
                specs_verification['market_value_reasonable']
            ])
            total_checks = 7
            specs_verification['verification_score'] = (valid_checks / total_checks) * 100
        except Exception as e:
            logger.error(f"Error calculating verification score: {str(e)}")
            specs_verification['verification_score'] = 0.0

        # Overall validity
        try:
            specs_verification['is_valid'] = all([
                specs_verification['bedrooms_reasonable'],
                specs_verification['bathrooms_reasonable'],
                specs_verification['total_rooms_reasonable'],
                specs_verification['year_built_reasonable'],
                specs_verification['parking_reasonable'],
                specs_verification['sq_ft_reasonable'],
                specs_verification['market_value_reasonable']
            ])
        except Exception as e:
            logger.error(f"Error calculating overall validity: {str(e)}")
            specs_verification['is_valid'] = False

    except Exception as e:
        logger.error(f"Error in property specs verification: {str(e)}")
        specs_verification['is_valid'] = False
        specs_verification['issues'].append(f"Error in verification: {str(e)}")

    return specs_verification