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# 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
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