import random
from typing import List
from dataclasses import dataclass


@dataclass
class Prediction:
    predicted_price: float
    confidence_score: float
    similar_listings: List[float]


class HousePricePredictor:
    """
    Mock ML model that predicts house prices.
    In a real scenario, this would load a trained model.
    """

    def __init__(self):
        # Mock initialization - in reality would load model weights
        pass

    def predict(
        self, square_feet: float, bedrooms: int, bathrooms: float
    ) -> Prediction:
        """
        Mock prediction method that returns:
        - predicted price
        - confidence score
        - similar listing prices
        """
        # Mock prediction logic
        base_price = square_feet * 200
        bedroom_value = bedrooms * 25000
        bathroom_value = bathrooms * 15000

        predicted_price = base_price + bedroom_value + bathroom_value

        # Add some randomness to make it interesting
        confidence_score = random.uniform(0.8, 0.99)
        similar_listings = [
            predicted_price * random.uniform(0.9, 1.1) for _ in range(3)
        ]

        return Prediction(predicted_price, confidence_score, similar_listings)