eamco_auto_api/app/script/fuel_estimator.py

from sqlalchemy.orm import Session
from sqlalchemy import func
from datetime import date, timedelta
from decimal import Decimal

# Import your existing database models
from app.models.auto import Auto_Delivery, Auto_Temp, Auto_Update, Tickets_Auto_Delivery

# --- Constants for the Model ---
# This is a baseline daily usage for homes that use oil for hot water.
# A typical value is 0.5 to 1.0 gallons per day. Adjust as needed.
HOT_WATER_DAILY_USAGE = Decimal('0.7') 

# This determines how quickly the K-Factor adjusts. 
# 0.7 means 70% weight is given to the historical factor and 30% to the new one.
# This prevents wild swings from a single unusual delivery period.
K_FACTOR_SMOOTHING_WEIGHT = Decimal('0.7') 


class FuelEstimator:
    def __init__(self, session: Session):
        self.session = session

    def _get_weather_for_date(self, target_date: date) -> Auto_Temp | None:
        """Helper to fetch weather data for a specific date."""
        return self.session.query(Auto_Temp).filter(Auto_Temp.todays_date == target_date).first()

    def run_daily_update(self):
        """
        Main function to run once per day. It updates the estimated fuel level
        for all active automatic delivery customers. The calling function must commit the session.
        """
        today = date.today()

        # 1. Check if the update has already run today
        if self.session.query(Auto_Update).filter(Auto_Update.last_updated == today).first():
            print(f"Daily update for {today} has already been completed.")
            return {"ok": True, "message": "Update already run today."}

        # 2. Get today's weather data (specifically the Heating Degree Days)
        todays_weather = self._get_weather_for_date(today)
        if not todays_weather:
            print(f"Error: Weather data for {today} not found. Cannot run update.")
            return {"ok": False, "message": f"Weather data for {today} not found."}

        # Degree days can't be negative for this calculation. If it's warm, HDD is 0.
        degree_day = Decimal(max(0, todays_weather.degree_day))

        # 3. Get all active automatic customers
        auto_customers = self.session.query(Auto_Delivery).filter(
            Auto_Delivery.auto_status == 1 # Assuming 1 means active
        ).all()

        if not auto_customers:
            print("No active automatic delivery customers found.")
            return {"ok": True, "message": "No active customers to update."}
            
        print(f"Staging daily fuel update for {len(auto_customers)} customers...")
        
        # 4. Loop through each customer and update their fuel level
        for customer in auto_customers:
            heating_usage = customer.house_factor * degree_day
            
            hot_water_usage = Decimal('0.0')
            if customer.hot_water_summer == 1:
                hot_water_usage = HOT_WATER_DAILY_USAGE
            
            gallons_used_today = heating_usage + hot_water_usage
            
            customer.estimated_gallons_left_prev_day = customer.estimated_gallons_left
            new_estimated_gallons = customer.estimated_gallons_left - gallons_used_today
            customer.estimated_gallons_left = max(Decimal('0.0'), new_estimated_gallons)
            customer.last_updated = today
            if customer.days_since_last_fill is not None:
                 customer.days_since_last_fill += 1

        # 5. Log that today's update is complete
        new_update_log = Auto_Update(last_updated=today)
        self.session.add(new_update_log)
        
        print("Daily update staged. Awaiting commit.")
        return {"ok": True, "message": f"Successfully staged updates for {len(auto_customers)} customers."}

    def refine_factor_after_delivery(self, ticket: Tickets_Auto_Delivery):
        """
        This is the self-correction logic. It recalculates and refines the customer's
        K-Factor (house_factor) after a delivery. The calling function must commit the session.
        """
        customer = self.session.query(Auto_Delivery).filter(
            Auto_Delivery.customer_id == ticket.customer_id
        ).first()

        if not customer or not customer.last_fill:
            print(f"Cannot refine K-Factor: Customer {ticket.customer_id} not found or has no previous fill date. Resetting tank only.")
            self._update_tank_after_fill(customer, ticket)
            return

        start_date = customer.last_fill
        end_date = ticket.fill_date
        
        if start_date >= end_date:
            print(f"Cannot refine K-Factor for customer {ticket.customer_id}: New fill date is not after the last one. Resetting tank only.")
            self._update_tank_after_fill(customer, ticket)
            return

        total_hdd_result = self.session.query(func.sum(Auto_Temp.degree_day)).filter(
            Auto_Temp.todays_date > start_date,
            Auto_Temp.todays_date <= end_date,
            Auto_Temp.degree_day > 0
        ).scalar()
        
        total_hdd = Decimal(total_hdd_result or 0)
        
        total_hot_water_usage = Decimal('0.0')
        if customer.hot_water_summer == 1:
            num_days = (end_date - start_date).days
            total_hot_water_usage = Decimal(num_days) * HOT_WATER_DAILY_USAGE

        gallons_for_heating = ticket.gallons_delivered - total_hot_water_usage
        if gallons_for_heating <= 0 or total_hdd == 0:
            print(f"Cannot calculate new K-Factor for customer {ticket.customer_id}. (HDD: {total_hdd}, Heating Gallons: {gallons_for_heating}). Resetting tank only.")
            self._update_tank_after_fill(customer, ticket)
            return
            
        new_k_factor = gallons_for_heating / total_hdd
        
        current_k_factor = customer.house_factor
        smoothed_k_factor = (current_k_factor * K_FACTOR_SMOOTHING_WEIGHT) + (new_k_factor * (Decimal('1.0') - K_FACTOR_SMOOTHING_WEIGHT))

        print(f"Refining K-Factor for Customer ID {customer.customer_id}:")
        print(f"  - Old K-Factor: {current_k_factor:.4f}, New Smoothed K-Factor: {smoothed_k_factor:.4f}")

        customer.house_factor = smoothed_k_factor
        self._update_tank_after_fill(customer, ticket)
        
        print(f"K-Factor and tank status for Customer {customer.customer_id} staged for update.")

    def _update_tank_after_fill(self, customer: Auto_Delivery, ticket: Tickets_Auto_Delivery):
        """Helper to reset customer tank status after a fill-up."""
        customer.last_fill = ticket.fill_date
        customer.days_since_last_fill = 0
        
        # A "fill-up" means the tank is full. This is critical for accuracy.
        if customer.tank_size and Decimal(customer.tank_size) > 0:
            customer.estimated_gallons_left = Decimal(customer.tank_size)
        else:
            # Default to a common tank size if not specified, e.g., 275
            customer.estimated_gallons_left = Decimal('275.0')
        
        # The previous day's value should match the new full value on a fill day.
        customer.estimated_gallons_left_prev_day = customer.estimated_gallons_left
        customer.last_updated = date.today()
        customer.auto_status = 1 # Reactivate the customer