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app/script/fuel_estimator_customer.py

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+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.customer import Customer_estimate_gallons, Customer_Update
+from app.models.delivery import Delivery
+from app.models.auto import Auto_Temp
+
+# --- 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('1.0')
+
+# 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')
+
+TANK_MAX_FILLS = {
+    275: 240,
+    330: 280,
+    500: 475,
+    550: 500
+}
+
+PARTIAL_DELIVERIES = [100, 125, 150, 200]
+
+
+class FuelEstimatorCustomer:
+    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 _estimate_initial_house_factor(self, customer: Customer_estimate_gallons) -> Decimal:
+        """
+        Generic function to estimate initial house factor for customers with only one delivery.
+        This can be improved with more sophisticated logic (e.g., averaging similar customers).
+        """
+        # Default generic house factor: 0.12 gallons per degree day (average based on existing customer data)
+        # This represents typical heating usage and can be adjusted based on future data analysis
+        return Decimal('0.12')
+
+    def _verify_house_factor_correctness(self, customer: Customer_estimate_gallons) -> bool:
+        """
+        Verify and correct house_factor based on delivery history.
+        Returns True if correction was made.
+        """
+        # Count deliveries for this customer
+        delivery_count = self.session.query(func.count(Delivery.id)).filter(
+            Delivery.customer_id == customer.customer_id
+        ).scalar()
+
+        corrected = False
+
+        if delivery_count <= 1:
+            # Customers with 0 or 1 delivery should have house_factor = 0.12 (initial average)
+            if customer.house_factor != Decimal('0.12'):
+                print(f"Correcting house_factor for customer {customer.customer_id} from {customer.house_factor} to 0.12 (1 or fewer deliveries)")
+                customer.house_factor = Decimal('0.12')
+                corrected = True
+        # For customers with 2+ deliveries, keep their calculated factor (no correction needed)
+
+        return corrected
+
+    def run_daily_update(self):
+        """
+        Main function to run once per day. It updates the estimated fuel level
+        for all active regular customers. The calling function must commit the session.
+        """
+        today = date.today()
+
+        # 1. Check if the update has already run today
+        if self.session.query(Customer_Update).filter(Customer_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 = 0.
+        degree_day = Decimal(max(0, 65 - float(todays_weather.temp_avg)))
+
+        # 3. Get all active regular customers
+        customer_estimates = self.session.query(Customer_estimate_gallons).filter(
+            Customer_estimate_gallons.auto_status == 1 # Assuming 1 means active
+        ).all()
+
+        if not customer_estimates:
+            print("No active regular delivery customers found.")
+            return {"ok": True, "message": "No active customers to update."}
+
+        print(f"Staging daily fuel update for {len(customer_estimates)} customers...")
+
+        corrections_made = 0
+
+        # 4. Loop through each customer and update their fuel level
+        for customer in customer_estimates:
+            # Verify and correct house_factor if needed
+            if self._verify_house_factor_correctness(customer):
+                corrections_made += 1
+
+            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 = Customer_Update(last_updated=today)
+        self.session.add(new_update_log)
+
+        print("Daily update staged. Awaiting commit.")
+        message = f"Successfully staged updates for {len(customer_estimates)} customers."
+        if corrections_made > 0:
+            message += f" Corrected house factors for {corrections_made} customers."
+
+        return {"ok": True, "message": message}
+
+    def refine_factor_after_delivery(self, delivery: 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(Customer_estimate_gallons).filter(
+            Customer_estimate_gallons.customer_id == delivery.customer_id
+        ).first()
+
+        if not customer:
+            print(f"Customer {delivery.customer_id} not found.")
+            return
+
+        if not customer.last_fill:
+            print(f"Setting initial K-Factor for new customer {delivery.customer_id} with only one delivery.")
+            customer.house_factor = self._estimate_initial_house_factor(customer)
+            self._update_tank_after_fill(customer, delivery)
+            return
+
+        start_date = customer.last_fill
+        end_date = delivery.when_delivered
+
+        if start_date >= end_date:
+            print(f"Cannot refine K-Factor for customer {delivery.customer_id}: New fill date is not after the last one. Resetting tank only.")
+            self._update_tank_after_fill(customer, delivery)
+            return
+
+        interval_temps = self.session.query(Auto_Temp).filter(
+            Auto_Temp.todays_date > start_date,
+            Auto_Temp.todays_date <= end_date
+        ).all()
+        total_degree_days = sum(max(0, 65 - float(temp.temp_avg)) for temp in interval_temps)
+        total_hdd = Decimal(total_degree_days)
+
+        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 = delivery.gallons_delivered - total_hot_water_usage
+        if gallons_for_heating <= 0 or total_hdd == 0:
+            print(f"Cannot calculate new K-Factor for customer {delivery.customer_id}. (HDD: {total_hdd}, Heating Gallons: {gallons_for_heating}). Resetting tank only.")
+            self._update_tank_after_fill(customer, delivery)
+            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, delivery)
+
+        print(f"K-Factor and tank status for Customer {customer.customer_id} staged for update.")
+
+    def _update_tank_after_fill(self, customer: Customer_estimate_gallons, delivery: Delivery):
+        """Helper to update customer tank status after a fill-up or partial delivery."""
+        customer.last_fill = delivery.when_delivered
+        customer.days_since_last_fill = 0
+
+        # Determine max fill capacity
+        if customer.tank_size and Decimal(customer.tank_size) > 0:
+            tank_size = float(Decimal(customer.tank_size))
+            max_fill = TANK_MAX_FILLS.get(tank_size, tank_size)
+        else:
+            # Default to legal max for common tank size (275 gallons = 240)
+            max_fill = 240.0
+
+        # Check if this is a partial delivery
+        if float(delivery.gallons_delivered) in PARTIAL_DELIVERIES:
+            # Partial delivery: add to current level, cap at max_fill
+            customer.estimated_gallons_left += delivery.gallons_delivered
+            customer.estimated_gallons_left = min(customer.estimated_gallons_left, Decimal(str(max_fill)))
+        else:
+            # Full delivery: set to max_fill
+            customer.estimated_gallons_left = Decimal(str(max_fill))
+
+        # The previous day's value should match the new 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