Files
eamco_auto_api/app/routers/fixstuff_customer.py
2026-01-05 08:43:40 -05:00

444 lines
20 KiB
Python

from fastapi import APIRouter
from fastapi.responses import JSONResponse
from fastapi.encoders import jsonable_encoder
from database import session
from sqlalchemy import func
from datetime import date
from decimal import Decimal
from app.models.customer import Customer_Customer, Customer_estimate_gallons
from app.models.delivery import Delivery
from app.models.auto import Auto_Temp
# Constants from fuel_estimator
HOT_WATER_DAILY_USAGE = Decimal('1.0')
K_FACTOR_SMOOTHING_WEIGHT = Decimal('0.7')
TUNING_FACTOR = Decimal('1.1')
# Maximum fill amounts for different tank sizes (gallons we can actually fill)
TANK_MAX_FILLS = {
275: 240,
330: 280,
500: 475,
550: 500
}
router = APIRouter(
prefix="/fixstuff_customer",
tags=["fixstuff_customer"],
responses={404: {"description": "Not found"}},
)
@router.get("/lastdelivered", status_code=200)
def fix_customer_last_delivered():
"""
Updates the last_fill date in the customer_estimate table for each customer
by finding the most recent completed delivery (delivery with non-NULL when_delivered)
from the delivery table, matched by customer_id and automatic == 0.
Returns statistics and a list of changes made.
"""
session.rollback() # Reset any aborted transaction state
customer_estimates = session.query(Customer_estimate_gallons).all()
changes = []
total_customers = len(customer_estimates)
deliveries_found = 0
updates_made = 0
for ce in customer_estimates:
latest_delivery = session.query(Delivery).filter(
Delivery.customer_id == ce.customer_id,
Delivery.automatic == 0,
Delivery.when_delivered.isnot(None)
).order_by(Delivery.when_delivered.desc()).first()
if latest_delivery:
deliveries_found += 1
if ce.last_fill != latest_delivery.when_delivered:
updates_made += 1
old_date = ce.last_fill
ce.last_fill = latest_delivery.when_delivered
changes.append({
"id": ce.id,
"customer_full_name": ce.customer_full_name,
"before_date": str(old_date) if old_date else None,
"new_date": str(latest_delivery.when_delivered)
})
session.add(ce)
session.commit()
result = {
"total_customers": total_customers,
"deliveries_found": deliveries_found,
"updates_made": updates_made,
"changes": changes
}
return JSONResponse(content=jsonable_encoder(result))
@router.get("/estimate_gallons/{update_db}", status_code=200)
def estimate_customer_gallons(update_db: int):
"""
Estimates current gallons for each regular customer based on delivery history and weather.
update_db: 0 for estimation only (no DB changes), 1 for estimation with DB updates.
No deliveries: assume 100 gallons. Single delivery: use weather for 2000 sq ft home.
Multiple deliveries: use historical average. Includes address and scaling factor.
When update_db=1, updates estimated_gallons_left and house_factor in database.
"""
session.rollback() # Reset any aborted transaction state
# Check if weather data is available
auto_temp_count = session.query(Auto_Temp).count()
if auto_temp_count == 0:
return JSONResponse(content={
"error": "Auto_Temp table is empty. Cannot perform fuel estimations without weather data.",
"solution": "Populate the Auto_Temp table with weather data first."
})
customer_estimates = session.query(Customer_estimate_gallons).all()
estimates = []
for ce in customer_estimates:
deliveries = session.query(Delivery).filter(
Delivery.customer_id == ce.customer_id,
Delivery.automatic == 0,
Delivery.when_delivered.isnot(None)
).order_by(Delivery.when_delivered).all()
# Get tank size and hot water setting
tank_size = Decimal(ce.tank_size) if ce.tank_size else Decimal('275')
# Use maximum fill amount (how much we can actually fill the tank)
tank_size_float = float(tank_size)
max_fill = TANK_MAX_FILLS.get(tank_size_float, tank_size_float)
effective_tank = Decimal(str(max_fill))
hot_water = ce.hot_water_summer == 1
calculated_scaling = None # For DB update
if not deliveries:
estimated_gallons = Decimal('100')
calculated_scaling = Decimal('0.12') # No deliveries = use average baseline
else:
last_fill = deliveries[-1].when_delivered
estimated_gallons_left = effective_tank
today = date.today()
if len(deliveries) == 1:
# Single delivery: use weather data for 2000 sq ft home, only heat when temp <=65
calculated_scaling = Decimal('0.12')
if last_fill < today:
# Get daily weather data
temp_days = session.query(Auto_Temp).filter(
Auto_Temp.todays_date > last_fill,
Auto_Temp.todays_date <= today
).all()
heating_usage = Decimal('0')
hot_water_usage = Decimal('0')
house_factor_2000_sqft = Decimal('0.12') # gallons per degree day (average)
for temp in temp_days:
degree_day = max(0, 65 - float(temp.temp_avg))
heating_usage += house_factor_2000_sqft * Decimal(degree_day)
if hot_water:
hot_water_usage += HOT_WATER_DAILY_USAGE
total_usage = heating_usage + hot_water_usage
estimated_gallons_left = max(Decimal('0'), estimated_gallons_left - total_usage)
else:
# Multiple deliveries: calculate house_factor (gallons per degree day)
calculated_scaling = Decimal('0.12') # Default average
daily_heating_usages = []
avg_degree_per_days = []
for i in range(len(deliveries) - 1):
prev_delivery = deliveries[i]
next_delivery = deliveries[i + 1]
days = (next_delivery.when_delivered - prev_delivery.when_delivered).days
if days > 0:
# Calculate degree days for this interval from temp_avg
interval_temps = session.query(Auto_Temp).filter(
Auto_Temp.todays_date > prev_delivery.when_delivered,
Auto_Temp.todays_date <= next_delivery.when_delivered
).all()
total_degree_days = sum(max(0, 65 - float(temp.temp_avg)) for temp in interval_temps)
total_degree_days = Decimal(total_degree_days)
avg_degree_per_day = total_degree_days / days
total_hot_water = HOT_WATER_DAILY_USAGE * days
gallons_heating = prev_delivery.gallons_delivered - total_hot_water
if gallons_heating > 0 and total_degree_days > 0:
daily_heating = gallons_heating / days
daily_heating_usages.append(daily_heating)
avg_degree_per_days.append(avg_degree_per_day)
if daily_heating_usages and avg_degree_per_days:
average_daily_heating = sum(daily_heating_usages) / len(daily_heating_usages)
average_degree_days_per_day = sum(avg_degree_per_days) / len(avg_degree_per_days)
if average_degree_days_per_day > 0:
house_factor = average_daily_heating / average_degree_days_per_day
calculated_scaling = house_factor * TUNING_FACTOR # Override default with calculated value
house_factor = calculated_scaling # Use the scaling factor for usage calculation
# Calculate usage from last_fill to today using temperature-dependent heating
if last_fill < today:
temp_days = session.query(Auto_Temp).filter(
Auto_Temp.todays_date > last_fill,
Auto_Temp.todays_date <= today
).all()
heating_usage = Decimal('0')
hot_water_usage = Decimal('0')
for temp in temp_days:
degree_day = max(0, 65 - float(temp.temp_avg))
heating_usage += house_factor * Decimal(degree_day)
if hot_water:
hot_water_usage += HOT_WATER_DAILY_USAGE
total_usage = heating_usage + hot_water_usage
estimated_gallons_left = max(Decimal('0'), estimated_gallons_left - total_usage)
estimated_gallons = estimated_gallons_left
# Update database if requested
if update_db == 1:
ce.estimated_gallons_left = estimated_gallons
if calculated_scaling is not None:
ce.house_factor = calculated_scaling
session.add(ce)
last_5 = deliveries[-5:] if deliveries else []
scaling_factor = float(calculated_scaling) if calculated_scaling is not None else (float(ce.house_factor) if ce.house_factor else None)
estimates.append({
"id": ce.id,
"total_deliveries": len(deliveries),
"customer_full_name": ce.customer_full_name,
"account_number": ce.account_number,
"address": ce.customer_address,
"estimated_gallons": float(estimated_gallons),
"scaling_factor": scaling_factor,
"last_5_deliveries": [
{
"fill_date": str(d.when_delivered),
"gallons_delivered": float(d.gallons_delivered),
"price_per_gallon": float(d.customer_price / d.gallons_delivered) if d.gallons_delivered and d.gallons_delivered > 0 else None,
"total_amount_customer": float(d.customer_price)
} for d in last_5
]
})
if update_db == 1:
session.commit()
return JSONResponse(content=jsonable_encoder(estimates))
@router.get("/estimate_gallons/customer/{customer_id}", status_code=200)
def estimate_customer_gallons_specific(customer_id: int):
"""
Estimates current gallons for a specific regular customer based on delivery history and weather.
Returns estimation data for the specified customer only.
"""
session.rollback() # Reset any aborted transaction state
# Check if weather data is available
auto_temp_count = session.query(Auto_Temp).count()
if auto_temp_count == 0:
return JSONResponse(content={
"error": "Auto_Temp table is empty. Cannot perform fuel estimations without weather data.",
"solution": "Populate the Auto_Temp table with weather data first."
})
customer_estimate = session.query(Customer_estimate_gallons).filter(
Customer_estimate_gallons.customer_id == customer_id
).first()
if not customer_estimate:
return JSONResponse(content={
"error": f"No fuel estimation data found for customer {customer_id}",
"solution": "Run the populate_estimates endpoint first to initialize customer data."
})
deliveries = session.query(Delivery).filter(
Delivery.customer_id == customer_estimate.customer_id,
Delivery.automatic == 0,
Delivery.when_delivered.isnot(None)
).order_by(Delivery.when_delivered).all()
# Get tank size and hot water setting
tank_size = Decimal(customer_estimate.tank_size) if customer_estimate.tank_size else Decimal('275')
# Use maximum fill amount (how much we can actually fill the tank)
tank_size_float = float(tank_size)
max_fill = TANK_MAX_FILLS.get(tank_size_float, tank_size_float)
effective_tank = Decimal(str(max_fill))
hot_water = customer_estimate.hot_water_summer == 1
calculated_scaling = None # For DB update
if not deliveries:
estimated_gallons = Decimal('100')
calculated_scaling = Decimal('0.12') # No deliveries = use average baseline
else:
last_fill = deliveries[-1].when_delivered
estimated_gallons_left = effective_tank
today = date.today()
if len(deliveries) == 1:
# Single delivery: use weather data for 2000 sq ft home, only heat when temp <=65
calculated_scaling = Decimal('0.12')
if last_fill < today:
# Get daily weather data
temp_days = session.query(Auto_Temp).filter(
Auto_Temp.todays_date > last_fill,
Auto_Temp.todays_date <= today
).all()
heating_usage = Decimal('0')
hot_water_usage = Decimal('0')
house_factor_2000_sqft = Decimal('0.12') # gallons per degree day (average)
for temp in temp_days:
degree_day = max(0, 65 - float(temp.temp_avg))
heating_usage += house_factor_2000_sqft * Decimal(degree_day)
if hot_water:
hot_water_usage += HOT_WATER_DAILY_USAGE
total_usage = heating_usage + hot_water_usage
estimated_gallons_left = max(Decimal('0'), estimated_gallons_left - total_usage)
else:
# Multiple deliveries: calculate house_factor (gallons per degree day)
calculated_scaling = Decimal('0.12') # Default average
daily_heating_usages = []
avg_degree_per_days = []
for i in range(len(deliveries) - 1):
prev_delivery = deliveries[i]
next_delivery = deliveries[i + 1]
days = (next_delivery.when_delivered - prev_delivery.when_delivered).days
if days > 0:
# Calculate degree days for this interval from temp_avg
interval_temps = session.query(Auto_Temp).filter(
Auto_Temp.todays_date > prev_delivery.when_delivered,
Auto_Temp.todays_date <= next_delivery.when_delivered
).all()
total_degree_days = sum(max(0, 65 - float(temp.temp_avg)) for temp in interval_temps)
total_degree_days = Decimal(total_degree_days)
avg_degree_per_day = total_degree_days / days
total_hot_water = HOT_WATER_DAILY_USAGE * days
gallons_heating = prev_delivery.gallons_delivered - total_hot_water
if gallons_heating > 0 and total_degree_days > 0:
daily_heating = gallons_heating / days
daily_heating_usages.append(daily_heating)
avg_degree_per_days.append(avg_degree_per_day)
if daily_heating_usages and avg_degree_per_days:
average_daily_heating = sum(daily_heating_usages) / len(daily_heating_usages)
average_degree_days_per_day = sum(avg_degree_per_days) / len(avg_degree_per_days)
if average_degree_days_per_day > 0:
house_factor = average_daily_heating / average_degree_days_per_day
calculated_scaling = house_factor * TUNING_FACTOR # Override default with calculated value
house_factor = calculated_scaling # Use the scaling factor for usage calculation
# Calculate usage from last_fill to today using temperature-dependent heating
if last_fill < today:
temp_days = session.query(Auto_Temp).filter(
Auto_Temp.todays_date > last_fill,
Auto_Temp.todays_date <= today
).all()
heating_usage = Decimal('0')
hot_water_usage = Decimal('0')
for temp in temp_days:
degree_day = max(0, 65 - float(temp.temp_avg))
heating_usage += house_factor * Decimal(degree_day)
if hot_water:
hot_water_usage += HOT_WATER_DAILY_USAGE
total_usage = heating_usage + hot_water_usage
estimated_gallons_left = max(Decimal('0'), estimated_gallons_left - total_usage)
estimated_gallons = estimated_gallons_left
last_5 = deliveries[-5:] if deliveries else []
scaling_factor = float(calculated_scaling) if calculated_scaling is not None else (float(customer_estimate.house_factor) if customer_estimate.house_factor else None)
result = {
"id": customer_estimate.id,
"customer_id": customer_estimate.customer_id,
"total_deliveries": len(deliveries),
"customer_full_name": customer_estimate.customer_full_name,
"account_number": customer_estimate.account_number,
"address": customer_estimate.customer_address,
"estimated_gallons": float(estimated_gallons),
"tank_size": float(tank_size),
"scaling_factor": scaling_factor,
"last_5_deliveries": [
{
"fill_date": str(d.when_delivered),
"gallons_delivered": float(d.gallons_delivered),
"price_per_gallon": float(d.customer_price / d.gallons_delivered) if d.gallons_delivered and d.gallons_delivered > 0 else None,
"total_amount_customer": float(d.customer_price)
} for d in last_5
]
}
return JSONResponse(content=jsonable_encoder(result))
@router.get("/populate_estimates", status_code=200)
def populate_customer_estimates():
"""
Populates the customer_estimate table with data from customer_customer for regular (non-automatic) customers.
Only creates records for customers that don't already exist in customer_estimate.
Sets default values for fuel estimation fields.
Returns statistics on records created.
"""
session.rollback() # Reset any aborted transaction state
# Get all regular customers (customer_automatic == 0)
regular_customers = session.query(Customer_Customer).filter(
Customer_Customer.customer_automatic == 0
).all()
records_created = 0
skipped_existing = 0
for customer in regular_customers:
# Check if estimate record already exists
existing_estimate = session.query(Customer_estimate_gallons).filter(
Customer_estimate_gallons.customer_id == customer.id
).first()
if existing_estimate:
skipped_existing += 1
continue
# Create new estimate record with defaults
new_estimate = Customer_estimate_gallons(
customer_id=customer.id,
account_number=customer.account_number,
customer_town=customer.customer_town,
customer_state=customer.customer_state,
customer_address=customer.customer_address,
customer_zip=customer.customer_zip,
customer_full_name=f"{customer.customer_first_name} {customer.customer_last_name}".strip(),
last_fill=None,
days_since_last_fill=None,
last_updated=None,
estimated_gallons_left=Decimal('100'), # Default starting value
estimated_gallons_left_prev_day=Decimal('100'),
tank_height=None,
tank_size='275', # Default tank size
house_factor=None,
auto_status=1, # Active
open_ticket_id=None,
hot_water_summer=0 # Default to no hot water heating
)
session.add(new_estimate)
records_created += 1
session.commit()
result = {
"total_regular_customers": len(regular_customers),
"records_created": records_created,
"skipped_existing": skipped_existing,
"message": f"Created {records_created} new customer estimate records"
}
return JSONResponse(content=jsonable_encoder(result))