#!/usr/bin/env python3 """ Saskatchewan HVAC Verified Route Calculator Uses OSRM-verified distances to calculate optimal routes Includes Basic and Guaranteed Protection Service (GPS) pricing """ import json # Verified distances from OSRM SITE_VISIT_HOURS = 2.5 HOURLY_RATE = 80 # Tech cost per hour MILEAGE_RATE = 1.25 # Pass-through (not marked up) HOTEL_COST = 150 # Per night CONSUMABLES_PER_SITE = 50 # Per trip OVERTIME_MULTIPLIER = 1.5 GROSS_MARGIN = 0.50 # 50% gross margin # GPS (Guaranteed Protection Service) add-ons GPS_EMERGENCY_PARTS = 250 # Per site GPS_EMERGENCY_FACTOR = 0.3 # Factor for expected emergency trips GPS_SERVICE_HOURS = 2.5 # Hours per emergency service call AVG_SPEED_KMH = 110 # Saskatchewan highway speed for emergency response def cost_to_retail(cost, pass_through=False): """Convert cost to retail price with 50% gross margin""" if pass_through: return cost # Mileage is pass-through return cost / (1 - GROSS_MARGIN) # Divide by 0.5 = multiply by 2 # All verified distances (km, hours) distances = { # Regina routes ("Regina Shop", "Lumsden"): (32.3, 0.49), ("Lumsden", "Regina ReStore"): (33.3, 0.49), ("Regina ReStore", "Regina Butterfield"): (3.6, 0.09), ("Regina Butterfield", "Regina Shop"): (6.5, 0.16), ("Regina Shop", "Bulyea"): (71.1, 1.07), ("Bulyea", "Strasbourg"): (12.8, 0.21), ("Strasbourg", "Regina Shop"): (84.1, 1.28), ("Regina Shop", "Nokomis"): (132.5, 2.02), ("Regina Shop", "Jansen"): (180.6, 2.76), ("Jansen", "Nokomis"): (65.0, 0.95), ("Nokomis", "Regina Shop"): (132.5, 2.02), ("Regina Shop", "Moose Jaw"): (71.9, 0.94), ("Moose Jaw", "Swift Current"): (176.0, 2.10), ("Swift Current", "Regina Shop"): (243.2, 2.87), ("Swift Current", "Moose Jaw"): (176.0, 2.10), ("Moose Jaw", "Regina Shop"): (71.9, 0.94), ("Regina Shop", "Yorkton"): (188.4, 2.50), ("Yorkton", "Regina Shop"): (188.4, 2.50), # Saskatoon routes ("Saskatoon Shop", "Jansen"): (154.9, 2.09), ("Saskatoon Shop", "Nokomis"): (165.1, 2.12), ("Nokomis", "Saskatoon Shop"): (164.5, 2.09), ("Jansen", "Saskatoon Shop"): (154.9, 2.09), ("Saskatoon Shop", "Saskatoon LINN"): (2.5, 0.07), ("Saskatoon LINN", "Saskatoon Old TT"): (7.4, 0.17), ("Saskatoon Old TT", "Casa Rio"): (17.3, 0.35), ("Casa Rio", "Saskatoon Shop"): (15.1, 0.32), ("Saskatoon Shop", "Clavet"): (36.1, 0.52), ("Clavet", "Cardinal Estates"): (12.3, 0.19), ("Cardinal Estates", "Shields"): (16.9, 0.27), ("Shields", "Saskatoon Shop"): (46.8, 0.63), ("Saskatoon Shop", "Allan"): (62.4, 0.82), ("Allan", "Young"): (24.0, 0.38), ("Young", "Saskatoon Shop"): (93.3, 1.18), ("Saskatoon Shop", "Prud'Homme"): (60.8, 0.88), ("Prud'Homme", "Humboldt"): (70.6, 0.91), ("Humboldt", "Tarnopol"): (74.0, 1.03), ("Tarnopol", "Saskatoon Shop"): (119.2, 1.58), ("Saskatoon Shop", "Neuanlage"): (40.7, 0.53), ("Neuanlage", "Waldheim"): (32.1, 0.52), ("Waldheim", "Rosthern"): (25.9, 0.34), ("Rosthern", "Saskatoon Shop"): (67.1, 0.83), ("Saskatoon Shop", "Prince Albert"): (140.9, 1.72), ("Prince Albert", "Saskatoon Shop"): (140.9, 1.72), } # Shop to site distances shop_to_site = { "Lumsden": {"Regina": 32.3, "Saskatoon": 228.0}, "Regina ReStore": {"Regina": 3.0, "Saskatoon": 260.3}, "Regina Butterfield": {"Regina": 6.5, "Saskatoon": 259.7}, "Bulyea": {"Regina": 71.1, "Saskatoon": 226.2}, "Strasbourg": {"Regina": 84.0, "Saskatoon": 214.8}, "Nokomis": {"Regina": 132.5, "Saskatoon": 165.1}, "Jansen": {"Regina": 180.6, "Saskatoon": 154.9}, "Moose Jaw": {"Regina": 71.9, "Saskatoon": 226.7}, "Swift Current": {"Regina": 244.8, "Saskatoon": 271.0}, "Yorkton": {"Regina": 188.4, "Saskatoon": 330.5}, "Saskatoon LINN": {"Regina": 261.2, "Saskatoon": 2.5}, "Saskatoon Old TT": {"Regina": 256.5, "Saskatoon": 7.4}, "Casa Rio": {"Regina": 245.7, "Saskatoon": 15.4}, "Neuanlage": {"Regina": 298.8, "Saskatoon": 40.7}, "Waldheim": {"Regina": 314.7, "Saskatoon": 56.6}, "Rosthern": {"Regina": 324.9, "Saskatoon": 66.8}, "Clavet": {"Regina": 241.1, "Saskatoon": 36.1}, "Cardinal Estates": {"Regina": 231.7, "Saskatoon": 32.5}, "Shields": {"Regina": 223.8, "Saskatoon": 46.5}, "Allan": {"Regina": 218.8, "Saskatoon": 62.4}, "Young": {"Regina": 199.8, "Saskatoon": 93.8}, "Prud'Homme": {"Regina": 272.8, "Saskatoon": 60.8}, "Humboldt": {"Regina": 218.4, "Saskatoon": 112.8}, "Tarnopol": {"Regina": 291.9, "Saskatoon": 119.5}, "Prince Albert": {"Regina": 362.2, "Saskatoon": 140.9}, } def calc_route_cost(total_hours, total_km, sites_list, hotel_nights=0): """Calculate detailed cost breakdown for a route""" num_sites = len(sites_list) # Labour calculation regular_hours = min(total_hours, 8) overtime_hours = max(0, total_hours - 8) labour_cost = (regular_hours * HOURLY_RATE) + (overtime_hours * HOURLY_RATE * OVERTIME_MULTIPLIER) # Mileage (pass-through) mileage_cost = total_km * MILEAGE_RATE # Consumables consumables_cost = num_sites * CONSUMABLES_PER_SITE # Hotel hotel_cost = hotel_nights * HOTEL_COST # Total cost total_cost = labour_cost + mileage_cost + consumables_cost + hotel_cost # GPS add-ons - calculated per-site based on distance from closest shop gps_parts_cost = num_sites * GPS_EMERGENCY_PARTS # Calculate emergency travel/labour for each site from its closest shop gps_travel_cost = 0 gps_labour_cost = 0 for site_name in sites_list: if site_name in shop_to_site: # Get distance from closest shop distances = shop_to_site[site_name] closest_distance = min(distances["Regina"], distances["Saskatoon"]) # Round trip for emergency call emergency_km = closest_distance * 2 emergency_drive_hours = emergency_km / AVG_SPEED_KMH emergency_total_hours = emergency_drive_hours + GPS_SERVICE_HOURS # Apply 0.3 factor (expected emergency trips) gps_travel_cost += emergency_km * GPS_EMERGENCY_FACTOR * MILEAGE_RATE gps_labour_cost += emergency_total_hours * GPS_EMERGENCY_FACTOR * HOURLY_RATE gps_total_addon = gps_parts_cost + gps_travel_cost + gps_labour_cost return { "labour_cost": round(labour_cost, 2), "mileage_cost": round(mileage_cost, 2), "consumables_cost": round(consumables_cost, 2), "hotel_cost": round(hotel_cost, 2), "total_cost": round(total_cost, 2), "gps_parts_cost": round(gps_parts_cost, 2), "gps_travel_cost": round(gps_travel_cost, 2), "gps_labour_cost": round(gps_labour_cost, 2), "gps_total_addon": round(gps_total_addon, 2), "gps_total_cost": round(total_cost + gps_total_addon, 2), # Retail prices "labour_retail": round(cost_to_retail(labour_cost), 2), "mileage_retail": round(mileage_cost, 2), # Pass-through "consumables_retail": round(cost_to_retail(consumables_cost), 2), "hotel_retail": round(cost_to_retail(hotel_cost), 2), "total_retail": round(cost_to_retail(labour_cost) + mileage_cost + cost_to_retail(consumables_cost) + cost_to_retail(hotel_cost), 2), "gps_parts_retail": round(cost_to_retail(gps_parts_cost), 2), "gps_travel_retail": round(gps_travel_cost, 2), # Pass-through (mileage) "gps_labour_retail": round(cost_to_retail(gps_labour_cost), 2), "gps_total_addon_retail": round(cost_to_retail(gps_parts_cost) + gps_travel_cost + cost_to_retail(gps_labour_cost), 2), } # Build routes with detailed cost breakdowns routes = [] # Helper to build route def add_route(name, branch, sites, total_km, drive_hours, schedule, hotel_nights=0, note=None): num_sites = len(sites) total_hours = drive_hours + (num_sites * SITE_VISIT_HOURS) overtime = max(0, total_hours - 8) costs = calc_route_cost(total_hours, total_km, sites, hotel_nights) # Calculate per-site allocation km_per_site = total_km / num_sites if num_sites > 0 else 0 hours_per_site = total_hours / num_sites if num_sites > 0 else 0 route_data = { "name": name, "branch": branch, "sites": sites, "km": round(total_km, 1), "drive_hours": round(drive_hours, 2), "total_hours": round(total_hours, 1), "overtime": round(overtime, 1), "schedule": schedule, # Cost breakdown "costs": costs, # Per-site metrics "km_per_site": round(km_per_site, 1), "hours_per_site": round(hours_per_site, 2), } if note: route_data["note"] = note routes.append(route_data) # Regina Local: Shop -> Lumsden -> ReStore -> Butterfield -> Shop r1_km = 32.3 + 33.3 + 3.6 + 6.5 r1_drive = 0.49 + 0.49 + 0.09 + 0.16 add_route("Regina Local", "Regina", ["Lumsden", "Regina ReStore", "Regina Butterfield"], r1_km, r1_drive, [{"day": 1, "sites": ["Lumsden", "Regina ReStore", "Regina Butterfield"], "km": round(r1_km, 1), "hours": round(r1_drive + 3 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Regina North: Shop -> Bulyea -> Strasbourg -> Shop r2_km = 71.1 + 12.8 + 84.1 r2_drive = 1.07 + 0.21 + 1.28 add_route("Regina North", "Regina", ["Bulyea", "Strasbourg"], r2_km, r2_drive, [{"day": 1, "sites": ["Bulyea", "Strasbourg"], "km": round(r2_km, 1), "hours": round(r2_drive + 2 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Yorkton: Shop -> Yorkton -> Shop r3_km = 188.4 * 2 r3_drive = 2.50 * 2 add_route("Yorkton", "Regina", ["Yorkton"], r3_km, r3_drive, [{"day": 1, "sites": ["Yorkton"], "km": round(r3_km, 1), "hours": round(r3_drive + 1 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Regina West: 2-day trip r4_d1_km = 71.9 + 176.0 r4_d1_drive = 0.94 + 2.10 r4_d2_km = 243.2 r4_d2_drive = 2.87 r4_km = r4_d1_km + r4_d2_km r4_drive = r4_d1_drive + r4_d2_drive add_route("Regina West", "Regina", ["Moose Jaw", "Swift Current"], r4_km, r4_drive, [ {"day": 1, "sites": ["Moose Jaw", "Swift Current"], "km": round(r4_d1_km, 1), "hours": round(r4_d1_drive + 2 * SITE_VISIT_HOURS, 1), "overnight": "Swift Current"}, {"day": 2, "sites": [], "km": round(r4_d2_km, 1), "hours": round(r4_d2_drive, 1), "overnight": None} ], hotel_nights=1) # Jansen + Nokomis from Saskatoon r5_km = 154.9 + 65.0 + 164.5 r5_drive = 2.09 + 0.95 + 2.09 add_route("North Corridor", "Saskatoon", ["Jansen", "Nokomis"], r5_km, r5_drive, [{"day": 1, "sites": ["Jansen", "Nokomis"], "km": round(r5_km, 1), "hours": round(r5_drive + 2 * SITE_VISIT_HOURS, 1), "overnight": None}], note="Verified: Saskatoon saves $69 vs Regina for this loop") # Saskatoon Local r6_km = 2.5 + 7.4 + 17.3 + 15.1 r6_drive = 0.07 + 0.17 + 0.35 + 0.32 add_route("Saskatoon Local", "Saskatoon", ["Saskatoon LINN", "Saskatoon Old TT", "Casa Rio"], r6_km, r6_drive, [{"day": 1, "sites": ["Saskatoon LINN", "Saskatoon Old TT", "Casa Rio"], "km": round(r6_km, 1), "hours": round(r6_drive + 3 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Saskatoon South r7_km = 36.1 + 12.3 + 16.9 + 46.8 r7_drive = 0.52 + 0.19 + 0.27 + 0.63 add_route("Saskatoon South", "Saskatoon", ["Clavet", "Cardinal Estates", "Shields"], r7_km, r7_drive, [{"day": 1, "sites": ["Clavet", "Cardinal Estates", "Shields"], "km": round(r7_km, 1), "hours": round(r7_drive + 3 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Saskatoon East r8_km = 62.4 + 24.0 + 93.3 r8_drive = 0.82 + 0.38 + 1.18 add_route("Saskatoon East", "Saskatoon", ["Allan", "Young"], r8_km, r8_drive, [{"day": 1, "sites": ["Allan", "Young"], "km": round(r8_km, 1), "hours": round(r8_drive + 2 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Saskatoon NE (Humboldt corridor) r9_km = 60.8 + 70.6 + 74.0 + 119.2 r9_drive = 0.88 + 0.91 + 1.03 + 1.58 add_route("Saskatoon NE (Humboldt)", "Saskatoon", ["Prud'Homme", "Humboldt", "Tarnopol"], r9_km, r9_drive, [{"day": 1, "sites": ["Prud'Homme", "Humboldt", "Tarnopol"], "km": round(r9_km, 1), "hours": round(r9_drive + 3 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Saskatoon North r10_km = 40.7 + 32.1 + 25.9 + 67.1 r10_drive = 0.53 + 0.52 + 0.34 + 0.83 add_route("Saskatoon North", "Saskatoon", ["Neuanlage", "Waldheim", "Rosthern"], r10_km, r10_drive, [{"day": 1, "sites": ["Neuanlage", "Waldheim", "Rosthern"], "km": round(r10_km, 1), "hours": round(r10_drive + 3 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Prince Albert r11_km = 140.9 * 2 r11_drive = 1.72 * 2 add_route("Prince Albert", "Saskatoon", ["Prince Albert"], r11_km, r11_drive, [{"day": 1, "sites": ["Prince Albert"], "km": round(r11_km, 1), "hours": round(r11_drive + 1 * SITE_VISIT_HOURS, 1), "overnight": None}]) # Calculate totals total_sites = sum(len(r["sites"]) for r in routes) total_km = sum(r["km"] for r in routes) total_hours = sum(r["total_hours"] for r in routes) total_overtime = sum(r["overtime"] for r in routes) total_days = sum(len(r["schedule"]) for r in routes) total_hotels = sum(1 for r in routes for s in r["schedule"] if s.get("overnight")) # Aggregate costs total_labour_cost = sum(r["costs"]["labour_cost"] for r in routes) total_mileage_cost = sum(r["costs"]["mileage_cost"] for r in routes) total_consumables_cost = sum(r["costs"]["consumables_cost"] for r in routes) total_hotel_cost = sum(r["costs"]["hotel_cost"] for r in routes) total_cost = sum(r["costs"]["total_cost"] for r in routes) total_labour_retail = sum(r["costs"]["labour_retail"] for r in routes) total_mileage_retail = sum(r["costs"]["mileage_retail"] for r in routes) total_consumables_retail = sum(r["costs"]["consumables_retail"] for r in routes) total_hotel_retail = sum(r["costs"]["hotel_retail"] for r in routes) total_retail = sum(r["costs"]["total_retail"] for r in routes) # GPS totals total_gps_parts_cost = sum(r["costs"]["gps_parts_cost"] for r in routes) total_gps_travel_cost = sum(r["costs"]["gps_travel_cost"] for r in routes) total_gps_labour_cost = sum(r["costs"]["gps_labour_cost"] for r in routes) total_gps_addon_cost = sum(r["costs"]["gps_total_addon"] for r in routes) total_gps_cost = sum(r["costs"]["gps_total_cost"] for r in routes) total_gps_parts_retail = sum(r["costs"]["gps_parts_retail"] for r in routes) total_gps_travel_retail = sum(r["costs"]["gps_travel_retail"] for r in routes) total_gps_labour_retail = sum(r["costs"]["gps_labour_retail"] for r in routes) total_gps_addon_retail = sum(r["costs"]["gps_total_addon_retail"] for r in routes) total_gps_retail = total_retail + total_gps_addon_retail print("=" * 90) print("VERIFIED ROUTE SUMMARY") print("=" * 90) print() print(f"{'Route':<30} {'Sites':>5} {'km':>8} {'Hours':>7} {'OT':>6} {'Cost':>10} {'Retail':>10}") print("-" * 80) for r in routes: ot_str = f"{r['overtime']:.1f}h" if r['overtime'] > 0 else "-" print(f"{r['name']:<30} {len(r['sites']):>5} {r['km']:>7.0f} {r['total_hours']:>6.1f}h {ot_str:>6} ${r['costs']['total_cost']:>9.2f} ${r['costs']['total_retail']:>9.2f}") print("-" * 80) print(f"{'TOTAL':<30} {total_sites:>5} {total_km:>7.0f} {total_hours:>6.1f}h {total_overtime:.1f}h ${total_cost:>9.2f} ${total_retail:>9.2f}") print() print("=" * 90) print("COST BREAKDOWN (Per Cycle)") print("=" * 90) print() print(f"{'Category':<25} {'Cost':>15} {'Retail':>15} {'Margin':>15}") print("-" * 70) print(f"{'Labour':<25} ${total_labour_cost:>14.2f} ${total_labour_retail:>14.2f} ${total_labour_retail - total_labour_cost:>14.2f}") print(f"{'Mileage (pass-through)':<25} ${total_mileage_cost:>14.2f} ${total_mileage_retail:>14.2f} ${0:>14.2f}") print(f"{'Consumables':<25} ${total_consumables_cost:>14.2f} ${total_consumables_retail:>14.2f} ${total_consumables_retail - total_consumables_cost:>14.2f}") print(f"{'Hotels':<25} ${total_hotel_cost:>14.2f} ${total_hotel_retail:>14.2f} ${total_hotel_retail - total_hotel_cost:>14.2f}") print("-" * 70) print(f"{'BASIC SERVICE TOTAL':<25} ${total_cost:>14.2f} ${total_retail:>14.2f} ${total_retail - total_cost - total_mileage_cost:>14.2f}") print() print("=" * 90) print("GUARANTEED PROTECTION SERVICE (GPS) ADD-ONS") print("=" * 90) print() print("GPS emergency costs calculated per-site from closest shop:") print(" - Round-trip mileage to site x 0.3 factor") print(" - Drive time + 2.5hr service x 0.3 factor") print() print(f"{'Category':<25} {'Cost':>15} {'Retail':>15} {'Margin':>15}") print("-" * 70) print(f"{'Emergency Parts':<25} ${total_gps_parts_cost:>14.2f} ${total_gps_parts_retail:>14.2f} ${total_gps_parts_retail - total_gps_parts_cost:>14.2f}") print(f"{'Emergency Travel (0.3x)':<25} ${total_gps_travel_cost:>14.2f} ${total_gps_travel_retail:>14.2f} ${0:>14.2f}") print(f"{'Emergency Labour (0.3x)':<25} ${total_gps_labour_cost:>14.2f} ${total_gps_labour_retail:>14.2f} ${total_gps_labour_retail - total_gps_labour_cost:>14.2f}") print("-" * 70) print(f"{'GPS ADD-ON TOTAL':<25} ${total_gps_addon_cost:>14.2f} ${total_gps_addon_retail:>14.2f} ${total_gps_addon_retail - total_gps_addon_cost - total_gps_travel_cost:>14.2f}") print() print(f"{'GPS TOTAL (Basic + GPS)':<25} ${total_gps_cost:>14.2f} ${total_gps_retail:>14.2f}") print() print("=" * 90) print("SERVICE TIER PRICING SUMMARY") print("=" * 90) print() print(f"{'Service Level':<30} {'Per Cycle':>15} {'Annual (x2)':>15}") print("-" * 60) print(f"{'Basic Service':<30} ${total_retail:>14,.2f} ${total_retail * 2:>14,.2f}") print(f"{'Guaranteed Protection (GPS)':<30} ${total_gps_retail:>14,.2f} ${total_gps_retail * 2:>14,.2f}") print() print(f"GPS Premium: ${total_gps_addon_retail:,.2f}/cycle (${total_gps_addon_retail * 2:,.2f}/year)") print() # Per-site breakdown print("=" * 90) print("PER-SITE PRICING") print("=" * 90) print() basic_per_site = total_retail / total_sites gps_per_site = total_gps_retail / total_sites print(f"Average cost per site (Basic): ${basic_per_site:,.2f}/visit (${basic_per_site * 2:,.2f}/year)") print(f"Average cost per site (GPS): ${gps_per_site:,.2f}/visit (${gps_per_site * 2:,.2f}/year)") print() # Per-site GPS emergency breakdown print("=" * 90) print("GPS EMERGENCY COST BY SITE (from closest shop)") print(f"Speed: {AVG_SPEED_KMH} km/h | Service: {GPS_SERVICE_HOURS}h | Factor: {GPS_EMERGENCY_FACTOR}") print("=" * 90) print() print(f"{'Site':<25} {'Closest':>8} {'1-Way km':>10} {'RT km':>10} {'Drive h':>8} {'Total h':>8} {'Travel$':>10} {'Labour$':>10}") print("-" * 100) for site_name in sorted(shop_to_site.keys()): dist = shop_to_site[site_name] regina_d = dist["Regina"] saskatoon_d = dist["Saskatoon"] closest = "Regina" if regina_d <= saskatoon_d else "S'toon" closest_km = min(regina_d, saskatoon_d) rt_km = closest_km * 2 drive_h = rt_km / AVG_SPEED_KMH total_h = drive_h + GPS_SERVICE_HOURS travel_cost = rt_km * GPS_EMERGENCY_FACTOR * MILEAGE_RATE labour_cost = total_h * GPS_EMERGENCY_FACTOR * HOURLY_RATE print(f"{site_name:<25} {closest:>8} {closest_km:>10.1f} {rt_km:>10.1f} {drive_h:>8.2f} {total_h:>8.2f} ${travel_cost:>9.2f} ${labour_cost:>9.2f}") print() print(f"Total route days: {total_days}") print(f"Overnight stays: {total_hotels}") print() # Output JSON for dashboard output = { "routes": routes, "totals": { "sites": total_sites, "km": round(total_km, 1), "hours": round(total_hours, 1), "overtime": round(total_overtime, 1), "days": total_days, "hotels": total_hotels, }, "costs": { "labour_cost": round(total_labour_cost, 2), "mileage_cost": round(total_mileage_cost, 2), "consumables_cost": round(total_consumables_cost, 2), "hotel_cost": round(total_hotel_cost, 2), "total_cost": round(total_cost, 2), "labour_retail": round(total_labour_retail, 2), "mileage_retail": round(total_mileage_retail, 2), "consumables_retail": round(total_consumables_retail, 2), "hotel_retail": round(total_hotel_retail, 2), "total_retail": round(total_retail, 2), "gps_parts_cost": round(total_gps_parts_cost, 2), "gps_travel_cost": round(total_gps_travel_cost, 2), "gps_labour_cost": round(total_gps_labour_cost, 2), "gps_addon_cost": round(total_gps_addon_cost, 2), "gps_total_cost": round(total_gps_cost, 2), "gps_parts_retail": round(total_gps_parts_retail, 2), "gps_travel_retail": round(total_gps_travel_retail, 2), "gps_labour_retail": round(total_gps_labour_retail, 2), "gps_addon_retail": round(total_gps_addon_retail, 2), "gps_total_retail": round(total_gps_retail, 2), "annual_basic_retail": round(total_retail * 2, 2), "annual_gps_retail": round(total_gps_retail * 2, 2), }, "per_site": { "basic_retail": round(basic_per_site, 2), "gps_retail": round(gps_per_site, 2), "basic_annual": round(basic_per_site * 2, 2), "gps_annual": round(gps_per_site * 2, 2), }, "rates": { "hourly_cost": HOURLY_RATE, "hourly_retail": cost_to_retail(HOURLY_RATE), "mileage_rate": MILEAGE_RATE, "consumables_cost": CONSUMABLES_PER_SITE, "consumables_retail": cost_to_retail(CONSUMABLES_PER_SITE), "hotel_cost": HOTEL_COST, "hotel_retail": cost_to_retail(HOTEL_COST), "gps_parts_cost": GPS_EMERGENCY_PARTS, "gps_parts_retail": cost_to_retail(GPS_EMERGENCY_PARTS), "gps_emergency_factor": GPS_EMERGENCY_FACTOR, "gross_margin": GROSS_MARGIN, }, "shop_distances": shop_to_site } with open("verified_routes.json", "w") as f: json.dump(output, f, indent=2) print("Route data saved to verified_routes.json")