mirror of
https://github.com/pacnpal/thrillwiki_django_no_react.git
synced 2025-12-20 10:31:09 -05:00
- Cleaned up and standardized assertions in ApiTestMixin for API response validation. - Updated ASGI settings to use os.environ for setting the DJANGO_SETTINGS_MODULE. - Removed unused imports and improved formatting in settings.py. - Refactored URL patterns in urls.py for better readability and organization. - Enhanced view functions in views.py for consistency and clarity. - Added .flake8 configuration for linting and style enforcement. - Introduced type stubs for django-environ to improve type checking with Pylance.
364 lines
12 KiB
Python
364 lines
12 KiB
Python
"""
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Demonstration script showing practical usage of the RoadTripService.
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This script demonstrates real-world scenarios for using the OSM Road Trip Service
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in the ThrillWiki application.
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"""
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from parks.models import Park
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from parks.services import RoadTripService
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import os
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import django
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# Setup Django
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os.environ.setdefault("DJANGO_SETTINGS_MODULE", "thrillwiki.settings")
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django.setup()
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def demo_florida_theme_park_trip():
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"""
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Demonstrate planning a Florida theme park road trip.
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"""
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print("🏖️ Florida Theme Park Road Trip Planner")
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print("=" * 50)
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service = RoadTripService()
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# Define Florida theme parks with addresses
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florida_parks = [
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("Magic Kingdom", "Magic Kingdom Dr, Orlando, FL 32830"),
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(
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"Universal Studios Florida",
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"6000 Universal Blvd, Orlando, FL 32819",
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),
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("SeaWorld Orlando", "7007 Sea World Dr, Orlando, FL 32821"),
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("Busch Gardens Tampa", "10165 McKinley Dr, Tampa, FL 33612"),
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]
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print("Planning trip for these Florida parks:")
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park_coords = {}
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for name, address in florida_parks:
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print(f"\n📍 Geocoding {name}...")
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coords = service.geocode_address(address)
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if coords:
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park_coords[name] = coords
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print(
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f" ✅ Located at {
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coords.latitude:.4f}, {
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coords.longitude:.4f}"
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)
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else:
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print(f" ❌ Could not geocode {address}")
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if len(park_coords) < 2:
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print("❌ Need at least 2 parks to plan a trip")
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return
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# Calculate distances between all parks
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print("\n🗺️ Distance Matrix:")
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park_names = list(park_coords.keys())
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for i, park1 in enumerate(park_names):
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for j, park2 in enumerate(park_names):
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if i < j: # Only calculate each pair once
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route = service.calculate_route(park_coords[park1], park_coords[park2])
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if route:
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print(f" {park1} ↔ {park2}")
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print(
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f" {
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route.formatted_distance}, {
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route.formatted_duration}"
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)
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# Find central park for radiating searches
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print("\n🎢 Parks within 100km of Magic Kingdom:")
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magic_kingdom_coords = park_coords.get("Magic Kingdom")
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if magic_kingdom_coords:
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for name, coords in park_coords.items():
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if name != "Magic Kingdom":
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route = service.calculate_route(magic_kingdom_coords, coords)
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if route:
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print(
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f" {name}: {
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route.formatted_distance} ({
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route.formatted_duration})"
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)
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def demo_cross_country_road_trip():
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"""
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Demonstrate planning a cross-country theme park road trip.
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"""
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print("\n\n🇺🇸 Cross-Country Theme Park Road Trip")
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print("=" * 50)
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service = RoadTripService()
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# Major theme parks across the US
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major_parks = [
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("Disneyland", "1313 Disneyland Dr, Anaheim, CA 92802"),
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("Cedar Point", "1 Cedar Point Dr, Sandusky, OH 44870"),
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(
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"Six Flags Magic Mountain",
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"26101 Magic Mountain Pkwy, Valencia, CA 91355",
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),
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("Walt Disney World", "Walt Disney World Resort, Orlando, FL 32830"),
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]
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print("Geocoding major US theme parks:")
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park_coords = {}
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for name, address in major_parks:
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print(f"\n📍 {name}...")
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coords = service.geocode_address(address)
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if coords:
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park_coords[name] = coords
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print(f" ✅ {coords.latitude:.4f}, {coords.longitude:.4f}")
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if len(park_coords) >= 3:
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# Calculate an optimized route if we have DB parks
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print("\n🛣️ Optimized Route Planning:")
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print("Note: This would work with actual Park objects from the database")
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# Show distances for a potential route
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route_order = [
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"Disneyland",
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"Six Flags Magic Mountain",
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"Cedar Point",
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"Walt Disney World",
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]
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total_distance = 0
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total_time = 0
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for i in range(len(route_order) - 1):
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from_park = route_order[i]
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to_park = route_order[i + 1]
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if from_park in park_coords and to_park in park_coords:
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route = service.calculate_route(
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park_coords[from_park], park_coords[to_park]
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)
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if route:
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total_distance += route.distance_km
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total_time += route.duration_minutes
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print(f" {i + 1}. {from_park} → {to_park}")
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print(
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f" {
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route.formatted_distance}, {
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route.formatted_duration}"
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)
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print("\n📊 Trip Summary:")
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print(f" Total Distance: {total_distance:.1f}km")
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print(
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f" Total Driving Time: {
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total_time //
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60}h {
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total_time %
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60}min"
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)
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print(f" Average Distance per Leg: {total_distance / 3:.1f}km")
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def demo_database_integration():
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"""
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Demonstrate working with actual parks from the database.
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"""
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print("\n\n🗄️ Database Integration Demo")
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print("=" * 50)
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service = RoadTripService()
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# Get parks that have location data
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parks_with_location = Park.objects.filter(
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location__point__isnull=False
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).select_related("location")[:5]
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if not parks_with_location:
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print("❌ No parks with location data found in database")
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return
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print(f"Found {len(parks_with_location)} parks with location data:")
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for park in parks_with_location:
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coords = park.coordinates
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if coords:
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print(f" 🎢 {park.name}: {coords[0]:.4f}, {coords[1]:.4f}")
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# Demonstrate nearby park search
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if len(parks_with_location) >= 1:
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center_park = parks_with_location[0]
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print(f"\n🔍 Finding parks within 500km of {center_park.name}:")
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nearby_parks = service.get_park_distances(center_park, radius_km=500)
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if nearby_parks:
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print(f" Found {len(nearby_parks)} nearby parks:")
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for result in nearby_parks[:3]: # Show top 3
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park = result["park"]
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print(
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f" 📍 {
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park.name}: {
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result['formatted_distance']} ({
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result['formatted_duration']})"
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)
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else:
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print(" No nearby parks found (may need larger radius)")
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# Demonstrate multi-park trip planning
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if len(parks_with_location) >= 3:
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selected_parks = list(parks_with_location)[:3]
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print("\n🗺️ Planning optimized trip for 3 parks:")
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for park in selected_parks:
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print(f" - {park.name}")
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trip = service.create_multi_park_trip(selected_parks)
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if trip:
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print("\n✅ Optimized Route:")
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print(f" Total Distance: {trip.formatted_total_distance}")
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print(f" Total Duration: {trip.formatted_total_duration}")
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print(" Route:")
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for i, leg in enumerate(trip.legs, 1):
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print(f" {i}. {leg.from_park.name} → {leg.to_park.name}")
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print(
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f" {
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leg.route.formatted_distance}, {
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leg.route.formatted_duration}"
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)
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else:
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print(" ❌ Could not optimize trip route")
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def demo_geocoding_fallback():
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"""
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Demonstrate geocoding parks that don't have coordinates.
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"""
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print("\n\n🌍 Geocoding Demo")
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print("=" * 50)
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service = RoadTripService()
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# Get parks without location data
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parks_without_coords = Park.objects.filter(
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location__point__isnull=True
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).select_related("location")[:3]
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if not parks_without_coords:
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print("✅ All parks already have coordinates")
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return
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print(f"Found {len(parks_without_coords)} parks without coordinates:")
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for park in parks_without_coords:
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print(f"\n🎢 {park.name}")
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if hasattr(park, "location") and park.location:
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location = park.location
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address_parts = [
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park.name,
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location.street_address,
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location.city,
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location.state,
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location.country,
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]
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address = ", ".join(part for part in address_parts if part)
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print(f" Address: {address}")
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# Try to geocode
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success = service.geocode_park_if_needed(park)
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if success:
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coords = park.coordinates
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print(f" ✅ Geocoded to: {coords[0]:.4f}, {coords[1]:.4f}")
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else:
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print(" ❌ Geocoding failed")
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else:
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print(" ❌ No location data available")
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def demo_cache_performance():
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"""
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Demonstrate caching performance benefits.
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"""
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print("\n\n⚡ Cache Performance Demo")
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print("=" * 50)
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service = RoadTripService()
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import time
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# Test address for geocoding
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test_address = "Disneyland, Anaheim, CA"
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print(f"Testing cache performance with: {test_address}")
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# First request (cache miss)
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print("\n1️⃣ First request (cache miss):")
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start_time = time.time()
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coords1 = service.geocode_address(test_address)
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first_duration = time.time() - start_time
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if coords1:
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print(f" ✅ Result: {coords1.latitude:.4f}, {coords1.longitude:.4f}")
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print(f" ⏱️ Duration: {first_duration:.2f} seconds")
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# Second request (cache hit)
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print("\n2️⃣ Second request (cache hit):")
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start_time = time.time()
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coords2 = service.geocode_address(test_address)
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second_duration = time.time() - start_time
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if coords2:
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print(f" ✅ Result: {coords2.latitude:.4f}, {coords2.longitude:.4f}")
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print(f" ⏱️ Duration: {second_duration:.2f} seconds")
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if first_duration > second_duration:
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speedup = first_duration / second_duration
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print(f" 🚀 Cache speedup: {speedup:.1f}x faster")
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if (
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coords1.latitude == coords2.latitude
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and coords1.longitude == coords2.longitude
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):
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print(" ✅ Results identical (cache working)")
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def main():
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"""
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Run all demonstration scenarios.
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"""
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print("🎢 ThrillWiki Road Trip Service Demo")
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print("This demo shows practical usage scenarios for the OSM Road Trip Service")
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try:
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demo_florida_theme_park_trip()
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demo_cross_country_road_trip()
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demo_database_integration()
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demo_geocoding_fallback()
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demo_cache_performance()
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print("\n" + "=" * 50)
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print("🎉 Demo completed successfully!")
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print("\nThe Road Trip Service is ready for integration into ThrillWiki!")
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print("\nKey Features Demonstrated:")
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print("✅ Geocoding theme park addresses")
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print("✅ Route calculation with distance/time")
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print("✅ Multi-park trip optimization")
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print("✅ Database integration with Park models")
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print("✅ Caching for performance")
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print("✅ Rate limiting for OSM compliance")
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print("✅ Error handling and fallbacks")
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except Exception as e:
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print(f"\n❌ Demo failed with error: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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main()
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