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thrillwiki_django_no_react/memory-bank/features/search/park-search.md

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Park Search Implementation

Overview

Integration of the parks app with the site-wide search system, providing both full search functionality and quick search for dropdowns.

Components

1. Filter Configuration (parks/filters.py)

ParkFilter = create_model_filter(
    model=Park,
    search_fields=['name', 'description', 'location__city', 'location__state', 'location__country'],
    mixins=[LocationFilterMixin, RatingFilterMixin, DateRangeFilterMixin],
    additional_filters={
        'status': {
            'field_class': 'django_filters.ChoiceFilter',
            'field_kwargs': {
                'choices': Park._meta.get_field('status').choices,
                'empty_label': 'Any status',
                'null_label': 'Unknown'
            }
        },
        'opening_date': {
            'field_class': 'django_filters.DateFromToRangeFilter',
            'field_kwargs': {
                'label': 'Opening date range',
                'help_text': 'Enter dates in YYYY-MM-DD format'
            }
        },
        # Additional filters for rides, size, etc.
    }
)

2. View Implementation (parks/views.py)

Full Search (ParkListView)

class ParkListView(HTMXFilterableMixin, ListView):
    model = Park
    filter_class = ParkFilter
    paginate_by = 20

    def get_queryset(self):
        try:
            return (
                super()
                .get_queryset()
                .select_related("owner")
                .prefetch_related(
                    "photos",
                    "location",
                    "rides",
                    "rides__manufacturer"
                )
                .annotate(
                    total_rides=Count("rides"),
                    total_coasters=Count("rides", filter=Q(rides__category="RC")),
                )
            )
        except Exception as e:
            messages.error(self.request, f"Error loading parks: {str(e)}")
            return Park.objects.none()
def search_parks(request):
    try:
        queryset = (
            Park.objects.prefetch_related('location', 'photos')
            .order_by('name')
        )
        filter_params = {'search': request.GET.get('q', '').strip()}
        park_filter = ParkFilter(filter_params, queryset=queryset)
        parks = park_filter.qs[:10]
        
        return render(request, "parks/partials/park_search_results.html", {
            "parks": parks,
            "is_quick_search": True
        })
    except Exception as e:
        return render(..., {"error": str(e)})

3. Template Structure

Main Search Page (parks/templates/parks/park_list.html)

  • Extends: search/layouts/filtered_list.html
  • Blocks:
    • filter_errors: Validation error display
    • list_header: Park list header + actions
    • filter_section: Filter form with clear option
    • results_section: Park results with pagination

Results Display (search/templates/search/partials/park_results.html)

  • Full park information
  • Status indicators
  • Ride statistics
  • Location details
  • Error state handling

Quick Search Results (parks/partials/park_search_results.html)

  • Simplified park display
  • Basic location info
  • Fallback for missing images
  • Error handling

4. Error Handling

View Level

  • Try/except blocks around queryset operations
  • Filter validation errors captured
  • Generic error states handled
  • User-friendly error messages

Template Level

  • Error states in both quick and full search
  • Safe data access (using with and conditionals)
  • Fallback content for missing data
  • Clear error messaging

5. Query Optimization

  • select_related: owner
  • prefetch_related: photos, location, rides, rides__manufacturer
  • Proper annotations for counts
  • Pagination for large results

Quick Search

  • Limited to 10 results
  • Minimal related data loading
  • Basic ordering optimization

6. Known Limitations

  1. Testing Coverage

    • Need unit tests for filters
    • Need integration tests for error cases
    • Need performance testing
  2. Performance

    • Large dataset behavior unknown
    • Complex filter combinations untested
  3. Security

    • SQL injection prevention needs review
    • Permission checks need audit
  4. Accessibility

    • ARIA labels needed
    • Color contrast validation needed

7. Next Steps

  1. Testing

    • Implement comprehensive test suite
    • Add performance benchmarks
    • Test edge cases
  2. Monitoring

    • Add error logging
    • Implement performance tracking
    • Add usage analytics
  3. Optimization

    • Profile query performance
    • Optimize filter combinations
    • Consider caching strategies