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thrillwiki_django_no_react/memory-bank/decisions/ride-search-architecture-2025-06-24.md
pacnpal de05a5abda Add comprehensive audit reports, design assessment, and non-authenticated features testing for ThrillWiki application
- Created critical functionality audit report identifying 7 critical issues affecting production readiness.
- Added design assessment report highlighting exceptional design quality and minor cosmetic fixes needed.
- Documented non-authenticated features testing results confirming successful functionality and public access.
- Implemented ride search form with autocomplete functionality and corresponding templates for search results.
- Developed tests for ride autocomplete functionality, ensuring proper filtering and authentication checks.
2025-06-25 20:30:02 -04:00

2.7 KiB

Ride Search Architecture Decision

Date: 2025-06-24
Status: Planned
Context: Extending search functionality from parks to rides

Decision

Implement ride search functionality following the established BaseAutocomplete pattern with these key architectural decisions:

1. Pattern Consistency

  • Extend BaseAutocomplete: Use same authentication-first approach as park search
  • Mirror Structure: RideAutocomplete + RideSearchForm following ParkAutocomplete pattern
  • HTMX Integration: Same frontend interaction patterns for consistency

2. Relationship Handling

  • Park Context: Rides belong to parks via ForeignKey, search results must show both
  • Query Optimization: Use select_related('park') for efficient database queries
  • Result Display: Show "Ride Name - Park Name" format in autocomplete results

3. Database Strategy

  • Indexes: Add database indexes on Ride.name and Ride.park_id
  • Query Limits: Limit autocomplete to 10 results for performance
  • Filtering: Support filtering by park, thrill level, duration

4. Frontend Architecture

  • Component Reuse: Leverage existing search CSS and JavaScript patterns
  • HTMX Endpoints: /search/rides/autocomplete/ and /search/rides/results/
  • AlpineJS State: Manage selection state and form interactions

5. Testing Strategy

  • Unit Tests: RideAutocomplete, RideSearchForm, and filter logic
  • Integration Tests: HTMX responses and authentication requirements
  • Performance Tests: Large dataset handling and query optimization

Rationale

This approach ensures:

  • Consistency: Users get familiar interaction patterns
  • Performance: Optimized queries and result limiting
  • Maintainability: Follows established codebase patterns
  • Scalability: Database indexes and query optimization

Implementation Files

Core Components

  • search/mixins.py - RideAutocomplete class
  • search/forms.py - RideSearchForm class
  • search/urls.py - URL routing for ride endpoints
  • rides/views.py - RideSearchView with authentication

Templates

  • search/templates/search/partials/_ride_search.html - Search form
  • rides/templates/rides/partials/ride_results.html - Results display

Tests

  • search/tests/test_autocomplete.py - RideAutocomplete tests
  • search/tests/test_forms.py - RideSearchForm tests
  • rides/tests/test_search_view.py - View and integration tests

Next Steps

  1. Code mode implementation of core components
  2. Database migration for indexes
  3. Template creation and HTMX integration
  4. Comprehensive test suite
  5. Performance validation

Dependencies

  • Existing BaseAutocomplete infrastructure
  • HTMX and AlpineJS frontend stack
  • Django authentication system
  • Ride model with park relationship