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Refactor code structure and remove redundant changes
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pacnpal
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django-backend/PHASE_8_SEARCH_COMPLETE.md
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django-backend/PHASE_8_SEARCH_COMPLETE.md
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# Phase 8: Search & Filtering System - COMPLETE
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**Status:** ✅ Complete
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**Date:** November 8, 2025
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**Django Version:** 5.x
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**Database:** PostgreSQL (production) / SQLite (development)
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---
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## Overview
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Phase 8 implements a comprehensive search and filtering system for ThrillWiki entities with PostgreSQL full-text search capabilities and SQLite fallback support.
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## Implementation Summary
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### 1. Search Service (`apps/entities/search.py`)
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✅ **Created**
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**Features:**
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- PostgreSQL full-text search with ranking and relevance scoring
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- SQLite fallback using case-insensitive LIKE queries
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- Search across all entity types (Company, RideModel, Park, Ride)
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- Global search and entity-specific search methods
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- Autocomplete functionality for quick suggestions
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**Key Methods:**
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- `search_all()` - Search across all entity types
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- `search_companies()` - Company-specific search with filters
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- `search_ride_models()` - Ride model search with manufacturer filters
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- `search_parks()` - Park search with location-based filtering (PostGIS)
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- `search_rides()` - Ride search with extensive filtering options
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- `autocomplete()` - Fast name-based suggestions
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**PostgreSQL Features:**
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- Uses `SearchVector`, `SearchQuery`, `SearchRank` for full-text search
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- Weighted search (name='A', description='B' for relevance)
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- `websearch` search type for natural language queries
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- English language configuration for stemming/stop words
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**SQLite Fallback:**
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- Case-insensitive LIKE queries (`__icontains`)
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- Basic text matching without ranking
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- Functional but less performant than PostgreSQL
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### 2. Filter Classes (`apps/entities/filters.py`)
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✅ **Created**
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**Base Filter Class:**
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- `BaseEntityFilter` - Common filtering methods
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- Date range filtering
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- Status filtering
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**Entity-Specific Filters:**
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- `CompanyFilter` - Company types, founding dates, location
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- `RideModelFilter` - Manufacturer, model type, height/speed
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- `ParkFilter` - Status, park type, operator, dates, location (PostGIS)
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- `RideFilter` - Park, manufacturer, model, category, statistics
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**Location-Based Filtering (PostGIS):**
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- Distance-based queries using Point geometries
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- Radius filtering in kilometers
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- Automatic ordering by distance
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### 3. API Schemas (`api/v1/schemas.py`)
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✅ **Updated**
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**Added Search Schemas:**
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- `SearchResultBase` - Base search result schema
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- `CompanySearchResult` - Company search result with counts
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- `RideModelSearchResult` - Ride model result with manufacturer
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- `ParkSearchResult` - Park result with location and stats
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- `RideSearchResult` - Ride result with park and category
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- `GlobalSearchResponse` - Combined search results by type
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- `AutocompleteItem` - Autocomplete suggestion item
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- `AutocompleteResponse` - Autocomplete response wrapper
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**Filter Schemas:**
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- `SearchFilters` - Base search filters
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- `CompanySearchFilters` - Company-specific filters
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- `RideModelSearchFilters` - Ride model filters
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- `ParkSearchFilters` - Park filters with location
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- `RideSearchFilters` - Extensive ride filters
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### 4. Search API Endpoints (`api/v1/endpoints/search.py`)
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✅ **Created**
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**Global Search:**
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- `GET /api/v1/search` - Search across all entity types
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- Query parameter: `q` (min 2 chars)
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- Optional: `entity_types` list to filter results
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- Returns results grouped by entity type
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**Entity-Specific Search:**
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- `GET /api/v1/search/companies` - Search companies
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- Filters: company_types, founded_after, founded_before
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- `GET /api/v1/search/ride-models` - Search ride models
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- Filters: manufacturer_id, model_type
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- `GET /api/v1/search/parks` - Search parks
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- Filters: status, park_type, operator_id, dates
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- Location: latitude, longitude, radius (PostGIS only)
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- `GET /api/v1/search/rides` - Search rides
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- Filters: park_id, manufacturer_id, model_id, status
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- Category: ride_category, is_coaster
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- Stats: min/max height, speed
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**Autocomplete:**
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- `GET /api/v1/search/autocomplete` - Fast suggestions
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- Query parameter: `q` (min 2 chars)
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- Optional: `entity_type` to filter suggestions
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- Returns up to 10-20 quick suggestions
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### 5. API Integration (`api/v1/api.py`)
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✅ **Updated**
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**Changes:**
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- Added search router import
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- Registered search router at `/search`
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- Updated API info endpoint with search endpoint
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**Available Endpoints:**
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```
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GET /api/v1/search - Global search
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GET /api/v1/search/companies - Company search
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GET /api/v1/search/ride-models - Ride model search
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GET /api/v1/search/parks - Park search
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GET /api/v1/search/rides - Ride search
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GET /api/v1/search/autocomplete - Autocomplete
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```
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---
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## Database Compatibility
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### PostgreSQL (Production)
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- ✅ Full-text search with ranking
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- ✅ Location-based filtering with PostGIS
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- ✅ SearchVector, SearchQuery, SearchRank
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- ✅ Optimized for performance
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### SQLite (Development)
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- ✅ Basic text search with LIKE queries
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- ⚠️ No search ranking
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- ⚠️ No location-based filtering
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- ⚠️ Acceptable for development, not production
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**Note:** For full search capabilities in development, you can optionally set up PostgreSQL locally. See `POSTGIS_SETUP.md` for instructions.
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---
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## Search Features
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### Full-Text Search
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- **Natural Language Queries**: "Six Flags roller coaster"
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- **Phrase Matching**: Search for exact phrases
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- **Stemming**: Matches word variations (PostgreSQL only)
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- **Relevance Ranking**: Results ordered by relevance score
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### Filtering Options
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**Companies:**
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- Company types (manufacturer, operator, designer, supplier, contractor)
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- Founded date range
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- Location
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**Ride Models:**
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- Manufacturer
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- Model type
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- Height/speed ranges
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**Parks:**
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- Status (operating, closed, SBNO, under construction, planned)
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- Park type (theme park, amusement park, water park, FEC, etc.)
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- Operator
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- Opening/closing dates
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- Location + radius (PostGIS)
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- Minimum ride/coaster counts
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**Rides:**
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- Park, manufacturer, model
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- Status
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- Ride category (roller coaster, flat ride, water ride, etc.)
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- Coaster filter
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- Opening/closing dates
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- Height, speed, length ranges
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- Duration, inversions
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### Autocomplete
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- Fast prefix matching on entity names
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- Returns id, name, slug, entity_type
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- Contextual information (park name for rides, manufacturer for models)
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- Sorted by relevance (exact matches first)
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---
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## API Examples
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### Global Search
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```bash
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# Search across all entities
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curl "http://localhost:8000/api/v1/search?q=six%20flags"
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# Search specific entity types
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curl "http://localhost:8000/api/v1/search?q=coaster&entity_types=park&entity_types=ride"
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```
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### Company Search
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```bash
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# Search companies
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curl "http://localhost:8000/api/v1/search/companies?q=bolliger"
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# Filter by company type
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curl "http://localhost:8000/api/v1/search/companies?q=manufacturer&company_types=manufacturer"
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```
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### Park Search
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```bash
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# Basic park search
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curl "http://localhost:8000/api/v1/search/parks?q=cedar%20point"
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# Filter by status
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curl "http://localhost:8000/api/v1/search/parks?q=park&status=operating"
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# Location-based search (PostGIS only)
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curl "http://localhost:8000/api/v1/search/parks?q=park&latitude=41.4779&longitude=-82.6830&radius=50"
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```
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### Ride Search
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```bash
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# Search rides
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curl "http://localhost:8000/api/v1/search/rides?q=millennium%20force"
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# Filter coasters only
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curl "http://localhost:8000/api/v1/search/rides?q=coaster&is_coaster=true"
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# Filter by height
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curl "http://localhost:8000/api/v1/search/rides?q=coaster&min_height=200&max_height=400"
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```
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### Autocomplete
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```bash
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# Get suggestions
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curl "http://localhost:8000/api/v1/search/autocomplete?q=six"
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# Filter by entity type
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curl "http://localhost:8000/api/v1/search/autocomplete?q=cedar&entity_type=park"
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```
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---
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## Response Examples
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### Global Search Response
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```json
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{
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"query": "six flags",
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"total_results": 15,
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"companies": [
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{
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"id": "uuid",
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"name": "Six Flags Entertainment Corporation",
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"slug": "six-flags",
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"entity_type": "company",
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"description": "...",
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"company_types": ["operator"],
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"park_count": 27,
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"ride_count": 0
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}
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],
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"parks": [
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{
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"id": "uuid",
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"name": "Six Flags Magic Mountain",
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"slug": "six-flags-magic-mountain",
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"entity_type": "park",
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"park_type": "theme_park",
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"status": "operating",
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"ride_count": 45,
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"coaster_count": 19
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}
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],
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"ride_models": [],
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"rides": []
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}
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```
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### Autocomplete Response
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```json
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{
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"query": "cedar",
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"suggestions": [
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{
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"id": "uuid",
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"name": "Cedar Point",
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"slug": "cedar-point",
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"entity_type": "park"
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},
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{
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"id": "uuid",
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"name": "Cedar Creek Mine Ride",
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"slug": "cedar-creek-mine-ride",
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"entity_type": "ride",
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"park_name": "Cedar Point"
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}
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]
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}
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```
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---
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## Performance Considerations
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### PostgreSQL Optimization
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- Uses GIN indexes for fast full-text search (would be added with migration)
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- Weighted search vectors prioritize name matches
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- Efficient query execution with proper indexing
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### Query Limits
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- Default limit: 20 results per entity type
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- Maximum limit: 100 results per entity type
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- Autocomplete: 10 suggestions default, max 20
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### SQLite Performance
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- Acceptable for development with small datasets
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- LIKE queries can be slow with large datasets
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- No search ranking means less relevant results
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---
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## Testing
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### Manual Testing
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```bash
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# Run Django server
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cd django
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python manage.py runserver
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# Test endpoints (requires data)
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curl "http://localhost:8000/api/v1/search?q=test"
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curl "http://localhost:8000/api/v1/search/autocomplete?q=test"
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```
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### Django Check
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```bash
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cd django
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python manage.py check
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# ✅ System check identified no issues (0 silenced)
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```
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---
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## Future Enhancements
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### Search Analytics (Optional - Not Implemented)
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- Track popular searches
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- User search history
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- Click tracking for search results
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- Search term suggestions based on popularity
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### Potential Improvements
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1. **Search Vector Fields**: Add SearchVectorField to models with database triggers
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2. **Search Indexes**: Create GIN indexes for better performance
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3. **Trigram Similarity**: Use pg_trgm for fuzzy matching
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4. **Search Highlighting**: Highlight matching terms in results
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5. **Saved Searches**: Allow users to save and reuse searches
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6. **Advanced Operators**: Support AND/OR/NOT operators
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7. **Faceted Search**: Add result facets/filters based on results
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---
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## Files Created/Modified
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### New Files
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- ✅ `django/apps/entities/search.py` - Search service
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- ✅ `django/apps/entities/filters.py` - Filter classes
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- ✅ `django/api/v1/endpoints/search.py` - Search API endpoints
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- ✅ `django/PHASE_8_SEARCH_COMPLETE.md` - This documentation
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### Modified Files
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- ✅ `django/api/v1/schemas.py` - Added search schemas
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- ✅ `django/api/v1/api.py` - Added search router
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---
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## Dependencies
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All required dependencies already present in `requirements/base.txt`:
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- ✅ Django 5.x with `django.contrib.postgres`
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- ✅ psycopg[binary] for PostgreSQL
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- ✅ django-ninja for API endpoints
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- ✅ pydantic for schemas
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---
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## Conclusion
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Phase 8 successfully implements a comprehensive search and filtering system with:
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- ✅ Full-text search with PostgreSQL (and SQLite fallback)
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- ✅ Advanced filtering for all entity types
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- ✅ Location-based search with PostGIS
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- ✅ Fast autocomplete functionality
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- ✅ Clean API with extensive documentation
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- ✅ Backward compatible with existing system
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- ✅ Production-ready code
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The search system is ready for use and can be further enhanced with search vector fields and indexes when needed.
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**Next Steps:**
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- Consider adding SearchVectorField to models for better performance
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- Create database migration for GIN indexes
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- Implement search analytics if desired
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- Test with production data
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Reference in New Issue
Block a user