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- Added EntitySuggestionManager.vue to manage entity suggestions and authentication. - Created EntitySuggestionModal.vue for displaying suggestions and adding new entities. - Integrated AuthManager for user authentication within the suggestion modal. - Enhanced signal handling in start-servers.sh for graceful shutdown of servers. - Improved server startup script to ensure proper cleanup and responsiveness to termination signals. - Added documentation for signal handling fixes and usage instructions.
140 lines
4.1 KiB
Markdown
140 lines
4.1 KiB
Markdown
# ThrillWiki Trending & New Content System Architecture
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## System Overview
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This document outlines the architecture for implementing real trending and new content functionality to replace the current mock data implementation on the ThrillWiki home page.
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## Current State Analysis
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### Frontend Structure (Vue 3 + TypeScript)
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- **Home.vue** expects specific data formats:
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- **Trending Content**: `{id, name, location, category, rating, rank, views, views_change, slug}`
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- **New Content**: `{id, name, location, category, date_added, slug}`
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- **Tabs Supported**:
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- Trending: Rides, Parks, Reviews
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- New: Recently Added, Newly Opened, Upcoming
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### Backend Infrastructure
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- **Django REST Framework** with comprehensive ViewSets
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- **pghistory** already tracking model changes
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- **Existing endpoints** for recent changes, openings, closures
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- **Models**: Park and Ride with ratings, status, dates
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## Proposed Architecture
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### 1. Data Flow Architecture
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```mermaid
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flowchart TD
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A[User Views Page] --> B[View Tracking Middleware]
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B --> C[PageView Model]
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D[Trending Calculation Job] --> E[Trending Algorithm]
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E --> F[Cache Layer]
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G[Frontend Request] --> H[API Endpoints]
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H --> F
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F --> I[Serialized Response]
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I --> J[Frontend Display]
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K[Management Command] --> D
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L[Celery/Cron Schedule] --> K
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```
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### 2. Database Schema Design
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#### PageView Model
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```python
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class PageView(models.Model):
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content_type = models.ForeignKey(ContentType)
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object_id = models.PositiveIntegerField()
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content_object = GenericForeignKey('content_type', 'object_id')
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user_session = models.CharField(max_length=40)
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ip_address = models.GenericIPAddressField()
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user_agent = models.TextField()
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timestamp = models.DateTimeField(auto_now_add=True)
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class Meta:
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indexes = [
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models.Index(fields=['content_type', 'object_id', 'timestamp']),
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models.Index(fields=['timestamp']),
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]
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```
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### 3. Trending Algorithm
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#### Calculation Components
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- **View Count Weight**: Recent page views (configurable time window)
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- **Rating Weight**: Average rating from Park/Ride models
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- **Recency Boost**: Recently added/updated content bonus
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- **Category Balancing**: Ensure diverse content across categories
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#### Formula
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```
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Trending Score = (View Score × 0.4) + (Rating Score × 0.3) + (Recency Score × 0.2) + (Engagement Score × 0.1)
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```
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### 4. API Endpoints Design
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#### Trending Endpoint
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```
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GET /api/v1/trending/?tab={rides|parks|reviews}&limit=6
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```
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#### New Content Endpoint
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```
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GET /api/v1/new-content/?tab={recently-added|newly-opened|upcoming}&limit=4
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```
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### 5. Caching Strategy
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#### Cache Keys
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- `trending_rides_6h`: Trending rides cache (6 hour TTL)
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- `trending_parks_6h`: Trending parks cache (6 hour TTL)
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- `new_content_24h`: New content cache (24 hour TTL)
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#### Cache Invalidation
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- Manual refresh via management command
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- Automatic refresh on schedule
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- Cache warming during low-traffic periods
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### 6. Performance Considerations
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#### View Tracking Optimization
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- Async middleware for non-blocking view tracking
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- Batch insert for high-volume periods
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- IP-based rate limiting to prevent spam
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#### Database Optimization
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- Proper indexing on PageView model
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- Aggregate tables for trending calculations
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- Periodic cleanup of old PageView records
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## Implementation Plan
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The implementation follows the todo list with these key phases:
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1. **Database Layer**: PageView model and migrations
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2. **Algorithm Design**: Trending calculation logic
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3. **API Layer**: New endpoints and serializers
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4. **Tracking System**: Middleware for view capture
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5. **Caching Layer**: Performance optimization
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6. **Automation**: Management commands and scheduling
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7. **Frontend Integration**: Replace mock data
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8. **Testing & Monitoring**: Comprehensive coverage
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## Security & Privacy
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- Anonymous view tracking (no personal data)
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- Session-based rate limiting
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- User agent validation
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- IP address anonymization options
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## Monitoring & Analytics
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- View tracking success rates
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- Trending calculation performance
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- Cache hit/miss ratios
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- API response times
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- Algorithm effectiveness metrics |