Tautulli Analytics

Tautulli Analytics Integration

This skill helps with Tautulli analytics features in homescreen-hero. Tautulli provides streaming metrics and watch history from Plex servers.

Key Files

• tautulli_client.py - Tautulli API client
• tautulli_analytics.py - Analytics collection logic
• analytics.py - Database operations for analytics
• analytics.py - API endpoints

Tautulli Client Overview

The TautulliClient wraps the Tautulli API v2. It handles:

• API authentication via API key in URL params
• Response parsing (Tautulli wraps responses in {"response": {"result": "success", "data": ...}})
• Error handling for timeouts, auth failures, HTTP errors

Key Methods

Configuration

Tautulli requires:

• HSH_TAUTULLI_API_KEY environment variable (or in config.yaml)
• HSH_TAUTULLI_BASE_URL environment variable (default: http://localhost:8181)
• enabled: true in config.yaml under tautulli section

Analytics Module

The tautulli_analytics.py module collects watch statistics and stores them in SQLite:

Main Functions

collect_analytics_for_collections(config, collection_names, rotation_id)

• Collects watch stats for specified collections
• Finds collections in Plex libraries using rating_key
• Aggregates stats from all items in each collection
• Stores snapshots in the database via record_collection_analytics()
• Returns summary dict with collected, failed, and total_collections

collect_analytics_for_all_active(config)

• Collects analytics for all currently promoted collections
• Queries Plex for collections with visibility > 0
• Uses collect_analytics_for_collections() internally

Data Flow

1. Find collection in Plex - Search enabled libraries for collection by name
2. Get rating_key - Extract Plex's internal ID for the collection
3. Query Tautulli - Use rating_key to get watch stats from Tautulli API
4. Aggregate - Sum stats across all items in the collection
5. Store - Save snapshot to collection_analytics table in SQLite

Common Tasks

Adding a New Chart

When adding a new chart to the frontend:

1. Check if the Tautulli API endpoint exists in tautulli_client.py
2. Add method to client if needed (follow pattern of existing methods)
3. Create API endpoint in homescreen_hero/web/routers/analytics.py
4. Fetch data in React component using the new endpoint
5. Use Recharts components to visualize

Testing Tautulli Connection

from homescreen_hero.core.integrations.tautulli_client import get_tautulli_client
from homescreen_hero.core.config.loader import load_config

config = load_config()
client = get_tautulli_client(config)
if client:
    success, error = client.ping()
    print(f"Tautulli connection: {'OK' if success else f'Failed - {error}'}")

Fetching Watch Stats

# Get stats for a specific collection (by rating_key)
stats = client.get_collection_stats(rating_key=12345, query_days=30)
print(f"Total plays: {stats['total_plays']}")

# Get play history
history = client.get_history(length=100)
for entry in history:
    print(f"{entry['user']}: {entry['title']} at {entry['date']}")

API Response Formats

get_collection_stats

{
  "total_plays": 42,
  "total_duration": 7200,
  "total_time": "2h 0m"
}

get_plays_by_date

{
  "categories": ["2024-01-01", "2024-01-02", ...],
  "series": {
    "Movies": [5, 8, 3, ...],
    "TV": [12, 15, 10, ...]
  }
}

get_plays_by_stream_type

{
  "categories": ["2024-01-01", "2024-01-02", ...],
  "series": {
    "Direct Play": [5, 8, ...],
    "Direct Stream": [3, 2, ...],
    "Transcode": [1, 4, ...],
    "Concurrent Streams": [8, 12, ...]  // Max concurrent per day
  }
}

Database Schema

Analytics are stored in collection_analytics table:

• collection_name - Name of the collection
• plex_library - Library name (Movies, TV Shows, etc.)
• rating_key - Plex rating key
• total_plays - Total play count
• total_duration_seconds - Total watch time in seconds
• unique_users - Count of unique users (nullable)
• rotation_id - FK to rotation that triggered collection (nullable)
• collected_at - Timestamp of collection
• extra_data - JSON field for additional metadata

Notes

• Tautulli tracks stats per-item, not per-collection
• Analytics module aggregates item-level stats to collection-level
• Concurrent streams calculation requires analyzing overlapping watch history timestamps
• All API methods include error handling and logging
• Use logger.debug() for API requests, logger.info() for successful operations, logger.error() for failures