mirror of
https://github.com/plexguide/Huntarr-Sonarr.git
synced 2025-12-16 20:04:16 -06:00
update
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Admin9705
@@ -2746,6 +2746,7 @@ let huntarrUI = {
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<div class="stat-value ${successClass}">${successRate}%</div>
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</div>
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`);
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console.log('Added success rate card:', successRate, successClass);
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// Average response time
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if (stats.avg_response_time !== undefined) {
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@@ -2785,7 +2786,10 @@ let huntarrUI = {
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if (statisticsCards.length === 0) {
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statisticsContent.innerHTML = '<div class="loading-text">No recent activity</div>';
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} else {
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statisticsContent.innerHTML = statisticsCards.join('');
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const finalHTML = statisticsCards.join('');
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console.log('Final Prowlarr statistics HTML:', finalHTML);
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console.log('Number of stat cards:', statisticsCards.length);
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statisticsContent.innerHTML = finalHTML;
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}
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},
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@@ -319,21 +319,52 @@ def _fetch_detailed_stats():
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if status_response.status_code == 200:
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stats['connected'] = True
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# Get API history/usage statistics
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# Get API history/usage statistics using the optimized /since endpoint
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try:
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history_url = f"{api_url.rstrip('/')}/api/v1/history"
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history_response = requests.get(history_url, headers=headers, timeout=15, params={'pageSize': 50})
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# Calculate date range for today and yesterday
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from datetime import datetime, timedelta
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now = datetime.utcnow()
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today = now.date()
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yesterday = today - timedelta(days=1)
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# Use the /history/since endpoint for efficient date-based filtering
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# This gets ALL records since yesterday without pagination limits
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yesterday_start = datetime.combine(yesterday, datetime.min.time())
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since_date = yesterday_start.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
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history_since_url = f"{api_url.rstrip('/')}/api/v1/history/since"
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params = {'date': since_date}
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prowlarr_logger.debug(f"Fetching history since {since_date} using /history/since endpoint")
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history_response = requests.get(history_since_url, headers=headers, timeout=15, params=params)
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all_records = []
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if history_response.status_code == 200:
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history_data = history_response.json()
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# /history/since returns an array directly, not a paged response
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all_records = history_response.json()
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prowlarr_logger.debug(f"Retrieved {len(all_records)} history records from /history/since endpoint")
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else:
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# Fallback to regular history endpoint if /since is not available
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prowlarr_logger.debug(f"/history/since failed with status {history_response.status_code}, falling back to regular history endpoint")
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history_url = f"{api_url.rstrip('/')}/api/v1/history"
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params = {
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'pageSize': 500, # Larger page size for fallback
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'sortKey': 'date',
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'sortDirection': 'descending'
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}
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fallback_response = requests.get(history_url, headers=headers, timeout=15, params=params)
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if fallback_response.status_code == 200:
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fallback_data = fallback_response.json()
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all_records = fallback_data.get('records', [])
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prowlarr_logger.debug(f"Fallback: Retrieved {len(all_records)} history records from regular endpoint")
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if all_records:
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# Total records gives us approximate API call count
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stats['total_api_calls'] = history_data.get('totalRecords', 0)
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stats['total_api_calls'] = len(all_records)
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# Analyze recent activity (overall and per indexer)
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from datetime import datetime, timedelta
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now = datetime.utcnow()
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today = now.date()
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yesterday = today - timedelta(days=1)
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searches_today = 0
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searches_yesterday = 0
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@@ -343,8 +374,9 @@ def _fetch_detailed_stats():
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# Track per-indexer statistics
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indexer_daily_stats = {}
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records = history_data.get('records', [])
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for record in records:
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prowlarr_logger.debug(f"Processing {len(all_records)} history records for date analysis")
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for record in all_records:
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try:
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# Parse the date from the record
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record_date = datetime.fromisoformat(record.get('date', '').replace('Z', '+00:00')).date()
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@@ -389,19 +421,79 @@ def _fetch_detailed_stats():
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stats['recent_failed_searches'] = failed_searches
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stats['indexer_daily_stats'] = indexer_daily_stats
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prowlarr_logger.debug(f"Calculated stats - Today: {searches_today}, Yesterday: {searches_yesterday}, Success rate: {stats['recent_success_rate']}%")
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except Exception as e:
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prowlarr_logger.debug(f"History endpoint failed: {str(e)}")
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# Get indexer performance statistics
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# Get indexer performance statistics with date filtering for today's data
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try:
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# Use indexerstats endpoint with date filtering for accurate daily statistics
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today_start = datetime.combine(today, datetime.min.time())
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today_end = datetime.combine(today + timedelta(days=1), datetime.min.time())
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indexerstats_url = f"{api_url.rstrip('/')}/api/v1/indexerstats"
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indexerstats_response = requests.get(indexerstats_url, headers=headers, timeout=15)
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indexerstats_params = {
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'startDate': today_start.strftime('%Y-%m-%dT%H:%M:%S.%fZ'),
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'endDate': today_end.strftime('%Y-%m-%dT%H:%M:%S.%fZ')
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}
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prowlarr_logger.debug(f"Fetching indexer stats for today: {today_start} to {today_end}")
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indexerstats_response = requests.get(indexerstats_url, headers=headers, timeout=15, params=indexerstats_params)
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if indexerstats_response.status_code == 200:
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indexerstats_data = indexerstats_response.json()
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indexer_stats = indexerstats_data.get('indexers', [])
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if indexer_stats:
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# Update individual indexer stats with indexerstats data for consistency
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for indexer_stat in indexer_stats:
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indexer_id = indexer_stat.get('indexerId')
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queries_today = indexer_stat.get('numberOfQueries', 0)
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if indexer_id and queries_today > 0:
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# Update the indexer_daily_stats with indexerstats data for consistency
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if indexer_id not in stats.get('indexer_daily_stats', {}):
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stats.setdefault('indexer_daily_stats', {})[indexer_id] = {
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'searches_today': 0,
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'searches_yesterday': 0,
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'successful_today': 0,
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'failed_today': 0
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}
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# Use indexerstats data as the authoritative source for today's count
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stats['indexer_daily_stats'][indexer_id]['searches_today'] = queries_today
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# Calculate main total from updated indexer stats for consistency
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total_searches_today = sum(
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indexer_data.get('searches_today', 0)
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for indexer_data in stats.get('indexer_daily_stats', {}).values()
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)
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if total_searches_today > 0:
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stats['searches_today'] = total_searches_today
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prowlarr_logger.debug(f"Using consistent indexerstats total: {total_searches_today} searches (sum of all indexers)")
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# Calculate main statistics from indexerstats data for consistency
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total_grabs = sum(stat.get('numberOfGrabs', 0) for stat in indexer_stats)
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total_failed = sum(stat.get('numberOfFailedQueries', 0) for stat in indexer_stats)
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# Update main success rate to match indexer calculations
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if total_searches_today > 0:
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stats['recent_success_rate'] = round((total_grabs / total_searches_today) * 100, 1)
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else:
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stats['recent_success_rate'] = 0
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# Update total API calls to match indexerstats
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stats['total_api_calls'] = sum(stat.get('numberOfQueries', 0) for stat in indexer_stats)
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stats['recent_failed_searches'] = total_failed
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prowlarr_logger.debug(f"Main stats updated - Success rate: {stats['recent_success_rate']}%, Total API calls: {stats['total_api_calls']}, Failed: {total_failed}")
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# Debug logging to track individual indexer contributions
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for idx_id, idx_data in stats.get('indexer_daily_stats', {}).items():
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prowlarr_logger.debug(f"Indexer {idx_id}: {idx_data.get('searches_today', 0)} searches today")
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# Calculate average response time
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total_response_time = 0
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total_queries = 0
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@@ -415,7 +507,7 @@ def _fetch_detailed_stats():
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indexer_id = indexer_stat.get('indexerId')
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indexer_name = indexer_stat.get('indexerName', 'Unknown')
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# Get daily stats for this indexer
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# Get daily stats for this indexer (now updated with consistent indexerstats data)
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daily_stats = stats.get('indexer_daily_stats', {}).get(indexer_id, {
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'searches_today': 0,
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'searches_yesterday': 0,
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@@ -423,10 +515,13 @@ def _fetch_detailed_stats():
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'failed_today': 0
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})
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# Calculate success rate for today
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# Use indexerstats numberOfQueries as the authoritative source for today's searches
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indexer_searches_today = queries # This comes from indexerstats API
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# Calculate success rate for today using indexerstats data (consistent with main calculation)
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today_success_rate = 0
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if daily_stats['searches_today'] > 0:
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today_success_rate = round((daily_stats['successful_today'] / daily_stats['searches_today']) * 100, 1)
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if indexer_searches_today > 0:
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today_success_rate = round((grabs / indexer_searches_today) * 100, 1)
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indexer_data = {
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'id': indexer_id,
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@@ -434,10 +529,10 @@ def _fetch_detailed_stats():
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'response_time': response_time,
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'queries': queries,
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'grabs': grabs,
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'success_rate': round((grabs / queries) * 100, 1) if queries > 0 else 0,
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'searches_today': daily_stats['searches_today'],
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'searches_yesterday': daily_stats['searches_yesterday'],
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'successful_today': daily_stats['successful_today'],
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'success_rate': today_success_rate, # Use consistent calculation method
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'searches_today': indexer_searches_today, # Use consistent indexerstats data
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'searches_yesterday': daily_stats['searches_yesterday'], # Keep history data for yesterday
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'successful_today': grabs, # Use grabs from indexerstats as successful searches
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'failed_today': daily_stats['failed_today'],
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'today_success_rate': today_success_rate
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}
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@@ -450,9 +545,11 @@ def _fetch_detailed_stats():
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# Store individual stats by name for easy lookup
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individual_indexer_stats[indexer_name] = indexer_data
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# Calculate overall average response time
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# Calculate overall average response time (weighted average across all indexers)
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avg_response_time = round(total_response_time / max(total_queries, 1), 0)
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stats['avg_response_time'] = avg_response_time
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prowlarr_logger.debug(f"Calculated weighted average response time: {avg_response_time}ms from {len(indexer_stats)} indexers")
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stats['indexer_performance'] = sorted(indexer_performance, key=lambda x: x['queries'], reverse=True)
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stats['individual_indexer_stats'] = individual_indexer_stats
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