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rpa_vision_v3/monitor_matching_health.py
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178
rpa_vision_v3/monitor_matching_health.py
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#!/usr/bin/env python3
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"""
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Dashboard de monitoring de la santé du système de matching.
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"""
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import json
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import time
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import sys
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from pathlib import Path
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from datetime import datetime, timedelta
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from typing import Dict, Any, List
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from collections import deque
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class MatchingHealthMonitor:
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"""Moniteur de santé du système de matching."""
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def __init__(
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self,
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failed_matches_dir: str = "data/failed_matches",
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alert_threshold: int = 5,
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window_minutes: int = 10
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):
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self.failed_matches_dir = Path(failed_matches_dir)
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self.alert_threshold = alert_threshold
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self.window_minutes = window_minutes
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self.recent_failures = deque(maxlen=100)
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self.last_check = None
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def check_health(self) -> Dict[str, Any]:
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"""Vérifier la santé du système."""
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now = datetime.now()
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# Charger les nouveaux échecs
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new_failures = self._load_new_failures(since=self.last_check)
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self.recent_failures.extend(new_failures)
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self.last_check = now
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# Calculer les métriques
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metrics = {
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'timestamp': now.isoformat(),
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'total_failures_tracked': len(self.recent_failures),
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'failures_last_10min': self._count_recent_failures(minutes=10),
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'failures_last_hour': self._count_recent_failures(minutes=60),
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'failure_rate_per_min': self._calculate_failure_rate(),
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'avg_confidence': self._calculate_avg_confidence(),
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'alerts': []
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}
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# Générer des alertes
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metrics['alerts'] = self._generate_alerts(metrics)
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return metrics
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def _load_new_failures(self, since: datetime = None) -> List[Dict[str, Any]]:
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"""Charger les nouveaux échecs."""
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if not self.failed_matches_dir.exists():
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return []
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if since is None:
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since = datetime.now() - timedelta(hours=1)
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new_failures = []
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for match_dir in self.failed_matches_dir.iterdir():
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if not match_dir.is_dir():
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continue
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try:
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timestamp_str = match_dir.name.replace("failed_match_", "")
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timestamp = datetime.strptime(timestamp_str, "%Y%m%d_%H%M%S")
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if timestamp > since:
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report_path = match_dir / "report.json"
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if report_path.exists():
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with open(report_path, 'r') as f:
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report = json.load(f)
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report['_timestamp'] = timestamp
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new_failures.append(report)
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except:
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continue
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return sorted(new_failures, key=lambda x: x['_timestamp'])
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def _count_recent_failures(self, minutes: int) -> int:
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"""Compter les échecs récents."""
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cutoff = datetime.now() - timedelta(minutes=minutes)
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return sum(1 for f in self.recent_failures if f['_timestamp'] > cutoff)
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def _calculate_failure_rate(self) -> float:
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"""Calculer le taux d'échec par minute."""
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if not self.recent_failures:
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return 0.0
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recent_count = self._count_recent_failures(minutes=self.window_minutes)
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return recent_count / self.window_minutes
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def _calculate_avg_confidence(self) -> float:
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"""Calculer la confiance moyenne."""
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if not self.recent_failures:
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return 0.0
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confidences = [f['matching_results']['best_confidence'] for f in self.recent_failures]
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return sum(confidences) / len(confidences)
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def _generate_alerts(self, metrics: Dict[str, Any]) -> List[Dict[str, str]]:
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"""Générer des alertes."""
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alerts = []
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if metrics['failures_last_10min'] >= self.alert_threshold:
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alerts.append({
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'level': 'WARNING',
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'type': 'HIGH_FAILURE_RATE',
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'message': f"{metrics['failures_last_10min']} échecs en 10 min"
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})
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if metrics['avg_confidence'] < 0.60:
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alerts.append({
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'level': 'CRITICAL',
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'type': 'LOW_CONFIDENCE',
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'message': f"Confiance moyenne: {metrics['avg_confidence']:.3f}"
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})
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return alerts
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def print_dashboard(self, metrics: Dict[str, Any]):
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"""Afficher le dashboard."""
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print("\n" + "="*70)
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print("DASHBOARD DE SANTÉ DU MATCHING")
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print("="*70)
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print(f"Timestamp: {metrics['timestamp']}")
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print(f"\n📊 Métriques")
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print(f" • Échecs suivis: {metrics['total_failures_tracked']}")
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print(f" • Échecs (10 min): {metrics['failures_last_10min']}")
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print(f" • Échecs (1 heure): {metrics['failures_last_hour']}")
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print(f" • Taux: {metrics['failure_rate_per_min']:.2f}/min")
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print(f" • Confiance moy: {metrics['avg_confidence']:.3f}")
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if metrics['alerts']:
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print(f"\n🚨 Alertes ({len(metrics['alerts'])})")
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for alert in metrics['alerts']:
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icon = {'CRITICAL': '🔴', 'WARNING': '🟡', 'INFO': '🔵'}.get(alert['level'], '⚪')
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print(f" {icon} [{alert['level']}] {alert['type']}")
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print(f" {alert['message']}")
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else:
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print(f"\n✅ Système en bonne santé")
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print("\n" + "="*70)
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def main():
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import argparse
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parser = argparse.ArgumentParser(description="Monitorer la santé du matching")
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parser.add_argument('--continuous', action='store_true', help="Mode continu")
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parser.add_argument('--interval', type=int, default=60, help="Intervalle (s)")
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args = parser.parse_args()
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monitor = MatchingHealthMonitor()
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if args.continuous:
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print("🔄 Monitoring continu... (Ctrl+C pour arrêter)")
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try:
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while True:
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metrics = monitor.check_health()
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monitor.print_dashboard(metrics)
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time.sleep(args.interval)
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except KeyboardInterrupt:
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print("\n✓ Arrêté")
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else:
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metrics = monitor.check_health()
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monitor.print_dashboard(metrics)
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return 0
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if __name__ == '__main__':
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sys.exit(main())
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