Update performance_analyzer.py

performance_analyzer.py

@@ -1,56 +1,34 @@
 import logging
 from typing import Dict, List
 
-logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger(__name__)
-
 class PerformanceAnalyzer:
-    def __init__(self, db_connection):  # Construtor que aceita a conexão do banco
+    def __init__(self, db_connection):
         self.conn = db_connection
-    
+
     def analyze_user_performance(self, user_id: str) -> Dict:
         try:
             cursor = self.conn.cursor()
             cursor.execute('''
-                SELECT 
-                    topic,
-                    AVG(performance_score) as avg_score,
-                    COUNT(*) as total_sessions
+                SELECT topic, AVG(performance_score) as avg_score
                 FROM study_progress
                 WHERE user_id = ?
                 GROUP BY topic
             ''', (user_id,))
-            
-            results = cursor.fetchall()
-            return {
-                'performance_by_topic': [dict(r) for r in results],
-                'overall_score': self._calculate_overall_score(results)
-            }
+            return dict(cursor.fetchall())
         except Exception as e:
-            logger.error(f"Erro ao analisar performance: {e}")
+            logging.error(f"Erro ao analisar performance: {e}")
             return {}
 
     def get_weak_areas(self, user_id: str) -> List[str]:
         try:
             cursor = self.conn.cursor()
             cursor.execute('''
-                SELECT 
-                    topic,
-                    AVG(performance_score) as avg_score
+                SELECT topic
                 FROM study_progress
-                WHERE user_id = ?
+                WHERE user_id = ? AND performance_score < 70
                 GROUP BY topic
-                HAVING avg_score < 70
-                ORDER BY avg_score ASC
             ''', (user_id,))
-            
             return [row['topic'] for row in cursor.fetchall()]
         except Exception as e:
-            logger.error(f"Erro ao identificar áreas fracas: {e}")
-            return []
-
-    def _calculate_overall_score(self, results) -> float:
-        if not results:
-            return 0.0
-        total_score = sum(r['avg_score'] for r in results)
-        return round(total_score / len(results), 2)
+            logging.error(f"Erro ao buscar áreas fracas: {e}")
+            return []