"""
Pattern Analysis Learner - Placeholder Implementation
This module will be fully implemented in Task 9
"""
from typing import Dict, Any
from sqlalchemy.orm import Session


class PatternAnalysisLearner:
    """
    Analyzes patterns in completed interviews to identify predictive questions
    and update selection weights.
    
    NOTE: This is a placeholder implementation for Task 12 (API endpoints).
    Full implementation will be completed in Task 9.
    """
    
    def __init__(self, db_session: Session, min_dataset_size: int = 50):
        """
        Initialize pattern analysis learner.
        
        Args:
            db_session: Database session
            min_dataset_size: Minimum number of completed interviews required
        """
        self.db_session = db_session
        self.min_dataset_size = min_dataset_size
        self.low_value_threshold = 0.3
    
    def analyze_patterns(self) -> Dict[str, Any]:
        """
        Run pattern analysis on completed interviews.
        
        This is a placeholder that returns mock results.
        Full implementation in Task 9 will:
        1. Query completed interviews with outcomes
        2. Group by outcome (hired/rejected)
        3. Identify question sequences in successful interviews
        4. Calculate topic/type correlations with success
        5. Update question selection weights
        6. Flag low-value questions
        
        Returns:
            Dictionary with analysis results
        """
        # Placeholder implementation
        return {
            "interviews_analyzed": 0,
            "questions_updated": 0,
            "low_value_questions": [],
            "message": "Pattern analysis not yet implemented (Task 9)"
        }
    
    def identify_predictive_questions(self, interviews) -> Dict[int, float]:
        """
        Identify which questions best predict success.
        
        Placeholder implementation.
        
        Args:
            interviews: List of completed interviews
            
        Returns:
            Dictionary mapping question_id to predictive_score
        """
        return {}
    
    def update_selection_weights(self, predictive_scores: Dict[int, float]):
        """
        Update question selection weights in database.
        
        Placeholder implementation.
        
        Args:
            predictive_scores: Dictionary mapping question_id to predictive_score
        """
        pass