backend/statistics.py

"""
Statistics computation utilities
"""


def compute_progress(scored_count, total_count):
    """Calcule le pourcentage de progression"""
    if total_count == 0:
        return 0.0
    return scored_count / total_count


def compute_score_distribution(feedback_scores):
    """
    Calcule la distribution des scores

    Args:
        feedback_scores: Dict {idx: score}

    Returns:
        Dict {score: count} pour scores 0-5
    """
    scores_list = list(feedback_scores.values())
    return {i: scores_list.count(i) for i in range(6)}


def compute_average_score(feedback_scores):
    """Calcule le score moyen"""
    if not feedback_scores:
        return 0.0
    scores_list = list(feedback_scores.values())
    return sum(scores_list) / len(scores_list)


def compute_most_common_score(feedback_scores):
    """
    Trouve le score le plus fréquent

    Returns:
        Tuple (score, count)
    """
    distribution = compute_score_distribution(feedback_scores)
    return max(distribution.items(), key=lambda x: x[1])


def find_unscored_indices(items_with_positive, feedback_scores):
    """
    Trouve les indices des items non encore scorés

    Returns:
        Liste d'indices
    """
    return [idx for idx, _ in items_with_positive if idx not in feedback_scores]