#!/usr/bin/env python3
"""
Analyse des résultats d'anonymisation.
"""
import json
from pathlib import Path
from collections import Counter
from evaluation import LeakScanner

def main():
    # Fichiers générés
    base_name = "003_simple_compte_rendu_CRO_23155084"
    output_dir = Path("tests/ground_truth/pdfs/anonymized_test")
    
    audit_path = output_dir / f"{base_name}.audit.jsonl"
    redacted_pdf = output_dir / f"{base_name}.redacted_raster.pdf"
    text_path = output_dir / f"{base_name}.pseudonymise.txt"
    
    print("="*80)
    print("ANALYSE DES RÉSULTATS D'ANONYMISATION")
    print("="*80)
    print(f"\n📄 Document: {base_name}.pdf")
    print(f"   Type: Compte-rendu opératoire (CRO)")
    
    # Analyser l'audit
    if audit_path.exists():
        print(f"\n📊 ANALYSE DE L'AUDIT")
        print(f"   Fichier: {audit_path.name}")
        
        pii_list = []
        with open(audit_path, 'r', encoding='utf-8') as f:
            for line in f:
                if line.strip():
                    pii_list.append(json.loads(line))
        
        print(f"\n   Total PII détectés: {len(pii_list)}")
        
        # Compter par type
        type_counts = Counter(pii['kind'] for pii in pii_list)
        
        print(f"\n   Répartition par type:")
        for pii_type, count in sorted(type_counts.items(), key=lambda x: -x[1]):
            print(f"     {pii_type:20s} : {count:3d}")
        
        # Afficher les PII uniques (page 0 uniquement)
        page0_pii = [p for p in pii_list if p.get('page') == 0]
        
        if page0_pii:
            print(f"\n   PII détectés sur la page principale:")
            for pii in page0_pii:
                original = pii.get('original', '')[:60]
                print(f"     • {pii['kind']:20s} : {original}")
        
        # Afficher les noms extraits (propagation globale)
        extracted_names = [p for p in pii_list if p.get('kind') == 'NOM_EXTRACTED']
        if extracted_names:
            unique_names = set(p['original'] for p in extracted_names)
            print(f"\n   Noms propagés globalement ({len(unique_names)} uniques):")
            for name in sorted(unique_names):
                count = sum(1 for p in extracted_names if p['original'] == name)
                print(f"     • {name:20s} : {count} occurrences")
    
    # Afficher le texte anonymisé
    if text_path.exists():
        print(f"\n📝 TEXTE ANONYMISÉ")
        print(f"   Fichier: {text_path.name}")
        
        with open(text_path, 'r', encoding='utf-8') as f:
            text = f.read()
        
        print(f"\n   Extrait (200 premiers caractères):")
        print("   " + "-"*76)
        lines = text[:200].split('\n')
        for line in lines[:5]:
            print(f"   {line}")
        print("   " + "-"*76)
    
    # Scanner les fuites
    if redacted_pdf.exists() and audit_path.exists():
        print(f"\n🔒 SCAN DE FUITE")
        print(f"   PDF anonymisé: {redacted_pdf.name}")
        
        scanner = LeakScanner()
        leak_report = scanner.scan(redacted_pdf, audit_path)
        
        if leak_report.is_safe:
            print(f"\n   ✓ DOCUMENT SÛR")
            print(f"     Aucune fuite détectée")
        else:
            print(f"\n   ✗ ATTENTION - {leak_report.leak_count} fuite(s)")
            
            # Par sévérité
            print(f"\n   Fuites par sévérité:")
            for severity, count in sorted(leak_report.severity_counts.items()):
                print(f"     {severity:10s} : {count}")
            
            # Détails
            print(f"\n   Détails des fuites:")
            for i, leak in enumerate(leak_report.leaks[:10], 1):
                print(f"     {i}. [{leak['severity']}] {leak['type']}")
                print(f"        {leak['message']}")
            
            if leak_report.leak_count > 10:
                print(f"     ... et {leak_report.leak_count - 10} autres")
    
    print("\n" + "="*80)
    print("✨ Analyse terminée")
    print("="*80)
    
    print(f"\n💡 Fichiers disponibles:")
    print(f"   - PDF anonymisé (raster): {redacted_pdf.name}")
    print(f"   - PDF anonymisé (vector): {base_name}.redacted_vector.pdf")
    print(f"   - Texte anonymisé: {text_path.name}")
    print(f"   - Audit complet: {audit_path.name}")
    
    print(f"\n📂 Répertoire: {output_dir}")
    
    print(f"\n🔍 Pour voir le PDF:")
    print(f"   xdg-open {redacted_pdf}")

if __name__ == "__main__":
    main()