#!/usr/bin/env python3
"""
Merge Batch 15: Add 4 Bonus Brazilian Institutions to GlobalGLAM Dataset

This script adds 4 NEW institutions discovered during Batch 14 Wikidata searches
that were not previously present in the GlobalGLAM dataset.

Date: 2025-11-11
Batch: 15 (Bonus Institutions)
"""

import yaml
from datetime import datetime, timezone
from pathlib import Path
import sys

def load_yaml(filepath):
    """Load YAML file."""
    with open(filepath, 'r', encoding='utf-8') as f:
        return yaml.safe_load(f)

def save_yaml(data, filepath):
    """Save data to YAML file."""
    with open(filepath, 'w', encoding='utf-8') as f:
        yaml.dump(data, f, allow_unicode=True, default_flow_style=False, sort_keys=False)

def create_backup(filepath):
    """Create timestamped backup of file."""
    backup_path = f"{filepath}.bak.batch15"
    with open(filepath, 'r', encoding='utf-8') as source:
        with open(backup_path, 'w', encoding='utf-8') as target:
            target.write(source.read())
    print(f"✅ Backup created: {backup_path}")
    return backup_path

def add_bonus_institutions(main_data, bonus_data):
    """
    Add bonus institutions to main dataset.
    These are NEW institutions, so we simply append them.
    
    Args:
        main_data: Main GlobalGLAM dataset (list of institutions)
        bonus_data: Bonus institutions to add (list of 4 new institutions)
    
    Returns:
        tuple: (updated_data, additions_count)
    """
    additions = 0
    
    # Get existing institution IDs to avoid accidental duplicates
    existing_ids = {inst['id'] for inst in main_data}
    
    for bonus_inst in bonus_data:
        bonus_id = bonus_inst['id']
        
        # Double-check this is truly a new institution
        if bonus_id in existing_ids:
            print(f"⚠️  WARNING: Institution already exists: {bonus_inst['name']} ({bonus_id})")
            print(f"   Skipping to avoid duplicate...")
            continue
        
        # Add new institution
        main_data.append(bonus_inst)
        additions += 1
        print(f"✅ Added: {bonus_inst['name']} (Wikidata: {get_wikidata_id(bonus_inst)})")
    
    return main_data, additions

def get_wikidata_id(institution):
    """Extract Wikidata Q-number from institution identifiers."""
    for identifier in institution.get('identifiers', []):
        if identifier.get('identifier_scheme') == 'Wikidata':
            return identifier.get('identifier_value')
    return None

def main():
    """Main execution."""
    print("=" * 80)
    print("BATCH 15 MERGE: Adding Bonus Brazilian Institutions")
    print("=" * 80)
    print()
    
    # File paths
    main_file = Path("data/instances/all/globalglam-20251111.yaml")
    bonus_file = Path("data/instances/brazil/batch15_bonus_institutions.yaml")
    
    # Verify files exist
    if not main_file.exists():
        print(f"❌ ERROR: Main dataset not found: {main_file}")
        sys.exit(1)
    
    if not bonus_file.exists():
        print(f"❌ ERROR: Bonus institutions file not found: {bonus_file}")
        sys.exit(1)
    
    print(f"📂 Main dataset: {main_file}")
    print(f"📂 Bonus institutions: {bonus_file}")
    print()
    
    # Load data
    print("Loading datasets...")
    main_data = load_yaml(main_file)
    bonus_data = load_yaml(bonus_file)
    
    print(f"✅ Main dataset loaded: {len(main_data)} institutions")
    print(f"✅ Bonus institutions loaded: {len(bonus_data)} institutions")
    print()
    
    # Count current Brazilian institutions with Wikidata
    br_institutions = [i for i in main_data if any(l.get('country') == 'BR' for l in i.get('locations', []))]
    br_with_wikidata = sum(1 for i in br_institutions if any(x.get('identifier_scheme') == 'Wikidata' for x in i.get('identifiers', [])))
    
    print("📊 BEFORE MERGE:")
    print(f"   Total institutions: {len(main_data)}")
    print(f"   Brazilian institutions: {len(br_institutions)}")
    print(f"   Brazilian with Wikidata: {br_with_wikidata} ({br_with_wikidata/len(br_institutions)*100:.1f}%)")
    print()
    
    # Create backup
    print("Creating backup...")
    create_backup(main_file)
    print()
    
    # Add bonus institutions
    print("Adding bonus institutions...")
    print("-" * 80)
    updated_data, additions = add_bonus_institutions(main_data, bonus_data)
    print("-" * 80)
    print()
    
    # Calculate new statistics
    br_institutions_after = [i for i in updated_data if any(l.get('country') == 'BR' for l in i.get('locations', []))]
    br_with_wikidata_after = sum(1 for i in br_institutions_after if any(x.get('identifier_scheme') == 'Wikidata' for x in i.get('identifiers', [])))
    
    print("📊 AFTER MERGE:")
    print(f"   Total institutions: {len(updated_data)}")
    print(f"   Brazilian institutions: {len(br_institutions_after)}")
    print(f"   Brazilian with Wikidata: {br_with_wikidata_after} ({br_with_wikidata_after/len(br_institutions_after)*100:.1f}%)")
    print()
    
    print("📈 CHANGES:")
    print(f"   Institutions added: {additions}")
    print(f"   Total growth: +{len(updated_data) - len(main_data)} institutions")
    print(f"   Brazilian growth: +{len(br_institutions_after) - len(br_institutions)} institutions")
    print(f"   Coverage improvement: +{br_with_wikidata_after - br_with_wikidata} institutions with Wikidata")
    print(f"   Coverage change: {br_with_wikidata/len(br_institutions)*100:.1f}% → {br_with_wikidata_after/len(br_institutions_after)*100:.1f}%")
    print()
    
    # Save updated dataset
    print(f"💾 Saving updated dataset to {main_file}...")
    save_yaml(updated_data, main_file)
    print("✅ Save complete!")
    print()
    
    print("=" * 80)
    print("🎉 BATCH 15 MERGE COMPLETE!")
    print("=" * 80)
    print()
    print("Summary:")
    print(f"  • {additions} bonus institutions added to dataset")
    print(f"  • All 4 institutions include Wikidata Q-numbers")
    print(f"  • Coverage: {br_with_wikidata_after}/{len(br_institutions_after)} ({br_with_wikidata_after/len(br_institutions_after)*100:.1f}%)")
    print()
    print("Next steps:")
    print("  1. Verify merge with: python3 -c \"import yaml; print(len(yaml.safe_load(open('data/instances/all/globalglam-20251111.yaml'))))\"")
    print("  2. Check Brazilian institutions count")
    print("  3. Generate Batch 15 final report")
    print("  4. Continue with Batch 16 enrichment (target: 70%+ coverage)")
    print()

if __name__ == "__main__":
    main()