#!/usr/bin/env python3
"""
Convert website_enrichment blocks to web_enrichment with claim-level provenance.

This script transforms the nested website_enrichment structure into the standardized
web_enrichment format with individual claims, each with its own provenance metadata.

Usage:
    python scripts/convert_website_enrichment_to_claims.py [--dry-run] [--limit N]
"""

import argparse
import sys
from pathlib import Path
from datetime import datetime, timezone
from typing import Any

import yaml


def flatten_dict(d: dict, parent_key: str = '', sep: str = '.') -> dict:
    """Flatten a nested dictionary into dot-notation keys."""
    items = []
    for k, v in d.items():
        new_key = f"{parent_key}{sep}{k}" if parent_key else k
        if isinstance(v, dict):
            items.extend(flatten_dict(v, new_key, sep).items())
        elif isinstance(v, list):
            # For lists, create indexed keys or join simple values
            if v and all(isinstance(x, str) for x in v):
                items.append((new_key, v))  # Keep as list
            elif v and all(isinstance(x, dict) for x in v):
                for i, item in enumerate(v):
                    items.extend(flatten_dict(item, f"{new_key}[{i}]", sep).items())
            else:
                items.append((new_key, v))
        else:
            items.append((new_key, v))
    return dict(items)


def extract_claims_from_website_enrichment(website_enrichment: dict, source_url: str, fetch_timestamp: str) -> list[dict]:
    """
    Extract individual claims from website_enrichment structure.
    
    Maps nested fields to claim types with appropriate confidence scores.
    """
    claims = []
    
    # Define claim type mappings with confidence scores
    # Higher confidence for factual data, lower for scraped descriptions
    claim_mappings = {
        # Organization details
        'organization_details.full_name': ('organization_full_name', 0.95),
        'organization_details.short_name': ('organization_short_name', 0.95),
        'organization_details.legal_form': ('legal_form', 0.90),
        'organization_details.founded': ('founded', 0.90),
        'organization_details.description': ('description', 0.85),
        'organization_details.mission': ('mission', 0.85),
        'organization_details.member_count': ('member_count', 0.85),
        'organization_details.membership_fee': ('membership_fee', 0.90),
        'organization_details.tagline': ('tagline', 0.85),
        'organization_details.parent_organization': ('parent_organization', 0.90),
        
        # Legal status
        'legal_status.anbi_status': ('anbi_status', 0.95),
        'legal_status.rsin': ('rsin', 0.95),
        'legal_status.kvk_number': ('kvk_number', 0.95),
        
        # Museum info
        'museum.name': ('museum_name', 0.95),
        'museum.description': ('museum_description', 0.85),
        'museum.website': ('museum_website', 0.95),
        'museum.established': ('museum_established', 0.90),
        
        # Location
        'location.street_address': ('street_address', 0.95),
        'location.postal_code': ('postal_code', 0.95),
        'location.city': ('city', 0.95),
        'location.municipality': ('municipality', 0.90),
        'location.province': ('province', 0.95),
        'location.country': ('country', 0.99),
        'location.venue_name': ('venue_name', 0.90),
        
        # Contact
        'contact.email': ('email', 0.95),
        'contact.phone': ('phone', 0.95),
        'contact.website': ('website', 0.99),
        'contact.facebook': ('facebook', 0.95),
        
        # Publications
        'publications.journal.name': ('journal_name', 0.95),
        'publications.journal.url': ('journal_url', 0.95),
        
        # Digital resources
        'digital_resources.beeldbank.url': ('beeldbank_url', 0.95),
        'digital_resources.beeldbank.description': ('beeldbank_description', 0.85),
        
        # Collections
        'collections.permanent_collection.description': ('collection_description', 0.85),
        
        # Opening hours
        'opening_hours': ('opening_hours', 0.90),
    }
    
    # Flatten the website_enrichment dict
    flat = flatten_dict(website_enrichment)
    
    for flat_key, value in flat.items():
        if value is None or value == '' or flat_key in ('fetch_timestamp', 'fetch_status', 'source_url'):
            continue
            
        # Check for direct mapping
        claim_type = None
        confidence = 0.80  # Default confidence
        
        for pattern, (ctype, conf) in claim_mappings.items():
            if flat_key == pattern or flat_key.startswith(pattern):
                claim_type = ctype
                confidence = conf
                break
        
        # If no mapping found, create a generic claim type from the key
        if claim_type is None:
            # Convert nested key to claim type
            claim_type = flat_key.replace('.', '_').replace('[', '_').replace(']', '')
            confidence = 0.80
        
        # Format the value
        if isinstance(value, list):
            if all(isinstance(x, str) for x in value):
                claim_value = '; '.join(value)
            else:
                claim_value = str(value)
        elif isinstance(value, bool):
            claim_value = str(value).lower()
        elif isinstance(value, dict):
            # Skip complex nested dicts that weren't flattened
            continue
        else:
            claim_value = str(value)
        
        claims.append({
            'claim_type': claim_type,
            'claim_value': claim_value,
            'source_url': source_url,
            'extraction_timestamp': fetch_timestamp,
            'confidence': confidence
        })
    
    return claims


def convert_file(filepath: Path, dry_run: bool = False) -> tuple[bool, str]:
    """
    Convert a single file's website_enrichment to web_enrichment format.
    
    Returns:
        Tuple of (success, message)
    """
    with open(filepath, 'r', encoding='utf-8') as f:
        data = yaml.safe_load(f)
    
    if not data:
        return False, "Empty file"
    
    # Check if website_enrichment exists
    if 'website_enrichment' not in data:
        return False, "No website_enrichment block"
    
    # Check if web_enrichment already exists (avoid duplicate conversion)
    if 'web_enrichment' in data:
        return False, "web_enrichment already exists (skipping)"
    
    website_enrichment = data['website_enrichment']
    
    # Extract metadata - handle multiple source URL formats
    source_url = website_enrichment.get('source_url', '')
    source_urls = website_enrichment.get('source_urls', [])
    
    # Handle 'sources' list format (e.g., [{url: ..., method: ...}])
    sources_list = website_enrichment.get('sources', [])
    if not source_url and not source_urls and sources_list:
        if isinstance(sources_list, list) and sources_list:
            first_source = sources_list[0]
            if isinstance(first_source, dict) and 'url' in first_source:
                source_url = first_source['url']
                source_urls = [s.get('url') for s in sources_list if isinstance(s, dict) and s.get('url')]
    
    # Use first source_url if source_urls is provided
    if not source_url and source_urls:
        source_url = source_urls[0] if isinstance(source_urls, list) else source_urls
    
    # Fallback: try to get URL from original_entry.webadres_organisatie
    if not source_url and 'original_entry' in data:
        source_url = data['original_entry'].get('webadres_organisatie', '')
    
    fetch_timestamp = website_enrichment.get('fetch_timestamp', datetime.now(timezone.utc).isoformat())
    fetch_status = website_enrichment.get('fetch_status', 'SUCCESS')
    
    if not source_url:
        return False, "No source_url found (checked website_enrichment and original_entry)"
    
    # Extract claims
    claims = extract_claims_from_website_enrichment(website_enrichment, source_url, fetch_timestamp)
    
    if not claims:
        return False, "No claims extracted"
    
    # Build raw_sources list (include all source URLs if multiple)
    raw_sources = []
    all_urls = source_urls if source_urls else [source_url]
    for url in all_urls:
        raw_sources.append({
            'url': url,
            'fetch_timestamp': fetch_timestamp,
            'source_type': 'official_website',
            'fetch_status': fetch_status
        })
    
    # Build new web_enrichment structure
    web_enrichment = {
        'enrichment_timestamp': fetch_timestamp,
        'enrichment_method': 'website_scrape_with_claim_provenance',
        'source_url': source_url,
        'claims': claims,
        'raw_sources': raw_sources,
        'web_enrichment_status': fetch_status
    }
    
    # Add the new web_enrichment block
    data['web_enrichment'] = web_enrichment
    
    if dry_run:
        return True, f"Would add web_enrichment with {len(claims)} claims"
    
    # Write back
    with open(filepath, 'w', encoding='utf-8') as f:
        yaml.dump(data, f, default_flow_style=False, allow_unicode=True, sort_keys=False)
    
    return True, f"Added web_enrichment with {len(claims)} claims"


def main():
    parser = argparse.ArgumentParser(description='Convert website_enrichment to web_enrichment with claims')
    parser.add_argument('--dry-run', action='store_true', help='Show what would be done without making changes')
    parser.add_argument('--limit', type=int, default=None, help='Limit number of files to process')
    parser.add_argument('--file', type=str, default=None, help='Process a single file')
    args = parser.parse_args()
    
    entries_dir = Path('/Users/kempersc/apps/glam/data/nde/enriched/entries')
    
    if args.file:
        files = [Path(args.file)]
    else:
        # Find all files with website_enrichment
        files = sorted(entries_dir.glob('*.yaml'))
    
    if args.limit:
        files = files[:args.limit]
    
    converted = 0
    skipped = 0
    errors = 0
    
    for filepath in files:
        try:
            # Quick check if file has website_enrichment
            with open(filepath, 'r', encoding='utf-8') as f:
                content = f.read()
            
            if 'website_enrichment:' not in content:
                continue
            
            if 'web_enrichment:' in content:
                print(f"SKIP: {filepath.name} - web_enrichment already exists")
                skipped += 1
                continue
            
            success, message = convert_file(filepath, dry_run=args.dry_run)
            
            if success:
                print(f"{'WOULD ' if args.dry_run else ''}OK: {filepath.name} - {message}")
                converted += 1
            else:
                print(f"SKIP: {filepath.name} - {message}")
                skipped += 1
                
        except Exception as e:
            print(f"ERROR: {filepath.name} - {e}")
            errors += 1
    
    print(f"\n{'DRY RUN ' if args.dry_run else ''}Summary:")
    print(f"  Converted: {converted}")
    print(f"  Skipped: {skipped}")
    print(f"  Errors: {errors}")
    
    return 0 if errors == 0 else 1


if __name__ == '__main__':
    sys.exit(main())