import pandas as pd
import os

def normalize(text):
    if not isinstance(text, str):
        return ""
    return text.strip().lower()

def recover_cologne():
    leads_csv_path = 'leads/leads.csv'
    cologne_raw_path = 'leads/raw/innungen_leads_koeln_duesseldorf.csv'
    
    if not os.path.exists(leads_csv_path) or not os.path.exists(cologne_raw_path):
        print("Files not found.")
        return

    # Load existing leads
    leads_df = pd.read_csv(leads_csv_path)
    done_emails = set(leads_df['Email'].apply(normalize))
    done_names = set(leads_df['Firm/Innung'].apply(normalize))

    # Load raw Cologne data
    cologne_df = pd.read_csv(cologne_raw_path)
    
    new_rows = []
    
    print(f"Scanning {len(cologne_df)} raw entries...")

    for _, row in cologne_df.iterrows():
        name = row.get('organisation', '')
        region = row.get('region', '')
        email = row.get('email', '')
        
        # We only care about Cologne for this recovery
        if str(region).lower() != 'koeln':
            continue
            
        # Must have a valid email
        if pd.isna(email) or email.strip() == '':
            continue
            
        # Check if already in leads.csv
        if normalize(email) in done_emails or normalize(name) in done_names:
            continue
            
        # It's a valid new lead!
        new_row = {
            'Firm/Innung': name,
            'Contact Person': 'N/A', # Raw data might not have person, or we need to check columns
            'Email': email,
            'Region': 'Köln'
        }
        new_rows.append(new_row)
        done_emails.add(normalize(email)) # Prevent dupes within batch

    print(f"Found {len(new_rows)} new Cologne leads to add.")
    
    if new_rows:
        new_df = pd.DataFrame(new_rows)
        # Append to CSV
        new_df.to_csv(leads_csv_path, mode='a', header=False, index=False)
        print("Successfully appended to leads.csv")
    else:
        print("No new leads found.")

if __name__ == "__main__":
    recover_cologne()