import pandas as pd
import json
import os

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

def main():
    # 1. Load the "Done" list
    leads_csv_path = 'leads/leads.csv'
    if os.path.exists(leads_csv_path):
        leads_df = pd.read_csv(leads_csv_path)
        done_names = set(leads_df['Firm/Innung'].apply(normalize))
        done_emails = set(leads_df['Email'].apply(normalize))
    else:
        done_names = set()
        done_emails = set()

    missing_duesseldorf = []
    missing_cologne = []
    missing_unterfranken = []

    # 2. Check Düsseldorf Targets
    duesseldorf_path = 'leads/cologne_duesseldorf_data/duesseldorf_targets.json'
    if os.path.exists(duesseldorf_path):
        with open(duesseldorf_path, 'r', encoding='utf-8') as f:
            targets = json.load(f)
            seen_d = set()
            for t in targets:
                name = t.get('innung', '')
                if normalize(name) not in done_names and normalize(name) not in seen_d:
                    missing_duesseldorf.append(t)
                    seen_d.add(normalize(name))

    # 3. Check Cologne/Düsseldorf Raw CSV
    cologne_raw_path = 'leads/raw/innungen_leads_koeln_duesseldorf.csv'
    if os.path.exists(cologne_raw_path):
        cologne_df = pd.read_csv(cologne_raw_path)
        seen_c = set()
        for _, row in cologne_df.iterrows():
            name = row.get('organisation', '')
            region = row.get('region', '')
            email = row.get('email', '')
            
            if str(region).lower() == 'koeln':
                if normalize(name) in seen_c:
                    continue
                seen_c.add(normalize(name))

                if pd.isna(email) or email.strip() == '':
                     missing_cologne.append({'name': name, 'reason': 'No Email'})
                else:
                    if normalize(email) not in done_emails and normalize(name) not in done_names:
                        missing_cologne.append({'name': name, 'email': email, 'reason': 'Not in final list'})

    # 4. Check Unterfranken Raw CSV
    unterfranken_raw_path = 'leads/raw/leads_unterfranken.csv'
    if os.path.exists(unterfranken_raw_path):
        uf_df = pd.read_csv(unterfranken_raw_path)
        name_col = None
        for col in uf_df.columns:
            if 'innung' in col.lower() or 'firm' in col.lower() or 'name' in col.lower():
                name_col = col
                break
        
        seen_u = set()
        if name_col:
            for _, row in uf_df.iterrows():
                name = str(row[name_col]).strip()
                # Filter garbage
                if len(name) < 5: continue
                if "regierungsbezirk" in name.lower() and "sitz" in name.lower(): continue # Garbage header line
                
                if normalize(name) not in done_names and normalize(name) not in seen_u:
                    missing_unterfranken.append(name)
                    seen_u.add(normalize(name))

    # 5. Generate Markdown
    with open('missing_leads.md', 'w', encoding='utf-8') as f:
        f.write('# Missing Leads Report\n\n')
        
        f.write(f'## Düsseldorf (Missing: {len(missing_duesseldorf)})\n')
        if not missing_duesseldorf:
             f.write("No missing leads identified (or source file empty).\n")
        for item in missing_duesseldorf:
            f.write(f"- {item.get('innung')} (Contact: {item.get('person', 'N/A')})\n")
        
        f.write(f'\n## Cologne (Missing: {len(missing_cologne)})\n')
        if not missing_cologne:
             f.write("No missing leads identified from raw source.\n")
        for item in missing_cologne:
            reason = item.get('reason', '')
            email_part = f" (Email: {item['email']})" if 'email' in item else ""
            f.write(f"- {item.get('name')}{email_part} [{reason}]\n")

        f.write(f'\n## Unterfranken (Missing: {len(missing_unterfranken)})\n')
        if not missing_unterfranken:
             f.write("All raw Unterfranken leads seem to be in the final list.\n")
        for name in missing_unterfranken:
            f.write(f"- {name}\n")

if __name__ == "__main__":
    main()