lead-scraper/lib/utils/csv.ts

import Papa from "papaparse";
import * as XLSX from "xlsx";

export function parseCSV(content: string): { data: Record<string, string>[]; headers: string[] } {
  const result = Papa.parse<Record<string, string>>(content, {
    header: true,
    skipEmptyLines: true,
    transformHeader: (h) => h.trim(),
  });
  return {
    data: result.data,
    headers: result.meta.fields || [],
  };
}

export function detectDomainColumn(headers: string[]): string | null {
  const candidates = ["domain", "website", "url", "web", "site", "homepage", "company_domain", "company_url"];
  for (const candidate of candidates) {
    const found = headers.find(h => h.toLowerCase().includes(candidate));
    if (found) return found;
  }
  return null;
}

export interface ExportRow {
  company_name?: string;
  domain?: string;
  contact_name?: string;
  contact_title?: string;
  email?: string;
  confidence_score?: number | string;
  source_tab?: string;
  job_id?: string;
  found_at?: string;
}

export function exportToCSV(rows: ExportRow[], filename: string): void {
  const csv = Papa.unparse(rows);
  const blob = new Blob([csv], { type: "text/csv;charset=utf-8;" });
  const url = URL.createObjectURL(blob);
  const link = document.createElement("a");
  link.href = url;
  link.download = filename;
  link.click();
  URL.revokeObjectURL(url);
}

export function exportToExcel(rows: ExportRow[], filename: string): void {
  const ws = XLSX.utils.json_to_sheet(rows);
  const wb = XLSX.utils.book_new();
  XLSX.utils.book_append_sheet(wb, ws, "Leads");
  XLSX.writeFile(wb, filename);
}