Data Export

CSV Export (Node.js)

import { stringify } from 'csv-stringify'; import { pipeline } from 'stream/promises';

// Streaming CSV (handles large datasets) app.get('/api/export/users.csv', async (req, res) => { res.setHeader('Content-Type', 'text/csv'); res.setHeader('Content-Disposition', 'attachment; filename="users.csv"');

const cursor = db.collection('users').find().cursor(); const csvStringifier = stringify({ header: true, columns: ['name', 'email', 'createdAt'], });

await pipeline(cursor, csvStringifier, res); });

// Simple in-memory CSV import { stringify } from 'csv-stringify/sync';

const csv = stringify(rows, { header: true, columns: ['name', 'email', 'amount'] });

Excel Export (ExcelJS — recommended)

import ExcelJS from 'exceljs';

app.get('/api/export/report.xlsx', async (req, res) => { const workbook = new ExcelJS.Workbook(); const sheet = workbook.addWorksheet('Report');

// Headers with styling sheet.columns = [ { header: 'Name', key: 'name', width: 25 }, { header: 'Email', key: 'email', width: 30 }, { header: 'Amount', key: 'amount', width: 15 }, ]; sheet.getRow(1).font = { bold: true };

// Data const users = await getUsers(); users.forEach((u) => sheet.addRow(u));

// Number formatting sheet.getColumn('amount').numFmt = '$#,##0.00';

res.setHeader('Content-Type', 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet'); res.setHeader('Content-Disposition', 'attachment; filename="report.xlsx"'); await workbook.xlsx.write(res); });

Streaming Excel for Large Datasets

const workbook = new ExcelJS.stream.xlsx.WorkbookWriter({ stream: res }); const sheet = workbook.addWorksheet('Data'); sheet.columns = [{ header: 'Name', key: 'name' }, { header: 'Value', key: 'value' }];

for await (const row of cursor) { sheet.addRow(row).commit(); // Flushes row to stream }

await workbook.commit();

Frontend CSV Parsing (Papa Parse)

import Papa from 'papaparse';

// Parse uploaded CSV const result = Papa.parse<UserRow>(file, { header: true, skipEmptyLines: true, dynamicTyping: true, complete: (results) => { console.log(results.data); // Parsed rows console.log(results.errors); // Parse errors }, });

// Generate CSV in browser const csv = Papa.unparse(data); const blob = new Blob([csv], { type: 'text/csv' }); const url = URL.createObjectURL(blob);

Python (openpyxl)

from openpyxl import Workbook from io import BytesIO

def export_excel(data: list[dict]) -> bytes: wb = Workbook() ws = wb.active ws.title = "Report"

headers = list(data[0].keys())
ws.append(headers)
for row in data:
    ws.append([row[h] for h in headers])

buffer = BytesIO()
wb.save(buffer)
return buffer.getvalue()

Anti-Patterns

Anti-Pattern Fix

Loading all data into memory Stream from DB cursor for large exports

No Content-Disposition header Always set for browser download

Generating exports in request handler Use background job for >10K rows

No progress indication Use WebSocket/SSE for large export progress

Unescaped CSV values Use library (csv-stringify, Papa Parse)

Production Checklist

• Streaming for datasets >10K rows

• Background job queue for large exports

• Proper Content-Type and Content-Disposition headers

• Memory limits monitored

• Rate limiting on export endpoints

• Temporary file cleanup if writing to disk