idempotency-handling

name	idempotency-handling
description	Idempotent API operations with idempotency keys, Redis caching, DB constraints. Use for payment systems, webhook retries, safe retries, or encountering duplicate processing, race conditions, key expiry errors.
license	MIT

Idempotency Handling

Ensure operations produce identical results regardless of execution count.

Idempotency Key Pattern

const redis = require('redis');
const client = redis.createClient();

async function idempotencyMiddleware(req, res, next) {
  const key = req.headers['idempotency-key'];
  if (!key) return next();

  const cached = await client.get(`idempotency:${key}`);
  if (cached) {
    const { status, body } = JSON.parse(cached);
    return res.status(status).json(body);
  }

  // Store original send
  const originalSend = res.json.bind(res);
  res.json = async (body) => {
    await client.setEx(
      `idempotency:${key}`,
      86400, // 24 hours
      JSON.stringify({ status: res.statusCode, body })
    );
    return originalSend(body);
  };

  next();
}

Database-Backed Idempotency

CREATE TABLE idempotency_keys (
  key VARCHAR(255) PRIMARY KEY,
  request_hash VARCHAR(64) NOT NULL,
  response JSONB,
  status VARCHAR(20) DEFAULT 'processing',
  created_at TIMESTAMP DEFAULT NOW(),
  expires_at TIMESTAMP DEFAULT NOW() + INTERVAL '24 hours'
);

CREATE INDEX idx_idempotency_expires ON idempotency_keys(expires_at);

async function processPayment(idempotencyKey, payload) {
  const requestHash = crypto.createHash('sha256')
    .update(JSON.stringify(payload)).digest('hex');

  // Try to insert with 'processing' status - only one request will succeed
  const insertResult = await db.query(
    `INSERT INTO idempotency_keys (key, request_hash, status)
     VALUES ($1, $2, 'processing')
     ON CONFLICT (key) DO NOTHING
     RETURNING *`,
    [idempotencyKey, requestHash]
  );

  // If we inserted the row (rowCount === 1), we're responsible for processing
  if (insertResult.rowCount === 1) {
    try {
      // Execute the payment
      const result = await executePayment(payload);

      // Update to completed with response
      await db.query(
        'UPDATE idempotency_keys SET status = $1, response = $2 WHERE key = $3',
        ['completed', JSON.stringify(result), idempotencyKey]
      );

      return result;
    } catch (error) {
      // Mark as failed on error
      await db.query(
        'UPDATE idempotency_keys SET status = $1, response = $2 WHERE key = $3',
        ['failed', JSON.({ : error. }), idempotencyKey]
      );
       error;
    }
  }

  
   existing =  db.(
    ,
    [idempotencyKey]
  );

   row = existing.[];
   (!row) {
      ();
  }

  
   (row. !== requestHash) {
      ();
  }

  
   (row. === ) {
     .(row.);
  }   (row. === ) {
      ();
  }   (row. === ) {
     failedResponse = .(row.);
      ();
  }

    ();
}

When to Apply

• Payment processing
• Order creation
• Webhook handling
• Email sending
• Any operation where duplicates cause issues

Best Practices

• Require idempotency keys for mutations
• Validate request body matches stored request
• Set appropriate TTL (24 hours typical)
• Use atomic database operations
• Implement cleanup jobs to prevent table bloat

TTL Cleanup Strategy

To prevent unbounded table growth, implement periodic cleanup of expired keys:

Option 1: Scheduled Database Job (PostgreSQL)

-- Run hourly via pg_cron or external scheduler
DELETE FROM idempotency_keys
WHERE expires_at < NOW()
LIMIT 1000; -- Batch delete to avoid long locks

Option 2: Application Cleanup Job (Node.js)

// Run via cron or job scheduler (e.g., node-cron, Bull)
async function cleanupExpiredKeys() {
  try {
    const result = await db.query(
      'DELETE FROM idempotency_keys WHERE expires_at < NOW()'
    );
    console.log(`Cleaned up ${result.rowCount} expired idempotency keys`);
  } catch (error) {
    console.error('Cleanup job failed:', error);
  }
}

// Schedule to run every hour
cron.schedule('0 * * * *', cleanupExpiredKeys);

Option 3: Application Cleanup Job (Python)

import asyncio
from datetime import datetime

async def cleanup_expired_keys():
    """Remove expired idempotency keys to prevent table bloat."""
    try:
        result = await db.execute(
            "DELETE FROM idempotency_keys WHERE expires_at < $1",
            datetime.now()
        )
        print(f"Cleaned up {result} expired idempotency keys")
    except Exception as e:
        print(f"Cleanup job failed: {e}")

# Run with APScheduler, Celery, or similar
# scheduler.add_job(cleanup_expired_keys, 'interval', hours=1)

Cleanup Best Practices:

• Run cleanup during low-traffic periods to minimize lock contention
• Use batched deletes (LIMIT 1000) for large tables
• Monitor cleanup job execution and failures
• Consider partitioning the table by created_at for easier cleanup
• Set up alerts if table size grows unexpectedly