async-batch-processor

npm install @ferrow/async-batch-processor

Sliding-window async pool. Keeps exactly N items in flight, preserves result order, supports per-item retry with exponential backoff, abort signaling, and progress callbacks.

Quickstart

import { AsyncBatchProcessor } from 'async-batch-processor';

const processor = new AsyncBatchProcessor();

const items = Array(20).fill(0).map((_, i) => i);
const results = await processor.process(
  items,
  async (item) => {
    const res = await fetch(`https://api.example.com/item/${item}`);
    return res.json();
  },
  {
    concurrency: 3,
    retry: 2,
    onProgress: (current, total) => console.log(`${current}/${total}`)
  }
);

// results[0].item === 0, results[0].result === { ... }
// results[0].retries === 0 (or 1/2 if retried)

API

process(items, worker, options?)

Run worker on items with concurrency control.

Options:

• concurrency (default 1) — max in-flight count
• retry (default 0) — max retry attempts per item
• onProgress — callback(current, total)
• signal — abort-like { aborted: boolean }

Returns: ItemResult[] preserving input order

interface ItemResult<T, R> {
  item: T;
  result?: R;
  error?: Error;
  retries: number;  // attempts made
}

mapLimit(items, concurrency, worker)

Shorthand for process() returning results array. Throws on error.

const results = await processor.mapLimit(items, 3, worker);

forEachLimit(items, concurrency, worker)

Shorthand for side-effect processing.

await processor.forEachLimit(items, 3, async (item) => {
  await save(item);
});

Scope & Limits

• Sliding window — not chunk barriers; exactly N in flight at steady state
• No persistence — in-memory; failures not logged
• Order preserved — results array index matches items array
• Retry is exponential backoff — 10ms * 2^attempt
• AbortSignal-like only — not full AbortController
• No timeout per item — use Promise.race or external timeout

License

MIT

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Sponsored by Ferrow

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Part of the ferrow-toolkit collection · Sponsored by Ferrow