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Bun workers

Skill secondsky/claude-skills/plugins/bun/skills/bun-workers

Use for Web Workers in Bun, worker_threads, parallel processing, and background tasks.From its SKILL.md

Install
npx -y skills add secondsky/claude-skills --skill bun-workers

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What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

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Bun Workers

Bun supports Web Workers and Node.js worker_threads for parallel execution.

Web Workers

Basic Usage

// main.ts
const worker = new Worker(new URL("./worker.ts", import.meta.url));

worker.postMessage({ type: "start", data: [1, 2, 3, 4, 5] });

worker.onmessage = (event) => {
  console.log("Result:", event.data);
};

worker.onerror = (error) => {
  console.error("Worker error:", error.message);
};

// worker.ts
self.onmessage = (event) => {
  const { type, data } = event.data;

  if (type === "start") {
    const result = data.map((x) => x * 2);
    self.postMessage(result);
  }
};

Worker with URL

// Import from file path
const worker = new Worker(new URL("./worker.ts", import.meta.url));

// Or with blob URL
const code = `
  self.onmessage = (e) => {
    self.postMessage(e.data * 2);
  };
`;
const blob = new Blob([code], { type: "application/javascript" });
const worker = new Worker(URL.createObjectURL(blob));

Transferable Objects

// main.ts
const buffer = new ArrayBuffer(1024 * 1024); // 1MB
const view = new Uint8Array(buffer);
view.fill(42);

// Transfer ownership (zero-copy)
worker.postMessage({ buffer }, [buffer]);
// buffer is now detached (empty)

// worker.ts
self.onmessage = (event) => {
  const { buffer } = event.data;
  const view = new Uint8Array(buffer);
  // Process buffer...

  // Transfer back
  self.postMessage({ buffer }, [buffer]);
};

Shared Memory

// main.ts
const shared = new SharedArrayBuffer(1024);
const view = new Int32Array(shared);

worker.postMessage({ shared });

// Both main and worker can access
Atomics.add(view, 0, 1);

// worker.ts
self.onmessage = (event) => {
  const { shared } = event.data;
  const view = new Int32Array(shared);

  // Atomic operations for thread safety
  Atomics.add(view, 0, 1);
  Atomics.notify(view, 0);
};

Node.js worker_threads

// main.ts
import { Worker, isMainThread, parentPort, workerData } from "worker_threads";

if (isMainThread) {
  const worker = new Worker(import.meta.filename, {
    workerData: { numbers: [1, 2, 3, 4, 5] },
  });

  worker.on("message", (result) => {
    console.log("Result:", result);
  });

  worker.on("error", (err) => {
    console.error("Error:", err);
  });

  worker.on("exit", (code) => {
    console.log("Worker exited with code:", code);
  });
} else {
  // Worker code
  const { numbers } = workerData;
  const sum = numbers.reduce((a, b) => a + b, 0);
  parentPort?.postMessage(sum);
}

Worker Pool

// worker-pool.ts
import { Worker } from "worker_threads";

class WorkerPool {
  private workers: Worker[] = [];
  private queue: Array<{
    task: any;
    resolve: (value: any) => void;
    reject: (err: Error) => void;
  }> = [];
  private activeWorkers = new Set<Worker>();

  constructor(
    private workerPath: string,
    private poolSize: number
  ) {
    for (let i = 0; i < poolSize; i++) {
      this.addWorker();
    }
  }

  private addWorker() {
    const worker = new Worker(this.workerPath);

    worker.on("message", (result) => {
      this.activeWorkers.delete(worker);
      this.processQueue();
    });

    worker.on("error", (err) => {
      this.activeWorkers.delete(worker);
      console.error("Worker error:", err);
    });

    this.workers.push(worker);
  }

  async execute(task: any): Promise<any> {
    return new Promise((resolve, reject) => {
      this.queue.push({ task, resolve, reject });
      this.processQueue();
    });
  }

  private processQueue() {
    for (const worker of this.workers) {
      if (!this.activeWorkers.has(worker) && this.queue.length > 0) {
        const { task, resolve, reject } = this.queue.shift()!;
        this.activeWorkers.add(worker);

        worker.once("message", resolve);
        worker.once("error", reject);
        worker.postMessage(task);
      }
    }
  }

  terminate() {
    this.workers.forEach((w) => w.terminate());
  }
}

// Usage
const pool = new WorkerPool("./worker.ts", 4);
const results = await Promise.all([
  pool.execute({ task: 1 }),
  pool.execute({ task: 2 }),
  pool.execute({ task: 3 }),
]);
pool.terminate();

Patterns

CPU-Intensive Tasks

// main.ts
const worker = new Worker(new URL("./cpu-worker.ts", import.meta.url));

// Process large dataset
const data = Array.from({ length: 1000000 }, () => Math.random());

worker.postMessage({ type: "process", data });

worker.onmessage = (event) => {
  if (event.data.type === "progress") {
    console.log(`Progress: ${event.data.percent}%`);
  } else if (event.data.type === "result") {
    console.log("Done:", event.data.result);
  }
};

// cpu-worker.ts
self.onmessage = (event) => {
  const { type, data } = event.data;

  if (type === "process") {
    const chunkSize = 10000;
    let result = 0;

    for (let i = 0; i < data.length; i++) {
      result += Math.sqrt(data[i]);

      // Report progress
      if (i % chunkSize === 0) {
        self.postMessage({
          type: "progress",
          percent: Math.round((i / data.length) * 100),
        });
      }
    }

    self.postMessage({ type: "result", result });
  }
};

Parallel Map

async function parallelMap<T, R>(
  items: T[],
  fn: string, // Function name in worker
  workerUrl: URL,
  concurrency = 4
): Promise<R[]> {
  const results: R[] = new Array(items.length);
  const workers: Worker[] = [];

  // Create workers
  for (let i = 0; i < concurrency; i++) {
    workers.push(new Worker(workerUrl));
  }

  // Process items
  let nextIndex = 0;
  const processNext = (worker: Worker): Promise<void> => {
    return new Promise((resolve) => {
      if (nextIndex >= items.length) {
        resolve();
        return;
      }

      const index = nextIndex++;
      worker.postMessage({ fn, item: items[index], index });

      worker.onmessage = (event) => {
        results[event.data.index] = event.data.result;
        processNext(worker).then(resolve);
      };
    });
  };

  await Promise.all(workers.map(processNext));

  workers.forEach((w) => w.terminate());
  return results;
}

Message Channel

// Create channel for worker-to-worker communication
const channel = new MessageChannel();

const worker1 = new Worker(new URL("./worker1.ts", import.meta.url));
const worker2 = new Worker(new URL("./worker2.ts", import.meta.url));

// Give each worker a port
worker1.postMessage({ port: channel.port1 }, [channel.port1]);
worker2.postMessage({ port: channel.port2 }, [channel.port2]);

// worker1.ts
let port: MessagePort;
self.onmessage = (event) => {
  if (event.data.port) {
    port = event.data.port;
    port.onmessage = (e) => console.log("From worker2:", e.data);
    port.postMessage("Hello from worker1!");
  }
};

Error Handling

const worker = new Worker(new URL("./worker.ts", import.meta.url));

worker.onerror = (error) => {
  console.error("Uncaught error in worker:", error.message);
  error.preventDefault(); // Prevent bubbling
};

worker.onmessageerror = (event) => {
  console.error("Message deserialization failed");
};

// In worker
self.onerror = (error) => {
  self.postMessage({ type: "error", message: error.message });
};

Termination

const worker = new Worker(new URL("./worker.ts", import.meta.url));

// Request graceful shutdown
worker.postMessage({ type: "shutdown" });

// Force terminate after timeout
setTimeout(() => {
  worker.terminate();
}, 5000);

// In worker
self.onmessage = (event) => {
  if (event.data.type === "shutdown") {
    // Cleanup
    self.close();
  }
};

Common Errors

ErrorCauseFix
Worker not foundWrong URLCheck worker file path
Cannot serializeNon-transferable dataUse transferable objects
DataCloneErrorFunctions/DOM in messageSend only serializable data
Worker terminatedPremature terminateCheck termination logic

When to Load References

Load references/optimization.md when:

  • Worker pool tuning
  • Memory management
  • Performance profiling

Load references/patterns.md when:

  • Complex coordination
  • Backpressure handling
  • Error recovery

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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