Use for Web Workers in Bun, worker_threads, parallel processing, and background tasks.
Provides Web Workers and worker_threads for CPU-intensive tasks. Use when processing large datasets or running parallel computations to avoid blocking the main thread.
/plugin marketplace add secondsky/claude-skills/plugin install bun@claude-skillsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Bun supports Web Workers and Node.js worker_threads for parallel execution.
// 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);
}
};
// 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));
// 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]);
};
// 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);
};
// 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.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();
// 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 });
}
};
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;
}
// 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!");
}
};
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 });
};
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();
}
};
| Error | Cause | Fix |
|---|---|---|
Worker not found | Wrong URL | Check worker file path |
Cannot serialize | Non-transferable data | Use transferable objects |
DataCloneError | Functions/DOM in message | Send only serializable data |
Worker terminated | Premature terminate | Check termination logic |
Load references/optimization.md when:
Load references/patterns.md when:
Use when working with Payload CMS projects (payload.config.ts, collections, fields, hooks, access control, Payload API). Use when debugging validation errors, security issues, relationship queries, transactions, or hook behavior.
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.