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parallel()

parallel<T>(functions, concurrency): Promise<T[]>

Executes multiple async functions in parallel with concurrency control.

note

Results preserve input order. Fails fast like Promise.all().

Type Parameters​

T: T​

The return type of the functions.

Parameters​

functions: () => Promise<T>[]​

Array of async functions to execute.

concurrency: number = Infinity​

Maximum number of concurrent executions. Defaults to Infinity.

Returns: Promise<T[]>​

Promise that resolves to array of results in original order.

Throws​

Rejects if any function rejects (remaining operations are aborted).

Default Value​

Infinity

Since​

1.1.0

Performance​

Early abort on first error prevents unnecessary work.

Also known as​

forEach (Effect) · parallel (Radashi) · ❌ (Lodash, es-toolkit, Remeda, Ramda, Modern Dash, Antfu)

Example​

const results = await parallel([
  () => fetchUser(1),
  () => fetchUser(2),
  () => fetchUser(3)
], 2);

How it works?​

Executes async functions in parallel with concurrency control. Limits how many functions run simultaneously — results preserve original order.

Concurrency Visualization​

Fail-Fast Behavior​

On first error, remaining operations are aborted:

Use Cases​

Control API rate limits 📌​

Execute multiple API calls with controlled concurrency to respect rate limits. Essential for working with APIs that have strict rate limiting.

// Controlled API calls to respect rate limits
const userData = await parallel(
  [
    () => fetchUser(1),
    () => fetchUser(2),
    () => fetchUser(3),
    () => fetchUser(4),
    () => fetchUser(5),
  ],
  2
); // Max 2 concurrent requests

console.log("Users loaded:", userData);

Manage resource-intensive operations​

Limit concurrent operations to prevent system overload. Critical for operations that consume significant system resources.

// Controlled image processing
const processedImages = await parallel(
  [
    () => processImage("image1.jpg"),
    () => processImage("image2.jpg"),
    () => processImage("image3.jpg"),
    () => processImage("image4.jpg"),
  ],
  2
); // Process max 2 images at a time

console.log("Images processed:", processedImages);

Optimize database operations​

Execute database queries with controlled concurrency for optimal performance. Essential for maintaining database performance and preventing connection exhaustion.

// Controlled database operations
const results = await parallel(
  [
    () => db.query("SELECT * FROM users WHERE active = 1"),
    () => db.query("SELECT * FROM posts WHERE published = 1"),
    () => db.query("SELECT * FROM comments WHERE approved = 1"),
    () => db.query("SELECT * FROM categories WHERE visible = 1"),
  ],
  3
); // Max 3 concurrent queries

console.log("Database queries completed:", results);

Handle file operations efficiently​

Process multiple files with controlled concurrency to prevent I/O overload. Critical for file processing systems and batch operations.

// Controlled file processing
const processedFiles = await parallel(
  [
    () => processFile("file1.txt"),
    () => processFile("file2.txt"),
    () => processFile("file3.txt"),
    () => processFile("file4.txt"),
    () => processFile("file5.txt"),
  ],
  2
); // Process max 2 files at a time

console.log("Files processed:", processedFiles);

Implement progressive loading​

Load content progressively with controlled concurrency for better user experience. Essential for large applications with multiple content sections.

// Progressive content loading
const content = await parallel(
  [
    () => loadHeaderContent(),
    () => loadSidebarContent(),
    () => loadMainContent(),
    () => loadFooterContent(),
  ],
  2
); // Load max 2 sections at a time

renderPage(content);

Scrape pages with politeness​

Crawl multiple URLs while limiting concurrent requests to avoid overwhelming servers. Essential for web scraping, link checking, or sitemap validation.

const urls = [
  "https://example.com/page1",
  "https://example.com/page2",
  // ... 100 more URLs
];

const results = await parallel(
  urls.map((url) => () => fetch(url).then((r) => r.text())),
  5 // Max 5 concurrent requests - be polite!
);

console.log(`Scraped ${results.length} pages`);

Fetch lab results in parallel for patient dashboards​

Fetch multiple lab test results concurrently with controlled parallelism. Essential for healthcare portals displaying comprehensive patient diagnostics.

const patientTests = [
  { testId: "CBC-001", type: "Complete Blood Count" },
  { testId: "LFT-002", type: "Liver Function" },
  { testId: "RFT-003", type: "Renal Function" },
  { testId: "TFT-004", type: "Thyroid Function" },
  { testId: "LIP-005", type: "Lipid Panel" },
  { testId: "GLU-006", type: "Glucose Tolerance" },
];

// Fetch results with concurrency limit to avoid overwhelming lab API
const labResults = await parallel(
  patientTests.map((test) => async () => {
    const result = await labAPI.getResult(test.testId);
    return {
      ...test,
      result: result.values,
      status: result.abnormal ? "ABNORMAL" : "NORMAL",
      date: result.completedAt,
    };
  }),
  3 // Max 3 concurrent requests to lab system
);

// Flag abnormal results for physician review
const abnormalResults = labResults.filter((r) => r.status === "ABNORMAL");
console.log(`${abnormalResults.length} results require review`);