Faker.js: Complete Guide to Generating Realistic Test Data with Best Practices

What Is Faker.js?

Faker.js is a popular JavaScript library used to generate fake yet realistic data, including names, emails, phone numbers, addresses, and business details. Supporting more than 70 locales, it has become a standard tool for creating mock datasets in development, testing, and prototyping.

In January 2022, the original Faker.js package was suddenly unpublished, sparking widespread disruption across projects. The open-source community quickly stepped in, reviving the project as @faker-js/faker, which is now actively maintained by a dedicated group of contributors.

With features like data seeding for determinism, Faker.js ensures your automated tests can simulate real-world scenarios in a scalable, reproducible, and safe way.

Key Features of Faker.js

Faker.js comes packed with a wide range of capabilities designed to simplify test data generation. From multilingual support to customizable data seeding, it provides developers with versatile tools to simulate real-world scenarios efficiently.

• Extensive Data Types: Generate fake names, addresses, emails, phone numbers, dates, images, and more.
• Locale Support: Over 70 locales to create region-specific data.
• Data Seeding: Use seeds to generate deterministic and reproducible datasets.
• Thematic Categories: Built-in modules for internet, commerce, company, finance, lorem text, and more.
• Lightweight & Modular: Import only the data modules you need.
• Randomization Utilities: Functions to shuffle, pick, and generate random values beyond predefined data.
• Actively Maintained: Available under the new package @faker-js/faker with ongoing community support.

Installing and Using Faker.js in 5 Minutes

Getting started with Faker.js is simple and fast. In just a few steps, you can install the library, set it up in your project, and begin generating realistic test data within minutes.

Prerequisites:

Before you begin, make sure you have:

• Node.js and npm are installed on your system. (You can verify using node -v and npm -v).
• A basic JavaScript project or a test environment is ready.

Running Faker.js in Your Project

Once Faker.js is installed and set up, the next step is to put it into action. You can use Faker.js to generate test data that simulates real-world scenarios, making your automated tests more reliable and effective.

Test Scenario:

• Launch the Chrome browser.
• Open the LambdaTest Sign Up page.
• Enter a randomly generated email address using Faker.js.
• Enter a randomly generated username using Faker.js.
• Click on the Sign Up button.
• Close the web browser.

Code Implementation:

const { Builder, By } = require("selenium-webdriver");
                                     const faker = require("@faker-js/faker").faker;
(async function runFakerTest() {

let driver = await new Builder().forBrowser("chrome").build();
 try {

// Navigate to LambdaTest signup page
await driver.get("https://accounts.lambdatest.com/register");

// Generate fake data
let fakeEmail = faker.internet.email();
let fakeUsername = faker.internet.userName();

// Fill in the signup form
await driver.findElement(By.id("email")).sendKeys(fakeEmail);
await driver.findElement(By.id("name")).sendKeys(fakeUsername);

// Click on Sign Up button
 await driver.findElement(By.xpath("//a[text()='Sign In']")).click();
console.log("Test executed with email:", fakeEmail, "and username:", fakeUsername);
} 

catch (err) {
console.error("Error during test execution:", err);
} 

finally {
await driver.quit();
}
 })();

Test Execution:

Code Walkthrough:

Here is the code walkthrough of the executed test on a local grid using Selenium WebDriver with Node.js and Faker.js.

• Import Modules: Imports Selenium WebDriver, enabling your script to control and interact with the browser.

const { Builder, By } = require("selenium-webdriver"); 



• Bring in Faker.js: Load Faker.js, which you’ll use to generate random test data like emails and usernames.

const faker = require("@faker-js/faker").faker; 



• Launch the Browser: Start a new Chrome browser instance using WebDriver.

let driver = await new Builder().forBrowser("chrome").build(); 



• Navigate to the Target Page: Open the LambdaTest Sign Up page.

await driver.get("https://accounts.lambdatest.com/register"); 



• Generate Test Data: Use Faker.js to create a random email address and username.

const fakeEmail = faker.internet.email();
const fakeUsername = faker.internet.userName();



• Fill in the Email Field: Locate the username field and enter the generated username.

driver.findElement(By.id("name")).sendKeys(fakeUsername); 



• Submit the Form: Click on the Sign Up button to submit the form.

driver.findElement(By.xpath("//a[text()='Sign In']")).click(); 



• Log Test Data: Use console.log() to log your data.

console.log("Test executed with email:", fakeEmail, "and username:", fakeUsername);



• Handle Errors: Catch runtime exceptions to prevent test crashes.

catch (err) { … }



• Close the Browser: End the browser session after test execution.

finally { await driver.quit(); }

A common challenge with Faker.js is keeping test data stable and predictable. Random values can make tests pass in one environment but fail in another, which makes debugging and maintenance frustrating.

In CI/CD pipelines, this problem grows as tests may behave differently across browsers, operating systems, or parallel runs. Teams need a setup where Faker.js data stays consistent across all runs and platforms.

Cloud-based platforms like LambdaTest offer controlled, scalable environments that ensure Faker.js-powered tests execute reliably across a wide range of browsers and OS combinations, minimizing flakiness, improving reproducibility, and providing faster, more dependable feedback to developers and QA teams.

Running and Testing Faker.js at Scale

LambdaTest provides scalable, cloud-based browsers where you can run your Faker.js-powered Selenium, Playwright, or Cypress tests.

Features like parallel execution, data seeding, and environment replication ensure your tests are predictable, reproducible, and easier to maintain.

By leveraging LambdaTest for cross-browser testing, you can execute tests across 3,000+ browser and OS combinations, reducing flakiness and delivering faster, dependable feedback.

To get started with LambdaTest, you need to follow a few steps given below:

• Set Up Your LambdaTest Account: Sign up or log in to LambdaTest and get your Username and Access Key from the profile section, which are required to connect your test scripts to the LambdaTest cloud.
• Add Testing Framework Dependencies: Depending on your preferred framework, install the necessary dependencies: Selenium, Playwright, or Cypress.

Note: For this demonstration, we will use Selenium. Install the required Selenium WebDriver package:



• Configure LambdaTest Remote URL: Replace your local WebDriver setup with LambdaTest’s remote WebDriver URL to execute tests in the cloud. You’ll need your LambdaTest username and access key:

  // For Selenium WebDriver
   const driver = await new Builder()
  .usingServer("https://undefined:undefined@hub.lambdatest.com/wd/hub")
  .forBrowser("chrome")
  .build();
  

• Generate Test Data Using Faker.js : Import Faker.js in your test file and create dynamic test data:

  const { faker } = require("@faker-js/faker");
  const fakeUser = {
  name: faker.person.fullName(),
  email: faker.internet.email(),
  username: faker.internet.userName()
  };
  

• Parallel Execution: LambdaTest supports parallel execution, which allows multiple browsers and OS combinations to run simultaneously.

  Configure your test capabilities to specify browsers, versions, and OS combinations:

  const capability = {
  "browserName": "Chrome",
  "browserVersion": "dev",
  "LT:Options": {
  "username": "process.env.LT_USERNAME",
  "accessKey": "process.env.LT_ACCESS_KEY",
  "visual": true,
  "video": true,
  "platformName": "Windows 10",
  "build": "FakerJS Test Build",
  "project": "Faker JS",
  "name": "Faker JS",
  "w3c": true,
  "plugin": "node_js-node_js"
  }
  }
  

  You can generate the above Node.js capabilities from the LambdaTest Automation Capabilities Generator.

• Seed Data for Reproducibility: Ensure your Faker.js data is consistent across runs by using seeding:

  faker.seed(12345);

  As it guarantees that tests will behave deterministically even across multiple browsers and parallel executions.

Test Execution:

Access your LambdaTest dashboard to check live execution, review logs, screenshots, and videos, and quickly identify flaky tests or failures.

To get started with LambdaTest, follow this support documentation on Selenium automation testing using LambdaTest.

Common Use Cases of Faker.js

Faker.js shines when you need realistic but fake data that behaves like production inputs without risking sensitive information. Below are some of the most common scenarios where developers rely on it.

Testing and QA

In automated testing, you often need user profiles, transactions, or order data to validate workflows. Faker.js helps you create these datasets on the fly, ensuring that test runs don’t rely on hardcoded or repetitive data.

const faker = require('@faker-js/faker');
const user = {
  name: faker.person.fullName(),
  email: faker.internet.email(),
  phone: faker.phone.number()
};

This snippet generates a random user profile for testing sign-up flows or data validation.

Frontend Development

When building UI components, placeholder text and static data don’t always showcase how designs hold up with real-world variation. Faker.js can populate cards, tables, or lists with dynamic sample data.

const faker = require('@faker-js/faker');
const product = {
  title: faker.commerce.productName(),
  price: faker.commerce.price(),
  image: faker.image.url()
};

Useful for quickly filling a product grid or catalog preview in frontend applications.

API Development

If your backend isn’t ready yet, Faker.js can generate realistic mock responses for REST or GraphQL APIs. This allows frontend teams to continue building against simulated endpoints.

const faker = require('@faker-js/faker');
app.get('/api/user', (req, res) => {
  res.json({ id: faker.string.uuid(), name: faker.person.fullName() });
});

Great for mocking endpoints during integration testing or when backend services are under development.

Database Seeding

To test performance and scalability, databases need to be populated with large amounts of dummy data. Faker.js makes it easy to seed thousands of records quickly.

const faker = require('@faker-js/faker');
let users = Array.from({ length: 1000 }, () => ({
  id: faker.string.uuid(),
  name: faker.person.fullName(),
  email: faker.internet.email()
}));

Generates a dataset of 1000 users to simulate load testing or stress test queries.

How to Work with Locales in Faker.js (Multilingual Support)?

Faker.js makes it easy to generate realistic test data across multiple languages and regions with its built-in locale support. You can also seed data for consistency, ensuring reliable and repeatable test runs in global-scale applications.

Working with Locales

One of the standout features of Faker.js is its support for 70+ locales, allowing you to generate data in different languages and cultural formats. This is especially useful when you’re testing applications that will be used by a global audience.

For instance, a German user expects addresses, names, and phone numbers to look different from those in the US or Japan. By setting the locale, you can instantly adapt your test data to match regional conventions, making your testing more realistic and inclusive.

Example:

import { faker } from "@faker-js/faker";
// Switch Faker.js to German locale
faker.setLocale('de');
console.log(faker.person.fullName());  
// Example Output: "Hans Müller"

With just one line, your fake data aligns with the region you’re targeting. This makes it easier to test UI rendering, form validations, and business logic across different cultures without manually curating sample data.

Seeding Data for Consistency

When running automated tests, consistency matters. If your test data changes on every run, debugging failures becomes a nightmare. Faker.js solves this problem with data seeding. By providing a fixed seed value, you ensure that the same fake data is generated every time the code runs.

This deterministic behavior is crucial in CI/CD pipelines, where reproducible results help identify real bugs rather than random data mismatches. It also makes collaboration easier since developers across teams will see the same test outputs when using the same seed.

Example:

import { faker } from "@faker-js/faker";
// Seed Faker.js with a fixed value
faker.seed(123);
console.log(faker.person.fullName());  
// Always outputs: "Corbin Nikolaus"

With seeding, your fake data becomes predictable and reliable. This guarantees that test runs are stable, repeatable, and easier to debug, which is exactly what teams need when scaling automation.

How to Use Faker.js with Popular Testing Frameworks?

Faker.js isn’t limited to generating mock data in isolation; it shines when paired with popular testing frameworks.

By plugging Faker.js into unit tests with Jest, end-to-end browser tests using Cypress, cross-browser automation through Selenium, and modern Playwright headless browser testing, you can make your test coverage stronger, more reliable, and closer to real-world scenarios without relying on static data.

Using Faker.js with Selenium (Cross-Browser Testing)

Selenium is a leading tool for cross-browser automation, widely used to validate applications across Chrome, Firefox, Edge, and Safari. By integrating Faker.js, you can dynamically generate test data such as user accounts, addresses, or form inputs during Selenium testing

Seeding ensures reproducibility while still allowing randomized input for broader coverage. To deep dive and get started with Selenium, follow this detailed guide on the Selenium tutorial.

Example: Filling out a signup form in Selenium with Faker.js (JavaScript)

const { Builder, By } = require("selenium-webdriver");
const { faker } = require("@faker-js/faker");
(async function signupForm() {
  let driver = await new Builder().forBrowser("chrome").build();
  try {
    const fakeUser = {
      username: faker.internet.userName(),
      email: faker.internet.email(),
      password: faker.internet.password(),
    };


    await driver.get("https://example.com/signup");
    await driver.findElement(By.name("username")).sendKeys(fakeUser.username);
    await driver.findElement(By.name("email")).sendKeys(fakeUser.email);
    await driver.findElement(By.name("password")).sendKeys(fakeUser.password);
    await driver.findElement(By.css("button[type='submit']")).click();
  } finally {
    await driver.quit();
  }
})();

You can also use Selenium with Java alongside Faker.js for more robust test automation, enabling you to generate dynamic test data, simulate diverse user interactions, and maintain consistent, reproducible results across different browsers and environments.

Using Faker.js with Playwright (Modern E2E Testing)

Playwright is designed for reliable, fast, and cross-browser end-to-end testing. By integrating Faker.js, you can dynamically generate names, emails, and messages to make your tests more realistic.

Seeding keeps results consistent while still allowing randomized input for broader test coverage. To deep dive into getting started, you can follow this detailed Playwright tutorial for step-by-step guidance on setup, writing tests, and leveraging its full potential in modern test automation.

Example: Submitting a contact form in Playwright with Faker.js

import { test, expect } from "@playwright/test";
import { faker } from "@faker-js/faker";

test("should submit the form successfully with fake data", async ({ page }) => {
  const fakeUser = {
    name: faker.person.fullName(),
    message: faker.lorem.sentence(),
  };

  await page.goto("https://example.com/contact");
  await page.fill("#name", fakeUser.name);
  await page.fill("#message", fakeUser.message);
  await page.click("button[type=submit]");

  await expect(page.locator(".success")).toHaveText(
    "Thank you for contacting us!"
  );
});

Using Playwright to run tests allows you to evaluate how your website performs across different browsers, including Chromium, Firefox, and WebKit. As your testing requirements expand, challenges may arise around maintaining scalability, ensuring consistent results, and managing test reliability across multiple environments.

Using Faker.js with Cypress (End-to-End Browser Testing)

Cypress is built for end-to-end testing in the browser. Instead of manually creating test users, you can use Faker.js to auto-generate credentials, addresses, or payment details during test execution. This helps validate how your UI and backend handle realistic input at scale.

To explore Cypress in more detail and get started step by step, you can follow this comprehensive Cypress tutorial for guidance on setup, writing tests, and maximizing test automation efficiency.

Example: Filling out a signup form in Cypress with Faker.js

import { faker } from "@faker-js/faker";
describe("Signup form with Faker.js data", () => {
  it("should submit the form successfully with fake user data", () => {
    const fakeUser = {
      firstName: faker.person.firstName(),
      lastName: faker.person.lastName(),
      email: faker.internet.email(),
      password: faker.internet.password(),
    };
    cy.visit("/signup");
    cy.get("input[name='firstName']").type(fakeUser.firstName);
    cy.get("input[name='lastName']").type(fakeUser.lastName);
    cy.get("input[name='email']").type(fakeUser.email);
    cy.get("input[name='password']").type(fakeUser.password);
    cy.get("form").submit();
    cy.contains("Welcome, " + fakeUser.firstName).should("be.visible");
  });
});

Running Cypress test cases is crucial for comprehensive and accurate testing of modern web applications. By integrating Faker.js with Cypress testing, you can generate dynamic test data that mirrors real-world scenarios, which not only improves test coverage but also reduces test execution time and minimizes repetitive setup. This ensures faster feedback and more reliable results across your automation suite.

Using Faker.js with Jest (Unit Testing)

Jest is widely used for testing JavaScript and TypeScript applications. Normally, developers hardcode values in their unit tests, which can make tests brittle and repetitive. Faker.js solves this by supplying dynamic, realistic test inputs.

To deep dive and get started, you can follow this detailed Jest tutorial for step-by-step guidance on setup, writing tests, and maximizing unit testing efficiency.

Example: Testing a user validation function with Faker.js in Jest

import { faker } from "@faker-js/faker";
import { validateUser } from "../utils/validateUser"; // Example utility to test

describe("User validation with Faker.js", () => {
  it("should validate a user with generated name and email", () => {
    const fakeUser = {
      name: faker.person.fullName(),
      email: faker.internet.email(),
    };
    const result = validateUser(fakeUser);
    expect(result).toBe(true);
  });
  it("should reject invalid user data", () => {
    const fakeUser = {
      name: faker.person.fullName(),
      email: "invalid-email", // forcing an invalid case
    };

    const result = validateUser(fakeUser);
    expect(result).toBe(false);
  });
});

By integrating Faker.js with Jest testing, you can dynamically generate diverse test inputs for your unit tests, making them more robust and closer to real-world scenarios. This approach reduces reliance on hardcoded values, improves coverage, and ensures your test cases are flexible, maintainable, and capable of detecting edge-case issues efficiently.

Best Practices & Tips for Using Faker.js in Test Automation

When working with Faker.js in test automation, it’s easy to get carried away with the endless variety of data you can generate. While randomized inputs improve coverage, there are certain practices you should follow to ensure tests remain stable, fast, and meaningful.

• Use Seeding in CI/CD to Avoid Flaky Tests: Random data is excellent for catching edge cases, but in CI/CD pipelines, you want repeatability. By setting a seed value, Faker.js will always generate the same set of test data across runs. This helps debug failing builds because you know the exact data used when a test failed.

  Example:

  faker.seed(12345); // Ensures reproducibility in CI/CD
  

  Think of seeding as a safety net, your test is still realistic but no longer unpredictable.

• Don’t Over-Generate Data (Performance Matters): Generating hundreds of random names, emails, or phone numbers when you only need a handful will slow down your tests unnecessarily. Faker.js is lightweight, but large-scale data generation can still impact performance.

  Tip: Only generate what you’ll actually use in the test case. If a form needs one user, don’t pre-generate 50.

• Choose Relevant Locales for Better Coverage: Faker.js supports multiple locales, which makes it easy to test applications that serve global users. Using the right locale ensures test data matches real-world formats (e.g., addresses in Japan, phone numbers in Germany). This helps uncover localization issues early.

  Example:

  const faker = require("@faker-js/faker/locale/de"); // German locale
  console.log(faker.phone.number());
  

  Matching locales to your application’s target regions ensures that you don’t miss region-specific formatting bugs.

• Separate Test Data Generation Logic from Test Execution:A common mistake is mixing data generation logic directly inside test scripts. This makes tests harder to maintain and less reusable. Instead, create a data utility layer where all Faker.js calls live. Your tests can then call this utility whenever fresh data is needed.
  • Cleaner, more readable test scripts.
  • Centralized control over how data is generated.
  • Easier updates if you want to change the way fake data is seeded or structured.

In short: Treat Faker.js as a powerful helper, not just a randomizer. Use it smartly, seed for stability, generate only what’s needed, respect locales, and keep data logic modular. Done right, Faker.js elevates your automation suite without introducing unnecessary noise.

Conclusion

Faker.js transforms how QA teams approach test data, shifting from static, repetitive inputs to dynamic, realistic, and context-aware datasets. Enabling automated generation of diverse user profiles, transactions, and content helps uncover edge cases that might otherwise go unnoticed. Its support for locales, seeding, and modular data generation ensures tests are reliable, reproducible, and globally relevant.

When integrated into modern frameworks like Selenium, Playwright, Cypress, or Jest, Faker.js elevates test automation by reducing manual effort, minimizing flaky results, and increasing confidence in software quality. Ultimately, it empowers teams to simulate real-world scenarios at scale, accelerate development cycles, and deliver more robust applications without compromising data safety or efficiency.

While it lacks flexibility and early feedback mechanisms, it provides strong process discipline, traceability, and scope management, making it ideal for high-stakes environments like finance, government, and infrastructure. Proper planning, role clarity, and disciplined execution are essential for success in Waterfall-driven SDLC projects.

Citations

• Faker JS: https://www.npmjs.com/package/@faker-js/faker
• Faker JS Github: https://github.com/faker-js