Synthetic Data Generation in JavaScript: casual vs chance vs faker vs randexp

When building modern web applications, developers often need realistic-looking test data — for UI demos, automated tests, or local development environments. The JavaScript ecosystem offers several libraries to generate synthetic data, each with distinct philosophies and capabilities. Among them, casual, chance, faker, and randexp stand out, but they solve different parts of the problem. Let’s examine how they compare in real-world usage.

🧪 Core Purpose: What Each Library Actually Does

casual, chance, and faker are general-purpose fake data generators. They produce structured values like names, addresses, emails, dates, and more. randexp, by contrast, is a specialized tool that generates random strings matching a given regular expression — it doesn’t know what a "phone number" is, but it can produce strings that look like one if you give it the right pattern.

This fundamental difference means randexp often complements the others rather than competing directly.

// casual: Built-in semantic generators
import casual from 'casual';
const name = casual.full_name; // "John Doe"
const email = casual.email;   // "john.doe@example.com"

// chance: Similar semantic API
import Chance from 'chance';
const chance = new Chance();
const name = chance.name();     // "Emma Thompson"
const email = chance.email();   // "emma.thompson82@example.org"

// faker: Rich, locale-aware data
import { faker } from '@faker-js/faker';
const name = faker.person.fullName(); // "Robert Johnson"
const email = faker.internet.email(); // "robert.johnson@acme.net"

// randexp: Pattern-based string generation only
import RandExp from 'randexp';
const phone = new RandExp(/\d{3}-\d{3}-\d{4}/).gen(); // "555-123-4567"

🌍 Locale and Internationalization Support

If your application serves users in multiple countries, locale support becomes critical.

faker (specifically the community-maintained @faker-js/faker) offers extensive localization. You can switch locales on the fly and even mix them:

import { faker } from '@faker-js/faker';
faker.locale = 'de';
console.log(faker.person.fullName()); // "Müller, Anna"

faker.setLocale('ja');
console.log(faker.person.fullName()); // "田中 花子"

casual includes some non-English data (like Russian names) but lacks a formal locale-switching mechanism. You’re mostly stuck with English defaults unless you manually override providers.

chance has minimal built-in internationalization. While you can seed dictionaries, there’s no official support for alternate locales.

randexp is inherently locale-agnostic — since it works from regex patterns, it can generate any character set you define, but you must craft the pattern yourself.

🔁 Seeding and Reproducibility

Deterministic test runs require seeded randomness so that the same input always produces the same output.

chance makes seeding straightforward:

import Chance from 'chance';
const chance1 = new Chance(123);
const chance2 = new Chance(123);
console.log(chance1.name() === chance2.name()); // true

faker also supports seeding via its .seed() method:

import { faker } from '@faker-js/faker';
faker.seed(123);
console.log(faker.person.fullName()); // Always the same

casual allows seeding through its global seed() function:

import casual from 'casual';
casual.seed(123);
console.log(casual.full_name); // Consistent across runs

randexp does not expose a seed API. Because it relies on JavaScript’s Math.random(), results aren’t reproducible unless you monkey-patch the global random function — which isn’t recommended in production code.

🧩 Extensibility and Custom Data

All three general-purpose libraries let you define custom generators, but their approaches differ.

casual uses a provider registration system:

import casual from 'casual';
casual.define('product_name', () => `${casual.word} ${casual.word}`);
console.log(casual.product_name); // "Solar Widget"

chance lets you add mixins:

import Chance from 'chance';
const chance = new Chance();
chance.mixin({
  product_name() {
    return `${this.word()} ${this.word()}`;
  }
});
console.log(chance.product_name()); // "Quantum Gadget"

faker supports module extension through direct assignment:

import { faker } from '@faker-js/faker';
faker.product = {
  name: () => `${faker.word.adjective()} ${faker.word.noun()}`
};
console.log(faker.product.name()); // "Innovative Solution"

randexp doesn’t need extensibility in the same way — you just write a new regex. However, complex patterns can become hard to maintain.

⚠️ Maintenance Status and Deprecation Warnings

As of 2024, casual is effectively unmaintained. Its npm page shows no recent updates, and the GitHub repository hasn’t seen meaningful activity in years. While it still works, it should be avoided in new projects.

chance is in maintenance mode. The author states it’s “feature complete” and only accepts critical bug fixes. It’s stable but unlikely to evolve.

faker (the original faker package) was deprecated in early 2022. The community fork @faker-js/faker is now the active, well-maintained successor. Any reference to “faker” in modern contexts should mean this fork.

randexp remains actively maintained, with recent updates addressing security and compatibility.

🛑 Important: Do not install the original faker package (npm install faker). Use @faker-js/faker instead.

🛠️ Real-World Usage Scenarios

Scenario 1: Generating User Profiles for E2E Tests

You need consistent, realistic user objects with names, emails, and addresses.

• ✅ Best choice: @faker-js/faker
• Why? Rich person/address modules, seeding support, and active maintenance.

import { faker } from '@faker-js/faker';
faker.seed(42);
const user = {
  name: faker.person.fullName(),
  email: faker.internet.email(),
  address: faker.location.streetAddress()
};

Scenario 2: Creating Mock API Responses with Custom Formats

Your backend returns IDs like USR-XXXX and order codes like ORD-9A3B.

• ✅ Best choice: randexp + faker
• Why? Use faker for semantic data and randexp for pattern-based IDs.

import RandExp from 'randexp';
import { faker } from '@faker-js/faker';

const userId = new RandExp(/USR-[A-Z0-9]{4}/).gen();
const orderCode = new RandExp(/ORD-[0-9A-Z]{4}/).gen();
const payload = {
  id: userId,
  code: orderCode,
  customer: faker.person.fullName()
};

Scenario 3: Lightweight Test Data in a Browser Environment

You’re writing unit tests in Jest and want minimal dependencies.

• ✅ Best choice: chance
• Why? Small footprint, simple API, and no heavy locale bundles.

import Chance from 'chance';
const chance = new Chance();
test('user creation', () => {
  const mockUser = { name: chance.name(), age: chance.age() };
  // ...
});

Scenario 4: Legacy Codebase Using casual

You inherited a project using casual and need to decide whether to migrate.

• ✅ Recommendation: Plan a migration to @faker-js/faker
• Why? casual won’t receive security patches or compatibility updates.

📊 Summary Table

💡 Final Recommendation

• For new projects, use @faker-js/faker as your primary fake data generator. It’s the most capable, well-maintained, and flexible option.
• Reach for randexp when you need to generate strings that match specific formats not covered by semantic generators (e.g., license keys, serial numbers).
• Consider chance only if you need a tiny, zero-locale-footprint library for basic randomness in constrained environments.
• Avoid casual in new codebases due to lack of maintenance.

Remember: these tools are for development and testing only. Never use them to generate real user data or in production data pipelines.