falso
Generate massive amounts of fake data in the browser and NodeJS with tree-shakable, fully-typed functions.
What is falso?
Falso is a comprehensive JavaScript and TypeScript library for generating realistic fake data in both browser and Node.js environments. It provides developers with a robust toolset of over 200 functions for creating mock data during development, testing, and prototyping, ensuring applications can be built and validated with realistic datasets. The library is designed to be tree-shakable and fully typed for optimal performance and developer experience.
Developers and testers working in JavaScript or TypeScript who need to generate mock data for frontend, backend, or full-stack applications. This includes those building prototypes, writing unit/integration tests, or creating demos that require realistic, structured fake data.
Developers choose Falso for its combination of a vast, modular API (205+ functions), tree-shakability to minimize bundle size, and full TypeScript support with strong typing. Its unique selling points include seedable randomness for reproducible data, specialized entity functions (like users or products), and factory patterns for customizable, consistent mock object generation.
Overview
All the Fake Data for All Your Real Needs 🙂
Use Cases
Best For
- Generating mock user data (emails, names, addresses) for prototyping a user management interface.
- Creating realistic product catalogs with fake data for e-commerce application testing.
- Seeding databases with consistent, reproducible fake datasets for development and QA environments using a fixed seed.
- Building demo applications or live examples that require large volumes of believable sample data without external APIs.
- Writing unit and integration tests that depend on controlled, typed mock data objects in TypeScript projects.
- Reducing bundle size in frontend applications by tree-shaking only the specific fake data functions needed.
Not Ideal For
- Projects requiring fake data for highly specialized or obscure domains not covered by the library's 205 predefined functions.
- Applications that need to generate complex, relational datasets with intricate dependencies between multiple entities.
- Teams preferring a graphical interface or no-code tool for creating and managing mock data without programming.
Pros & Cons
Pros
Only the functions you import are bundled, keeping application sizes minimal as emphasized in the README's key features and design philosophy.
Complete typing support ensures type safety and enhances IDE autocompletion, making it ideal for modern TypeScript workflows, as highlighted in the 'Fully Typed' feature.
With over 205 functions, it covers common entities like users, products, and addresses, reducing the need for manual data creation during development and testing.
Setting a seed allows for reproducible fake data generation, which is crucial for consistent testing and debugging, as demonstrated in the README's seed example.
Cons
The library is restricted to its predefined functions; generating data for unique or niche use cases requires additional coding or extensions beyond the provided API.
While it generates data in memory, there's no direct support for exporting to common formats like CSV or JSON, necessitating extra steps for data persistence or sharing.
The README points to a docs site, but it may lack in-depth examples for advanced usage, such as creating custom factory functions or handling edge cases.
Frequently Asked Questions
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.