TTULAKITO
Developer

Mock Data Generator

Generate fake users, addresses, and records as JSON for testing.

All tools

Mock data

[
  {
    "id": 1,
    "name": "Hedy Torvalds",
    "email": "hedy.torvalds@example.com",
    "age": 27,
    "city": "Lisbon",
    "active": false
  },
  {
    "id": 2,
    "name": "Anita Lovelace",
    "email": "anita.lovelace@example.com",
    "age": 71,
    "city": "Lisbon",
    "active": false
  },
  {
    "id": 3,
    "name": "Grace Hamilton",
    "email": "grace.hamilton@example.com",
    "age": 42,
    "city": "Cape Town",
    "active": true
  },
  {
    "id": 4,
    "name": "Rosa Torvalds",
    "email": "rosa.torvalds@example.com",
    "age": 43,
    "city": "Hanoi",
    "active": true
  },
  {
    "id": 5,
    "name": "Grace Thompson",
    "email": "grace.thompson@example.com",
    "age": 24,
    "city": "Dublin",
    "active": true
  }
]

Frequently asked questions

Is mock data safe to use in production seed scripts?
Mock generators produce values that look real but are not - fake names, emails on example.com, and made-up addresses. That is perfect for tests and demos, but never use these as real customer records.
How do I get deterministic mock data across test runs?
Use a seeded random generator and pass the same seed each run, which produces identical fake records every time. That makes snapshot tests stable and bug reports easier to reproduce.
Will the generated emails or phone numbers belong to real people?
Fake data uses reserved patterns like the example.com email domain and 555 phone prefixes specifically to avoid hitting real accounts. Be cautious if you switch a generator to "realistic" mode, which may produce values that happen to collide with real records.