JSON Generator

What is the JSON Generator?

The JSON Generator produces structured sample data, objects with realistic-looking names, emails, dates, numbers, and identifiers, for use as test fixtures, API mocks, and development seed data.

Building anything data-driven requires data, and real data is usually unavailable early in development or unsafe to use because it contains personal information. Hand-writing fixtures is slow and tends to produce unrealistically tidy records.

Generated data avoids both problems. It produces volume quickly, it contains no real personal information, and it can include the awkward cases, long names, unusual characters, missing optional fields, that hand-written fixtures rarely cover but that break interfaces in practice.

Using synthetic data rather than a copy of production data is also the right default from a privacy standpoint. Production copies in development environments are a recurring source of data breaches, and generated data removes the exposure entirely.

How to use the JSON Generator

1. Define the shape you want. Specify the fields and their types, strings, numbers, booleans, dates, identifiers, and nested objects.
2. Set how many records to produce. Generate one object or an array of many for list and pagination testing.
3. Generate. A JSON document matching your specification is produced immediately.
4. Copy or download. Save as a fixture file or paste into your mock server.

Worked examples

Fields: id (uuid), name (string), email (email),
        active (boolean), createdAt (date)
Count:  3

[
  {
    "id": "f47ac10b-58cc-4372-a567-0e02b2c3d479",
    "name": "Amara Okafor",
    "email": "amara.okafor@example.com",
    "active": true,
    "createdAt": "2024-03-15T09:24:11Z"
  },
  {
    "id": "9c1e4a7b-2d3f-4e8a-b5c6-7d8e9f0a1b2c",
    "name": "Tomasz Nowak",
    "email": "tomasz.nowak@example.com",
    "active": false,
    "createdAt": "2024-07-02T16:41:53Z"
  },
  {
    "id": "3b8d5f2a-6c9e-4b1d-a7f3-2e5c8a9b4d61",
    "name": "Mei-Ling Chen",
    "email": "mei-ling.chen@example.com",
    "active": true,
    "createdAt": "2024-11-28T04:07:36Z"
  }
]

Common use cases

• Seeding a development database. Populating a local environment with enough records to work with realistically.
• Mocking API responses. Building frontend features before the backend endpoint exists.
• Testing list and pagination behaviour. Generating enough records to exercise paging, sorting, and filtering.
• Creating demo content. Populating a prototype with plausible data for a walkthrough.
• Load testing. Producing bulk payloads to exercise a service under volume.

Features and limitations

• Generates strings, numbers, booleans, dates, emails, and UUIDs.
• Supports nested objects and arrays.
• Produces single objects or arrays of arbitrary length.
• Runs entirely in the browser with no network requests.
• Data is synthetic and randomly generated, names and emails are fabricated and do not correspond to real people.

Frequently asked questions