Mock Data Generator

About the Mock Data Generator

Seeding a database, filling a design with something other than "Test User", or building a fixture for a test — all of them need rows that look plausible and none of them should use real people's details.

This produces mock rows as JSON, NDJSON, CSV or SQL INSERT statements, with the fields you choose: identifiers, UUIDs, names, email addresses, phone numbers, addresses, cities, postcodes, company names, timestamps, prices and booleans.

Names and addresses come from India by default, with the United States and United Kingdom available. That default is deliberate rather than incidental. Most generators produce American names exclusively, so an Indian team building for Indian users ends up demonstrating their product to stakeholders with a screen full of Johns and Marys from Springfield. Phone numbers follow the right shape for each locale too — an Indian mobile starting with 6 to 9, a UK number starting 07, an American number with a valid area code.

The seed field is the part that matters for testing. Generation is driven by a seeded pseudorandom generator rather than the ordinary random function, so the same seed always produces exactly the same rows. A fixture that changes between runs turns a failing test into a mystery: you cannot tell whether the code broke or the data moved. Give each fixture its own seed and it is reproducible forever, on any machine.

The SQL output quotes and escapes values properly, so a name containing an apostrophe produces valid SQL rather than a syntax error. None of these people exist. The names are drawn from common name lists and combined at random, which is why you may occasionally see a combination that belongs to somebody real — the addresses will not.

How to use it

1. 1Set how many rows you need and pick the fields to include.
2. 2Choose the locale so names, phone numbers and postcodes match where your users are.
3. 3Pick the output format — SQL if you are seeding directly, CSV for a spreadsheet, JSON for a fixture.
4. 4Set a seed and record it with the fixture. The same seed regenerates the identical rows whenever you need them.

Questions

Are these real people's details?

No. First names, surnames, street names and cities are drawn from common lists and combined at random, and the numbers are generated. A name may coincide with a real person's, which is unavoidable with common names; the address and phone number attached to it will not be theirs.

Why does the seed matter?

Because it makes the data reproducible. The same seed always produces the same rows, so a test fixture stays stable between runs and between machines. Without that, a failing test leaves you unable to tell whether the code or the data changed.

Can I use this data in production?

For seeding a demo or staging environment, yes. Never mix it into a production table holding real records — plausible fake rows are extremely hard to distinguish from real ones once they are in the same table.

How many rows can it generate?

Up to a thousand at a time. Beyond that a browser tab is the wrong tool; take the SQL output as a template and generate the rest in a script where you can stream it straight into the database.