DomNarzędzia[pl] Mock Data Generator

[pl] Mock Data Generator

[pl] Generate random JSON or CSV data for testing purposes with custom schema.

[pl] Configuration

[pl] Fields

[pl] Data Preview

Loading...

[pl] Generate data to see preview...

Himanshi Gangwar

[pl] Community Credit

[pl] This tool was inspired by a suggestion from Himanshi Gangwar(@himanshig25).
[pl] Thanks for helping make DailyDevTools better ❤️

Use these tools directly in Chrome

Install the DailyDevTools extension — access all tools from your browser toolbar

Add to Chrome

What is Mock Data Generator?

Building and testing applications requires realistic fake data — names, email addresses, phone numbers, addresses, dates, and more. Hardcoding test data leads to brittle tests, and real user data cannot be used for development due to privacy regulations. DailyDevTools' Mock Data Generator creates configurable sets of fake but realistic-looking data in JSON, CSV, or SQL format, ready for database seeding and API testing.

How to use Mock Data Generator

  1. 1Select the fields you need: name, email, phone, address, date, UUID, lorem ipsum, numbers, etc.
  2. 2Set the number of records to generate (1–1000)
  3. 3Choose the output format: JSON array, CSV, or SQL INSERT statements
  4. 4Click Generate and then Download or Copy the mock dataset

Frequently asked questions

Is the generated data truly random and private?
Yes. All data is generated locally in your browser using random algorithms. No real people's data is used. The names, emails, and addresses are entirely fictional and generated on-demand.
Can I use mock data for GDPR compliance testing?
Yes. Using fictional mock data instead of real user data for development and testing is a core GDPR compliance practice — it eliminates the risk of exposing real personal data in non-production environments.
What is the difference between mock data and seed data?
Seed data is a fixed, deterministic dataset loaded once to initialize a database (e.g., admin user, default categories). Mock data is randomly generated for testing different scenarios. Both are important — seeds for consistent setup, mocks for varied test cases.

Comments