What is Mock Data?

Mock data is algorithmically generated, format-valid data used in software development and testing without affecting real systems, users, or transactions. Mock Jutsu generates algorithmically correct test data across 390+ types (SSN, IBAN, credit cards, FHIR records, and more) instantly and offline.

Why Use Mock Data?

Create a safe test environment without using real customer data
Maintain GDPR, PCI DSS and regulatory compliance during testing
Generate repeatable, deterministic data on every test run
Develop against endpoints or services that don't exist yet
Generate thousands of unique records for load and performance tests

Use Across All Testing Layers

Unit & Integration Tests

Generates instant data for developers to test their modules without a real database or external service.

System & End-to-End Tests

Enables QA engineers to build complete scenarios representing real user flows.

Acceptance Tests

Demonstrate features to business stakeholders with realistic data without touching the live system.

Load & Performance Tests

Simulate real production load by generating thousands of unique records per second with JMeter.

Use in Any Environment

CLI

In terminals and CI/CD pipelines

mockjutsu generate ssn

Python API

In any Python project via PyPI

from mockjutsu import jutsu
jutsu.generate('ssn')

REST API

Language-agnostic, as a server via Docker

GET /generate/ssn

JMeter Plugin

In load and performance tests

Mock Jutsu Functions → ssn()

Maven / Java

In JVM-based projects

MockJutsu.generate("ssn")

Frequently Asked Questions

What is the difference between mock data and real data?

Mock data is synthetic data not belonging to any real user or transaction, generated purely for testing purposes. Real data carries GDPR/PCI DSS compliance risks; mock data does not. Mock Jutsu generates data that is format and checksum-valid but does not correspond to any real person or account.

How does Mock Jutsu differ from Faker or Mimesis?

Faker generates random-looking text; Mock Jutsu uses real algorithms like IBAN (MOD-97), Luhn (card numbers), and TCKN (weighted checksum) to produce format and checksum-valid data. This means test data passes validation in real integration scenarios.

How do I use it with JMeter?

Install the 'Mock Jutsu Functions' plugin via JMeter Plugins Manager. Then add a JSR223 Sampler inside your Thread Group and use functions like tckn(), iban(), or cardnum() directly in your test plan.

What does zero-dependency mean?

Mock Jutsu requires no third-party libraries to run. All algorithms are implemented in pure Python, minimizing security vulnerability risk and ensuring installation works in any environment.

Can generated data belong to a real person?

No. Mock Jutsu generates only algorithmically valid synthetic data. Generated TCKNs, IBANs or card numbers do not correspond to any real person or account, but behave like real data in format validation tests.