SimpleIDGen
§ · Use Case · CI / Testing

Deterministic Test Data for CI

Test fixtures should be identical on every run. SimpleIDGen is deterministic by seed — the same seed produces the same people, byte for byte — so you can pin a dataset once and rely on it across your suite and CI, without copying production data or fighting random fixtures.

The sample is a stable, no-login fixture. Generate custom seeds and sizes from a free account →

§ · Same seed, same people

Generation is fully reproducible: a given seed always yields the same records, in the same order, with the same values. Pin a seed for a suite and the fixture never drifts — so a failing test means your code changed, not the data. Different seeds give independent, non-overlapping populations when you want variety.

The free 1,000-row sample is itself a fixed artifact — commit it as a fixture, or pull it in a setup step, and every run sees identical data.

§ · Why not the usual options
ApproachProblem in CI
A copy of production dataCompliance risk, and the data shifts as prod changes — flaky, non-reproducible tests.
Random fakersNon-deterministic unless seeded, and fields are independent — a 24-year-old with stage-3 CKD breaks realistic assertions.
Hand-written fixturesTiny, unrealistic, and tedious to maintain at scale.
SimpleIDGenDeterministic, calibrated, and as large as you need — a fixture that looks like real people and never drifts.
§ · Frequently asked
Q1
Is generation actually reproducible?

Yes — the generator is deterministic by seed. The same seed yields identical records every time, so fixtures don't drift between runs.

Q2
Can I use it without an account?

The 1,000-row sample needs no signup and never changes — ideal as a committed fixture. For custom seeds and sizes, a free account generates up to 5,000 rows per day.

Q3
How do I pick a seed?

Any integer works; reuse the same one for a stable fixture, or vary it for independent populations. The seed is part of the generation request and is recorded in the dataset manifest.

Q4
What formats?

CSV and JSONL — drop straight into a database seed step, a test fixture, or a data pipeline.