Generate realistic test data for your databases. Schema-aware, relationship-preserving, privacy-safe.
Project description
Seedbase
Generate realistic, relationship-preserving, privacy-safe test data for your databases — and pull it straight into your local or CI database.
Seedbase lives on seedba.se: you model (or import) a schema there, generate datasets, and use this package to pull them into Postgres, MySQL, SQLite and more. Schema-aware, foreign-key-correct, reproducible by seed.
Install
pip install seedbase
Zero dependencies — pure Python (3.10+).
CLI quickstart
seedbase login # opens the browser, stores a token
seedbase init # creates .seedbase.json (project + target DB)
seedbase generate --seed 42 # trigger a generation on the platform
seedbase pull all # write schema + data into your target DB
The CLI is pull-oriented: schema and datasets live on the platform, you pull them into your database. Other commands: projects, generations, connections, pull schema|data|subset, mask, db-push, diff, export config, import config.
Python SDK
from seedbase import SeedbaseClient
client = SeedbaseClient(token="dr_sk_...") # or from ~/.seedbase/config.json
gen = client.generate(project_id, seed=42, wait=True)
data = client.download(gen["id"], fmt="sql")
pytest fixtures
Seedbase ships a pytest plugin, so a freshly seeded dataset is one fixture away:
def test_orders(seeded_data):
assert seeded_data # deterministic test data pulled from the platform
Configure via env (SEEDBASE_TOKEN, SEEDBASE_PROJECT, SEEDBASE_SEED) or pytest.ini.
Links
- Website: https://seedba.se
- Docs: https://seedba.se/docs
- API keys: https://seedba.se/settings?tab=api-keys
MIT licensed.
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