seedbase 0.2.0

Generate realistic test data for your databases. Schema-aware, relationship-preserving, privacy-safe.

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.

Create a free account at seedba.se/register, no credit card. The free tier is enough to generate full, foreign-key-consistent datasets.

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 realistic, foreign-key-consistent test data is one fixture away. pytest fixtures are dependency injection, so this is your test data, injected.

Inject a populated test database (the headline). The target database needs its schema already migrated; SeedBase fills it with FK-consistent data and cleans up after the session. Needs SQLAlchemy 2.0 (pip install "seedbase[database]"):

import sqlalchemy

def test_pagination(seeded_database):
    # seeded_database is a live connection to a DB full of realistic data
    rows = seeded_database.execute(
        sqlalchemy.text("SELECT email FROM users LIMIT 5")
    ).fetchall()
    assert all("@" in email for (email,) in rows)

Inject the rows directly (no database, no driver):

def test_user_shape(seeded_rows):
    # {table_name: [row_dict, ...]}, in foreign-key-safe order
    assert seeded_rows["users"][0]["email"]

Raw bytes (SQL/CSV/JSON dump) if you want to load it yourself:

def test_dump(seeded_data):
    assert seeded_data

Deterministic per seed, so the same seed gives the same data and your tests are reproducible. Configure via env (SEEDBASE_TOKEN, SEEDBASE_PROJECT, SEEDBASE_SEED, SEEDBASE_TEST_DATABASE_URL) or pytest.ini (seedbase_project, seedbase_seed, seedbase_rows, seedbase_database_url). All fixtures skip with a helpful message if the project or credentials are missing, so they never break a suite that has not configured them.

Links

• Website: https://seedba.se
• Docs: https://seedba.se/docs
• API keys: https://seedba.se/settings?tab=api-keys

MIT licensed.