sqlalchemy-seedling 0.2.0

Async-native seeder and factory library for SQLAlchemy

sqlalchemy-seedling

Async-native seeder and factory library for SQLAlchemy. Dependency-aware runners, declarative factories, and a CLI — Laravel-style ergonomics for the Python async ecosystem.

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Why seedling?

• Dependency-aware — declare depends_on between seeders and the runner resolves the correct execution order automatically (Kahn's topological sort).
• Async-native — built for async/await and SQLAlchemy's async session from the ground up; no sync wrappers.
• Declarative factories — Factory[T] with LazyAttribute, Sequence, SubFactory, and as_trait() for composable test data.
• Environment filtering — tag seeders with environments = {DEV, TEST, PROD} and the runner skips what doesn't belong.
• Zero boilerplate CLI — one line in pyproject.toml and you get seed run, seed fresh, and seed list.

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Installation

pip install sqlalchemy-seedling
# or
uv add sqlalchemy-seedling

Requires Python 3.11+ and SQLAlchemy 2.0+.

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Quick start

1. Define seeders

# myapp/seeders/user_seeder.py
from seedling import Seeder, DEV_AND_TEST
from sqlalchemy.ext.asyncio import AsyncSession
from myapp.models import User

class UserSeeder(Seeder):
    environments = DEV_AND_TEST

    async def run(self, session: AsyncSession) -> None:
        session.add(User(email="[e-mail]", name="Admin"))
        await session.commit()

    async def truncate(self, session: AsyncSession) -> None:
        await session.execute(delete(User))
        await session.commit()


# myapp/seeders/post_seeder.py
from seedling import Seeder, DEV_AND_TEST

class PostSeeder(Seeder):
    depends_on = [UserSeeder]       # runs after UserSeeder automatically
    environments = DEV_AND_TEST

    async def run(self, session: AsyncSession) -> None:
        ...

2. Create a runner factory

# myapp/seeders/__init__.py
from seedling import SeederRunner
from myapp.db import async_session_maker
from myapp.seeders.user_seeder import UserSeeder
from myapp.seeders.post_seeder import PostSeeder

def create_runner(env: str = "development") -> SeederRunner:
    runner = SeederRunner(session_factory=async_session_maker, env=env)
    runner.register(UserSeeder, PostSeeder)
    return runner

3. Configure the CLI

# pyproject.toml
[tool.seedling]
runner = "myapp.seeders:create_runner"

4. Run

seed run                        # run all seeders for the default env
seed run UserSeeder             # run a specific seeder (+ its dependencies)
seed fresh                      # truncate then re-seed
seed list                       # print execution order without running
seed run --env production       # target a different environment

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Factories

Use Factory[T] to build and persist model instances with minimal boilerplate.

from seedling import Factory, LazyAttribute, Sequence, SubFactory, faker
from myapp.models import User, Post

class UserFactory(Factory[User]):
    model = User
    email = LazyAttribute(lambda f: faker.unique.email())
    name  = Sequence(lambda n: f"User {n}")

class PostFactory(Factory[Post]):
    model = Post
    author = SubFactory(UserFactory)       # creates a User row automatically
    title  = LazyAttribute(lambda f: faker.sentence())

# In tests or seeders:
user = await UserFactory.create(session)
posts = await PostFactory.create_batch(session, 5)

# build() never touches the DB — useful in pure unit tests:
user = UserFactory.build(email="[e-mail]")

# Traits for scenario-specific variants:
AdminUser = UserFactory.as_trait(is_superuser=True)
admin = await AdminUser.create(session)

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Helpers

from seedling import upsert

# Idempotent insert — ON CONFLICT DO NOTHING (PostgreSQL) / INSERT OR IGNORE (SQLite)
await upsert(session, MyModel, {"id": 1, "name": "Foo"})
await upsert(session, MyModel, {"id": 1, "name": "Foo"}, constraint="uq_mymodel_name")

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Environment constants

from seedling import DEV, TEST, PROD, ALL, DEV_AND_TEST

Constant	Value
DEV	"development"
TEST	"test"
PROD	"production"
DEV_AND_TEST	{"development", "test"}
ALL	{"development", "test", "production"}

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On the horizon

• State tracking — seedling_state table records every run with timestamps, status, and a content hash for drift detection. seed status and --new-only flag coming in 0.3.
• Factory power — AutoFactory[Model] with mapper introspection, declarative Trait classes, @post_generation hooks, RelatedFactory, and bulk insert. Coming in 0.4.
• Scaffolding — seed init, seed make:seeder, seed make:factory, and a transactional pytest fixture. Coming in 0.5.

See ROADMAP.md for the full plan.

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License

MIT — see LICENSE.