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A Django-style Python ORM powered by sqlx (Rust) via PyO3.

Project description

Ryx ORM

Ryx ORM

Django-style Python ORM. Powered by Rust.

Python 3.10+ PyPI Downloads Version License Rust 1.83+

GitHub stars


Ryx gives you the query API you love — .filter(), Q objects, aggregations, relationships — with the raw performance of a compiled Rust core. Async-native. Zero event-loop blocking.

import ryx
from ryx import (
    Model, CharField, IntField, BooleanField, 
    DateTimeField, Q, Count, Sum
)

class Post(Model):
    title = CharField(max_length=200)
    slug = CharField(max_length=210, unique=True)
    views = IntField(default=0)
    active = BooleanField(default=True)
    created = DateTimeField(auto_now_add=True)

    class Meta:
        ordering = ["-created"]

# Setup once
await ryx.setup("postgres://user:pass@localhost/mydb")

# Query like Django, run like Rust
posts = await (
    Post.objects
        .filter(Q(active=True) | Q(views__gte=1000))
        .exclude(title__startswith="Draft")
        .order_by("-views")
        .limit(20)
)

# Aggregations
stats = await Post.objects.aggregate(
    total=Count("id"), avg_views=Avg("views"), top=Max("views"),
)

# Transactions with savepoints
async with ryx.transaction():
    post = await Post.objects.create(title="Atomic post", slug="atomic")
    await post.save()

Why Ryx

Django ORM SQLAlchemy Ryx
API Ergonomic Verbose Ergonomic
Runtime Sync Python Async Python Async Rust
GIL blocking Yes Yes Zero
Backends All All PG · MySQL · SQLite
Migrations Built-in Alembic Built-in

Performance

Benchmark of 1 000 rows on SQLite (lower is better):

Operation Ryx ORM SQLAlchemy ORM SQLAlchemy Core Ryx raw
bulk_create 0.007 s 0.121 s 0.002 s 0.001 s
bulk_update 0.003 s 0.001 s 0.001 s 0.001 s
bulk_delete 0.001 s 0.001 s 0.001 s 0.001 s
filter + order + limit 0.001 s 0.002 s 0.001 s 0.000 s
aggregate 0.000 s 0.001 s 0.001 s 0.000 s

Ryx ORM is 16× faster than SQLAlchemy ORM on bulk inserts and 2× faster on deletes — while keeping the same Django-style API. The raw SQL layer (raw_execute / raw_fetch) gives you near-C speed when you need it.

Run the benchmark yourself:

uv add sqlalchemy[asyncio] aiosqlite
uv run python examples/13_benchmark_sqlalchemy.py

Quick Start

pip install maturin
maturin develop          # compile Rust + install
import asyncio, ryx
from ryx import Model, CharField

class Article(Model):
    title = CharField(max_length=200)

async def main():
    await ryx.setup("sqlite:///app.db")
    await ryx.migrate([Article])
    await Article.objects.create(title="Hello Ryx")
    print(await Article.objects.all())

asyncio.run(main())

Key Features

  • 30+ field types — from AutoField to JSONField, with validation built in
  • Q objects — complex AND / OR / NOT expressions with nesting
  • AggregationsCount, Sum, Avg, Min, Max with GROUP BY and HAVING
  • RelationshipsForeignKey, OneToOneField, ManyToManyField with select_related / prefetch_related
  • Transactions — async context managers with nested savepoints
  • Signalspre_save, post_save, pre_delete, post_delete and more
  • Migrations — autodetect schema changes, generate and apply
  • Validation — field-level + model-level, collects all errors before raising
  • Sync/async bridge — use from sync or async code seamlessly
  • CLIpython -m ryx migrate, makemigrations, shell, inspectdb

Architecture

Ryx Architecture

Your Python queries are compiled to SQL in Rust, executed by sqlx, and decoded back — all without blocking the Python event loop.

Documentation

Full documentation with guides, API reference, and examples: docs

Contributing

See CONTRIBUTING.md for development setup, architecture details, and contribution guidelines.

License

Python code: AGPL-3.0 · Rust code: MIT OR Apache-2.0

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