An async Python ORM for PostgreSQL, SQLite and ClickHouse, built with relations in mind. Models are
plain classes, queries are built lazily through a QuerySet, and migrations are generated from the
changes to the models. Coming from Django? See Coming from Django.
- Fast. A Rust PostgreSQL driver decodes rows and converts values outside Python, and every query shape is built once: a repeated query only binds its new values — see Benchmarks.
- Relations done right. Composite primary keys everywhere — as foreign-key targets too — generic
relations made of real foreign keys,
select_related()/prefetch_related()with filters, recursive queries over a tree, and an error instead of a silently inflated aggregate — see Models and relations. - Your schema, declared. Constraints, partial and expression indexes, triggers, views,
materialized views, functions, sequences, row level security policies, grants and partitioning
live in the model's
Metaand are created and changed by migrations — see The schema inMeta. - Application patterns built in. Soft delete, versioned rows, multi-tenancy (by column, by
schema or by row level security), optimistic locking, dirty-field tracking and a transactional
outbox are
Metaoptions — see Behavior declared inMeta. - Migrations you can trust. Detected from the models, checked for operations that lock a busy
table, compared with the live database (
hare drift), and generated from an existing database (hare inspectdb) — see Migrations. - Every database on its own terms. SQLite, PostgreSQL and ClickHouse are dialects built on the
public API a third-party package uses; PostgreSQL's types, indexes, PostGIS, pgvector, full-text
search and
LISTEN/NOTIFYcome with it, and a database lacking a feature raises a clear error instead of returning a wrong result — see Databases. - Ready for production. Observers, OpenTelemetry, SQL comment tags, an N+1 detector, pool metrics, distributed transactions, read replicas and routers, PgBouncer support, Pydantic schemas and Litestar, FastAPI and Robyn integrations — see Observability.
- Checked before it runs. A mypy plugin rejects a misspelled filter and types the rows of
values(); a pytest plugin, factories and query-count assertions cover the tests — see Testing and type checking.
The full tour, area by area, is on the documentation's home page.
Contents
Quick start
pip install hare-orm
# library/models.py
from hare import fields
from hare.models import Model
class Author(Model):
id = fields.IntField(primary_key=True)
name = fields.CharField(max_length=120)
class Book(Model):
id = fields.IntField(primary_key=True)
author = fields.ForeignKeyField("models.Author", related_name="books")
title = fields.CharField(max_length=300)
rating = fields.IntField(default=0)
# main.py
import asyncio
from hare import Hare, HareConfig
from library.models import Author, Book
async def main() -> None:
await Hare.init(HareConfig.from_db_url("sqlite+aiosqlite://db.sqlite3", {"models": ["library.models"]}))
await Hare.generate_schemas()
author = await Author.objects.create(name="Ursula K. Le Guin")
await Book.objects.create(author=author, title="The Left Hand of Darkness", rating=5)
async for book in Book.objects.filter(author__name__icontains="le guin").select_related("author"):
print(book.title, "—", book.author.name)
await Hare.close_connections()
asyncio.run(main())
A real project keeps its schema in migrations instead of generate_schemas():
hare makemigrations, then hare migrate. See
Your first model.
Installation
pip install hare-orm
pip install hare-orm[asyncpg] # the pure-Python PostgreSQL driver, instead of the Rust one
pip install hare-orm[clickhouse-connect] # the ClickHouse dialect over HTTP (clickhouse-connect)
pip install hare-orm[clickhouse-driver] # the ClickHouse dialect over the native TCP protocol (clickhouse-driver)
pip install hare-orm[sqlite-vec] # vector search on SQLite
pip install hare-orm[encryption] # EncryptedTextField / EncryptedJSONField (Fernet)
pip install hare-orm[fastapi] # also: litestar, robyn, request-query, taskiq
pip install hare-orm[kafka] # outbox delivery; also: rabbitmq, redis, http
pip install hare-orm[opentelemetry] # an OpenTelemetry span around every query
pip install hare-orm[pytest] # the pytest plugin; also: mypy, pyright
pip install hare-orm[ipython] # `hare shell` with IPython
Every extra is listed under Installation. Requires Python 3.12, 3.13 or 3.14.
Benchmarks
hare-orm against SQLAlchemy, tortoise-orm, yara-orm and Django on PostgreSQL, SQLite and ClickHouse, on the same scenarios: how many times slower than hare-orm each ORM is on each database, on average, and hare-orm's operations per second under load, measured warm — a running application, not one just started:
Every scenario, the machine and the versions are on the
Benchmarks pages; the benchmark itself is
benchmarks/bench.py.
Documentation
hare-orm.github.io/hare-orm — the full
reference: every field type, Meta option, QuerySet method, migration operation, transaction
primitive, dialect feature, PostgreSQL type and index, and the exception hierarchy, in English and
Russian. If you're new to hare-orm, start with
Getting Started.
To build and browse it locally instead (e.g. to preview an unreleased change):
poetry install
poetry run mkdocs serve
Versioning and releases
hare-orm follows Semantic Versioning. Its public API is what the documentation describes; undocumented names and names with a leading underscore are internal and may change in any release.
Before 1.0.0 the API is still settling:
- a patch release (
0.9.1) only fixes bugs; - a minor release (
0.10.0) adds features and may change or remove public API. Every such change is listed under Breaking changes in that release's CHANGELOG entry. A renamed or removed name is gone in that same release — hare-orm doesn't keep deprecated aliases.
From 1.0.0 on, breaking changes land only in a major release. Pin the minor version you tested
against (hare-orm>=0.9,<0.10) and read the changelog before moving to the next one.
Each release is tagged vX.Y.Z, published to PyPI and to
GitHub Releases, and described in
CHANGELOG.md. Work in progress lives on the dev branch; main points at the
latest release.
Supported versions
| Component | Supported |
|---|---|
| hare-orm | The latest minor release; fixes ship as its patch releases |
| Python | CPython 3.12, 3.13, 3.14 |
| SQLite | 3.35.5+ |
| PostgreSQL | 14+ |
| PgBouncer | 1.22.1+ |
| ClickHouse | 25.8+ |
| Redis, RabbitMQ, Kafka (outbox) | 7.2+, 4.0+, 3.9+ |
Full support is promised on Linux only: the databases are tested there. On Windows and macOS hare installs and runs for development — the wheels, the CLI and the tests reading no database are checked on all three systems.
Dropping a Python or database version is a breaking change and is announced in the changelog. Security fixes follow SECURITY.md.
Contributing
Bug reports, feature proposals and pull requests are welcome. CONTRIBUTING.md
covers the dev environment, the test matrix (SQLite, PostgreSQL via
asyncpg and via the Rust driver, PgBouncer, ClickHouse), code style, how a change gets reviewed and
merged, and the sign-off every commit needs.
License
MIT — see LICENSE. hare-orm began as a fork of Tortoise ORM and vendors an adapted
copy of PyPika's query-builder internals; both are Apache License 2.0. The Rust PostgreSQL driver
was inspired by the one in yara-orm, an open-source ORM
under the MIT License, and adapts parts of its code. The required notices of all three live in
NOTICE.md.
1 maintainer
Metadata
1 maintainer
Release files for hare-orm 0.10.0
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