Ormophine
A fast, Pythonic ORM that gets out of your way.
Write database queries the way you think — in plain Python.
The Problem with Other ORMs
Most Python ORMs are either too verbose, too magical, or too slow. Compare fetching filtered rows with a popular ORM versus Ormophine:
Other ORMs:
# SQLAlchemy (Core)
with engine.connect() as conn:
stmt = select(users.c.phone, users.c.name, users.c.age).where(
and_(
users.c.age > 18,
or_(
users.c.phone.like('+98%'),
func.substr(users.c.phone, 1, 3) == '+98'
)
)
).order_by(users.c.age)
result = conn.execute(stmt).fetchall()
Ormophine:
my_db = Ormophine.Sqlite('my_db')
users = my_db.users
phone, name, age = users.phone, users.name, users.age
users.get_row(
[phone, name, age],
where = (age > 18) & (phone.startswith('+98') | (phone[:3] == '+98')),
order_by = age
)
Same result. No boilerplate. No imports. No ceremony.
Why Ormophine?
- Intuitive syntax — columns behave like Python variables with full operator overloading (
>,&,|,+,[],.startswith(), etc.) - Fast — built on a dedicated writer thread + read-only connection pool; no ORM overhead on the hot path
- Multi-database — one API across all supported backends
- Connection pooling built-in — parallel reads, serialized writes, no configuration needed
- WAL mode support (SQLite) — automatic checkpointing for maximum write throughput
- Blocking and non-blocking — fire-and-forget writes or wait for commit confirmation
Supported Databases
| Database | Status |
|---|---|
| SQLite | ✅ Available |
| MySQL | 🔧 In development |
| MariaDB | 🔧 In development |
| PostgreSQL | 🔧 In development |
The API is identical across all backends. Switch databases by changing one line.
Benchmark Results
📊 Coming soon — benchmark results comparing Ormophine against SQLAlchemy, Tortoise ORM, and raw DB-API 2.0 will be published here across INSERT, SELECT, bulk operations, and concurrent read workloads.
Quick Examples
Connect and access tables
import Ormophine
db = Ormophine.Sqlite('company.db')
# Tables and columns are discovered automatically
users = db.users
orders = db.orders
Insert
users.insert({
users.name: 'Alice',
users.email: 'alice@example.com',
users.age: 30
})
Select with conditions
name, email, age = users.name, users.email, users.age
rows = users.get_row(
[name, email],
where = (age >= 18) & name.startswith('A'),
order_by = age
)
Update
users.update(
update = {users.age: users.age + 1},
where = users.status == 'active'
)
Bulk insert
users.bulk_insert(
columns = [users.name, users.age],
data_list = [['Bob', 25], ['Carol', 32], ['Dave', 28]]
)
Joins
from Ormophine import Join
result = orders.join(
columns = [users.name, orders.amount, orders.date],
joins_list = [Join.Inner(users, users.id == orders.user_id)],
where = orders.amount > 100,
order_by = [orders.date]
)
Batch operations (single transaction)
(users.batch()
.insert({users.name: 'Eve', users.age: 28})
.update({users.age: 29}, where=users.name == 'Eve')
.run())
Schema management
from Ormophine import TableStructure
schema = TableStructure('products', strict=True)
schema.add_column('id', int, primary_key=True)
schema.add_column('title', str, not_null=True, unique=True)
schema.add_column('price', float, default_value=0.0)
products = db.create_table(schema)
# Add / rename / drop columns
products.add_column('stock', int, default_value=0, not_null=True)
products.rename_column(products.stock, 'inventory')
products.delete_column(products.inventory, True, True, True)
WAL mode and performance tuning
db.set_WAL_mode(True, wal_timer=60) # automatic checkpoint every 60 s
db.SetPragma.synchronous('NORMAL')
db.SetPragma.cache_size(-4000) # 4 MiB page cache
db.SetPragma.foreign_keys(True)
Operator Reference
Ormophine columns support native Python expressions — all values are automatically parameterized.
| Expression | SQL equivalent |
|---|---|
age > 18 |
age > 18 |
(age >= 18) & (age < 65) |
age >= 18 AND age < 65 |
status == 'active' |
status = 'active' |
name.startswith('A') |
name LIKE 'A%' |
email.contains('@corp.com') |
email LIKE '%@corp.com%' |
code[:3] |
SUBSTR(code, 1, 3) |
name.upper().strip() |
TRIM(UPPER(name)) |
price * qty - discount |
price * qty - discount |
Installation
🚧 PyPI release coming soon.
# Not yet available — star the repo to get notified
pip install ormophine
Roadmap
- SQLite backend with full ORM
- Operator overloading for columns
- Read-only connection pool
- WAL mode + automatic checkpointing
- Batch / bulk operations
- MySQL / MariaDB backend
- PostgreSQL backend
- Async support
- PyPI release
- Benchmark suite publication
Contributing
The codebase is currently in active development and not yet public. Once released, contributions, bug reports, and feature requests will be very welcome.
License
MIT — free to use, modify, and distribute.
1 maintainer
Release files for Ormophine 0.7.5
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ormophine-0.7.5.tar.gz | 569.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ormophine-0.7.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / ormophine-0.7.5.tar.gz
| Download URL | ormophine-0.7.5.tar.gz |
|---|---|
| Size | 569.6 kB |
| Tags | Source |
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| Uploaded via |
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|
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