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Ferrum

A next-generation async ORM for Python. Rust-powered engine. Pydantic-native models. Django-inspired developer experience.

Ferrum is an async-first ORM designed for modern Python applications.

Built around a Rust-powered core and a Python-native API, Ferrum combines the ergonomics of Django's ORM, the type safety of Pydantic, and the performance of Rust.

Why Ferrum?

Existing Python ORMs often force developers to choose between:

  • Developer experience
  • Async support
  • Type safety
  • Performance

Ferrum aims to provide all four.

Goals

  • Native async from day one
  • Pydantic-first models
  • Django-inspired ORM experience
  • Rust-powered query engine
  • PostgreSQL-first architecture (MySQL, SQLite, and SQL Server via optional extras)
  • Type-safe query construction
  • Automatic migrations
  • High-performance result hydration
  • Production-ready observability

Quick Example

from ferrum import Model


class User(Model):
    id: int
    email: str
    is_active: bool = True


user = await User.objects.create(
    conn,
    email="john@example.com",
)

# Insert from an instance (sentinel PK is dropped so the DB default runs)
draft = User(id=0, email="dana@example.com")
created = await User.objects.create(conn, draft)

# Persist one instance's changes by primary key
created.is_active = False
await User.objects.update_instance(conn, created, fields=["is_active"])

users = await (
    User.objects
    .filter(is_active=True)
    .order_by("-id")
    .limit(10)
    .all(conn)
)

async with conn.transaction() as tx:
    user = await User.objects.create(tx, email="jane@example.com")
    await AuditLog.objects.create(tx, user_id=user.id, action="signup")

Features

Async First

No synchronous compatibility layer.

Ferrum is designed around modern async Python applications.

users = await User.objects.all(conn)

Pydantic Native

Models are built directly on top of Pydantic.

class User(Model):
    id: int
    email: str

No duplicate schema definitions.

Field Options

ferrum.Field() accepts column-level constraints that are carried through to DDL:

Parameter Type Description
db_default str | None DB-side DEFAULT expression (e.g. "NOW()", "''", "GEN_RANDOM_UUID()"). Token casing is normalised (now() → NOW()).
nullable bool | None Override annotation-derived nullability. Use nullable=False to force NOT NULL even on a T | None-annotated field.
db_index bool Emit a CREATE INDEX on this column (auto-named idx_{table}_{field}).
unique bool Emit a UNIQUE constraint.
db_column str | None Override the database column name.
primary_key bool Declare this field as the primary key.
uuid_generate "v4" | "v7" | None Set GEN_RANDOM_UUID() / UUIDV7() as the DB default for UUID PK columns.
max_length int | None Emit VARCHAR(n) instead of TEXT.
max_digits / decimal_places int | None Emit NUMERIC(p,s).
vector_dimensions int | None Required for Vector columns; emits VECTOR(n).
from datetime import datetime
from typing import Annotated
from ferrum import Model, Field

class Event(Model):
    id: int
    # DB-side timestamp default; Python annotation allows None but column is NOT NULL
    created_at: Annotated[datetime | None, Field(db_default="now()", nullable=False)]
    # Indexed text column
    kind: Annotated[str, Field(db_index=True, max_length=64)]

makemigrations honours these field attributes:

  • db_default / nullable are written into CREATE TABLE and ADD COLUMN DDL.
  • db_index=True emits CREATE INDEX after the table op.
  • For already-existing tables, makemigrations now autodiffs index and column attribute changes against the state projected from prior migration files:
    • Adding db_index=True to an existing field → AddIndex op.
    • Removing db_index=True → DropIndex op.
    • Adding or changing db_default → AlterColumn … SET DEFAULT … op.
    • Removing db_default → AlterColumn … DROP DEFAULT op.
    • Changing nullability → AlterColumn … SET / DROP NOT NULL op (SET NOT NULL is classified destructive and requires --confirm).
    • Column type changes, renames, and drops remain manual (out of scope for v0.1).

Django-Inspired API

Familiar query interface.

users = await (
    User.objects
    .filter(email__contains="@gmail.com")
    .order_by("-created_at")
    .all(conn)
)

First-Class IDE Support

Ferrum ships a PEP 561 py.typed marker, so editors and type checkers (mypy, pyright, ty) resolve its inline hints out of the box. Model.objects is typed as QuerySet[YourModel], chaining preserves the model type, and terminals infer precise results — no casts:

users: list[User] = await User.objects.filter(is_active=True).all(conn)   # list[User]
user: User | None = await User.objects.first(conn)                        # User | None
rows: list[dict[str, Any]] = await User.objects.values("id", "email").all(conn)
ids: list[Any] = await User.objects.values_list("id", flat=True).all(conn)

values() / values_list() return dedicated ValuesQuerySet, ValuesListQuerySet, and FlatValuesListQuerySet variants (all exported from ferrum) so all() returns list[dict[str, Any]], list[tuple[Any, ...]], or list[Any] respectively.

Rust-Powered Core

Performance-critical components are implemented in Rust:

  • Query compilation
  • SQL generation
  • Result decoding
  • Schema analysis
  • Migration planning

This allows Ferrum to maintain a Pythonic API without sacrificing performance.

Native full-text search across PostgreSQL, MySQL, SQLite FTS5, and SQL Server — one QuerySet API, dialect-specific SQL emit and migration DDL.

Query modes (filter lookups and ranking):

Mode Lookup operator Typical use
plain __match Natural-language terms
phrase __match_phrase Exact phrase
websearch __match_websearch Web-style quotes, - negation
boolean __match_boolean Boolean operators (&, |, !)

Convenience methods:

# Filter + relevance ranking in one call
hits = await Article.objects.search(
    "python async orm", field="body", mode="websearch"
).limit(10).all(conn)

# Rank without an implicit filter
ranked = await Article.objects.rank_by("body", "rust", mode="plain").all(conn)

Index declaration — PostgreSQL uses TSVector columns; other drivers index base text columns via Meta.full_text_indexes:

from ferrum.models import Field, FullTextIndex

class Article(Model):
    search_vector: Annotated[TSVector, Field(fts_config="english")] | None = None
    body: str = ""

    class Meta:
        full_text_indexes = [FullTextIndex(fields=("body",), config="english")]

Query strings are always bound parameters; fts_config and index names come from model-metadata allowlists only. See Getting Started → Vector and full-text columns and API Reference for per-dialect DDL and operator mapping.

Architecture

┌──────────────────────────┐
│      Python API          │
│  Models / QuerySets      │
└────────────┬─────────────┘
             │
             ▼
┌──────────────────────────┐
│      Ferrum Core         │
│      (Rust Engine)       │
├──────────────────────────┤
│ Query Compiler           │
│ SQL AST                  │
│ Result Decoder           │
│ Migration Planner        │
└────────────┬─────────────┘
             │
             ▼
┌──────────────────────────┐
│       PostgreSQL         │
└──────────────────────────┘

Roadmap

v0.1 (complete)

  • PostgreSQL support
  • Basic CRUD operations
  • Async query execution
  • Pydantic models
  • Query builder
  • Type-safe filters
  • Transactions and savepoints
  • Bulk operations (bulk_create, bulk_update, bulk_delete)
  • Migrations (schema diff, apply, revert, CLI)
  • Relationships (ForeignKey, OneToOne, ManyToMany)
  • pgvector KNN search and HNSW/IVFFLAT index DDL
  • Full-text search (cross-dialect: PostgreSQL, MySQL, SQLite FTS5, SQL Server)
  • Observability hooks (Tier A/B/C)
  • CLI (makemigrations, migrate, revert, showmigrations, inspectdb, resetdb)

v0.2 (in progress)

  • Upsert API (upsert, bulk_upsert with conflict targets and RETURNING)
  • Composite primary keys
  • Array field types (uuid[], text[], scalar arrays)
  • JSONB operators (__contains, __has_key)
  • RLS / tenant session helpers (set_config, tenant_session)
  • call_function for allowlisted stored-procedure calls
  • Migration ops for extensions, RLS policies, and function DDL
  • pgvector similarity score projection (vector_search helper)
  • Field(db_default=..., nullable=...) — first-class DB-side defaults and nullability override
  • makemigrations autodiff for index / default / nullability changes on existing tables
  • Query optimization (deferred fields, prefetch tuning)
  • Advanced relationship loading

v1.0

  • Production-ready stability
  • Performance benchmarking suite
  • Full documentation site

Project Status

Ferrum is currently in active development.

The API is not yet stable and breaking changes should be expected until the first public release.

Installation

# PostgreSQL (most common)
pip install 'ferrum-orm[pg]'

# PostgreSQL + migrations CLI
pip install 'ferrum-orm[pg,cli]'

# MySQL
pip install 'ferrum-orm[mysql]'

# SQLite + migrations CLI (testing / local dev)
pip install 'ferrum-orm[sqlite,cli]'

# SQL Server (also needs a system ODBC driver, e.g. msodbcsql18)
pip install 'ferrum-orm[mssql]'

# Optional MessagePack wire format for the Python<->Rust boundary
pip install 'ferrum-orm[msgpack]'

# Everything (all drivers + CLI + dotenv)
pip install 'ferrum-orm[all]'

# Core ORM only (no database driver — install a driver extra before connecting)
pip install ferrum-orm

Bare ferrum-orm installs Pydantic and the Rust core only. Choose a driver extra (pg, mysql, sqlite, or mssql) before calling ferrum.connect().

MySQL, SQLite, and SQL Server are thin-parity backends: they support core CRUD and migrations but not transactions, upsert, bulk_update, RLS, or pgvector (PostgreSQL only). SQL Server connects via aioodbc/pyodbc and requires a system ODBC driver such as msodbcsql18; DSNs use the mssql:// or sqlserver:// scheme.

Wire format (advanced)

The Python↔Rust IR/hydration boundary defaults to JSON. Installing the msgpack extra lets you switch it to MessagePack, selected via the FERRUM_WIRE_FORMAT environment variable (json | msgpack) or the [ferrum] wire_format key in ferrum.toml / pyproject.toml. JSON remains the default; MessagePack is opt-in.

From source, build the native extension with maturin develop (or mise run dev).

Examples

Runnable samples live under examples/:

Contributing

Contributions are welcome. Start with CONTRIBUTING.md for local setup, scoped verification, architecture rules, and pull request expectations.

License

Apache License 2.0

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0.1.17

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