# SQLAlchemy-PGView **A SQLAlchemy 2.0+ extension that provides first-class support for PostgreSQL views and materialized views.** [](https://github.com/astral-sh/ty) [](https://github.com/astral-sh/uv) [](https://github.com/astral-sh/ruff) [](https://www.python.org/downloads/) [](https://www.sqlalchemy.org/) [](https://opensource.org/licenses/MIT) --- ## Features - **Declarative Views** - Class-based view definitions using multiple inheritance with SQLAlchemy ORM - **View & MaterializedView Classes** - Define PostgreSQL views as Python objects with full DDL support - **Alembic Integration** - Database migration operations (`op.create_view()`, `op.drop_view()`, etc.) - **Auto-Refresh** - Automatically refresh materialized views on data changes - **Async Support** - Works with asyncpg and SQLAlchemy's async engines - **Dependency Tracking** - Query PostgreSQL system catalogs for view dependencies - **Type Safety** - Full type annotations for modern Python development ## Requirements - Python 3.10+ - SQLAlchemy 2.0+ - PostgreSQL 12+ - Alembic 1.10+ (optional, for migrations) ## Installation === "Base package" ```bash uv pip install "sqlalchemy-pgview" ``` === "With alembic support" ```bash uv pip install "sqlalchemy-pgview[alembic]" ``` ## Quick Start The recommended way to define views is using the **declarative pattern** with multiple inheritance. This integrates seamlessly with SQLAlchemy ORM models. ### Define Your Models and Views ```python from decimal import Decimal from sqlalchemy import create_engine, select, func, String, Numeric, Integer from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, Session from sqlalchemy_pgview import ViewBase, MaterializedViewBase # Define your base and models class Base(DeclarativeBase): pass class User(Base): __tablename__ = "users" id: Mapped[int] = mapped_column(primary_key=True) name: Mapped[str] = mapped_column(String(100)) is_active: Mapped[bool] = mapped_column(default=True) class Order(Base): __tablename__ = "orders" id: Mapped[int] = mapped_column(primary_key=True) user_id: Mapped[int] = mapped_column(Integer) total: Mapped[Decimal] = mapped_column(Numeric(10, 2)) # Define a regular view (computed on every query) class ActiveUsers(ViewBase, Base): __tablename__ = "active_users" __select__ = select(User.id, User.name).where(User.is_active == True) # Define a materialized view (cached results, needs refresh) class UserStats(MaterializedViewBase, Base): __tablename__ = "user_stats" __select__ = select( User.id.label("user_id"), User.name, func.count(Order.id).label("order_count"), func.coalesce(func.sum(Order.total), 0).label("total_spent"), ).select_from(User.__table__.outerjoin(Order.__table__, User.id == Order.user_id) ).group_by(User.id, User.name) # Create everything (tables + views) engine = create_engine("postgresql://user:pass@localhost/mydb") Base.metadata.create_all(engine) ``` ### Query Views ```python from sqlalchemy import select with engine.connect() as conn: # Query regular view (always shows current data) result = conn.execute(select(ActiveUsers.as_table())).fetchall() for row in result: print(f"{row.name}") # Query materialized view (shows cached data) stats = conn.execute(select(UserStats.as_table())).fetchall() for stat in stats: print(f"{stat.name}: {stat.order_count} orders, ${stat.total_spent}") ``` ### Refresh Materialized Views Materialized views store cached results - refresh them when data changes: ```python with engine.begin() as conn: UserStats.refresh(conn) # Concurrent refresh (allows reads during refresh, requires unique index) UserStats.refresh(conn, concurrently=True) ``` ### Auto-Refresh on Data Changes Automatically refresh materialized views when underlying data changes: ```python from sqlalchemy.orm import Session # Enable auto-refresh when Order table changes UserStats.auto_refresh_on(Session, Order.__table__) # Now commits automatically refresh the materialized view with Session(engine) as session: session.add(Order(user_id=1, total=Decimal("100.00"))) session.commit() # UserStats is automatically refreshed ``` ## Next Steps