feat: add Pydantic schemas, SQLAlchemy models, and parser structure

Sprint 3 implementation:
- Pydantic schemas for TRREB, CMHC, and dimension data validation
- SQLAlchemy models with PostGIS geometry for fact and dimension tables
- Parser structure (stubs) for TRREB PDF and CMHC CSV processing

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

portfolio_app/toronto/models/base.py

@@ -0,0 +1,30 @@
+"""SQLAlchemy base configuration and engine setup."""
+
+from sqlalchemy import Engine, create_engine
+from sqlalchemy.orm import DeclarativeBase, Session, sessionmaker
+
+from portfolio_app.config import get_settings
+
+
+class Base(DeclarativeBase):  # type: ignore[misc]
+    """Base class for all SQLAlchemy models."""
+
+    pass
+
+
+def get_engine() -> Engine:
+    """Create database engine from settings."""
+    settings = get_settings()
+    return create_engine(settings.database_url, echo=False)
+
+
+def get_session_factory() -> sessionmaker[Session]:
+    """Create session factory."""
+    engine = get_engine()
+    return sessionmaker(bind=engine)
+
+
+def create_tables() -> None:
+    """Create all tables in database."""
+    engine = get_engine()
+    Base.metadata.create_all(engine)