refactor: Delete legacy TRREB Python modules (#47)

- Delete portfolio_app/toronto/schemas/trreb.py
- Delete portfolio_app/toronto/parsers/trreb.py
- Delete portfolio_app/toronto/loaders/trreb.py
- Remove TRREB imports from __init__.py files

Part of Sprint 9: Toronto Neighbourhood Dashboard transition
See docs/changes/Change-Toronto-Analysis-Reviewed.md

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

portfolio_app/toronto/loaders/__init__.py

@@ -10,7 +10,6 @@ from .dimensions import (
     load_time_dimension,
     load_trreb_districts,
 )
-from .trreb import load_trreb_purchases, load_trreb_record
 
 __all__ = [
     # Base utilities
@@ -25,8 +24,6 @@ __all__ = [
     "load_neighbourhoods",
     "load_policy_events",
     # Fact loaders
-    "load_trreb_purchases",
-    "load_trreb_record",
     "load_cmhc_rentals",
     "load_cmhc_record",
 ]

portfolio_app/toronto/loaders/trreb.py

@@ -1,129 +0,0 @@
-"""Loader for TRREB purchase data into fact_purchases."""
-
-from sqlalchemy.orm import Session
-
-from portfolio_app.toronto.models import DimTime, DimTRREBDistrict, FactPurchases
-from portfolio_app.toronto.schemas import TRREBMonthlyRecord, TRREBMonthlyReport
-
-from .base import get_session, upsert_by_key
-from .dimensions import generate_date_key
-
-
-def load_trreb_purchases(
-    report: TRREBMonthlyReport,
-    session: Session | None = None,
-) -> int:
-    """Load TRREB monthly report data into fact_purchases.
-
-    Args:
-        report: Validated TRREB monthly report containing records.
-        session: Optional existing session.
-
-    Returns:
-        Number of records loaded.
-    """
-
-    def _load(sess: Session) -> int:
-        # Get district key mapping
-        districts = sess.query(DimTRREBDistrict).all()
-        district_map = {d.district_code: d.district_key for d in districts}
-
-        # Build date key from report date
-        date_key = generate_date_key(report.report_date)
-
-        # Verify time dimension exists
-        time_dim = sess.query(DimTime).filter_by(date_key=date_key).first()
-        if not time_dim:
-            raise ValueError(
-                f"Time dimension not found for date_key {date_key}. "
-                "Load time dimension first."
-            )
-
-        records = []
-        for record in report.records:
-            district_key = district_map.get(record.area_code)
-            if not district_key:
-                # Skip records for unknown districts (e.g., aggregate rows)
-                continue
-
-            fact = FactPurchases(
-                date_key=date_key,
-                district_key=district_key,
-                sales_count=record.sales,
-                dollar_volume=record.dollar_volume,
-                avg_price=record.avg_price,
-                median_price=record.median_price,
-                new_listings=record.new_listings,
-                active_listings=record.active_listings,
-                avg_dom=record.avg_dom,
-                avg_sp_lp=record.avg_sp_lp,
-            )
-            records.append(fact)
-
-        inserted, updated = upsert_by_key(
-            sess, FactPurchases, records, ["date_key", "district_key"]
-        )
-        return inserted + updated
-
-    if session:
-        return _load(session)
-    with get_session() as sess:
-        return _load(sess)
-
-
-def load_trreb_record(
-    record: TRREBMonthlyRecord,
-    session: Session | None = None,
-) -> int:
-    """Load a single TRREB record into fact_purchases.
-
-    Args:
-        record: Single validated TRREB monthly record.
-        session: Optional existing session.
-
-    Returns:
-        Number of records loaded (0 or 1).
-    """
-
-    def _load(sess: Session) -> int:
-        # Get district key
-        district = (
-            sess.query(DimTRREBDistrict)
-            .filter_by(district_code=record.area_code)
-            .first()
-        )
-        if not district:
-            return 0
-
-        date_key = generate_date_key(record.report_date)
-
-        # Verify time dimension exists
-        time_dim = sess.query(DimTime).filter_by(date_key=date_key).first()
-        if not time_dim:
-            raise ValueError(
-                f"Time dimension not found for date_key {date_key}. "
-                "Load time dimension first."
-            )
-
-        fact = FactPurchases(
-            date_key=date_key,
-            district_key=district.district_key,
-            sales_count=record.sales,
-            dollar_volume=record.dollar_volume,
-            avg_price=record.avg_price,
-            median_price=record.median_price,
-            new_listings=record.new_listings,
-            active_listings=record.active_listings,
-            avg_dom=record.avg_dom,
-            avg_sp_lp=record.avg_sp_lp,
-        )
-
-        inserted, updated = upsert_by_key(
-            sess, FactPurchases, [fact], ["date_key", "district_key"]
-        )
-        return inserted + updated
-
-    if session:
-        return _load(session)
-    with get_session() as sess:
-        return _load(sess)