feat: Implement Phase 3 neighbourhood data model

Add schemas, parsers, loaders, and models for Toronto neighbourhood-centric
data including census profiles, crime statistics, and amenities.

Schemas:
- NeighbourhoodRecord, CensusRecord, CrimeRecord, CrimeType
- AmenityType, AmenityRecord, AmenityCount

Models:
- BridgeCMHCNeighbourhood (zone-to-neighbourhood mapping with weights)
- FactCensus, FactCrime, FactAmenities

Parsers:
- TorontoOpenDataParser (CKAN API for neighbourhoods, census, amenities)
- TorontoPoliceParser (crime rates, MCI data)

Loaders:
- load_census_data, load_crime_data, load_amenities
- build_cmhc_neighbourhood_crosswalk (PostGIS area weights)

Also updates CLAUDE.md with projman plugin workflow documentation.

Closes #53, #54, #55, #56, #57, #58, #59

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

portfolio_app/toronto/loaders/amenities.py

@@ -0,0 +1,93 @@
+"""Loader for amenities data to fact_amenities table."""
+
+from collections import Counter
+
+from sqlalchemy.orm import Session
+
+from portfolio_app.toronto.models import FactAmenities
+from portfolio_app.toronto.schemas import AmenityCount, AmenityRecord
+
+from .base import get_session, upsert_by_key
+
+
+def load_amenities(
+    records: list[AmenityRecord],
+    year: int,
+    session: Session | None = None,
+) -> int:
+    """Load amenity records to fact_amenities table.
+
+    Aggregates individual amenity records into counts by neighbourhood
+    and amenity type before loading.
+
+    Args:
+        records: List of validated AmenityRecord schemas.
+        year: Year to associate with the amenity counts.
+        session: Optional existing session.
+
+    Returns:
+        Number of records loaded (inserted + updated).
+    """
+    # Aggregate records by neighbourhood and amenity type
+    counts: Counter[tuple[int, str]] = Counter()
+    for r in records:
+        key = (r.neighbourhood_id, r.amenity_type.value)
+        counts[key] += 1
+
+    # Convert to AmenityCount schemas then to models
+    def _load(sess: Session) -> int:
+        models = []
+        for (neighbourhood_id, amenity_type), count in counts.items():
+            model = FactAmenities(
+                neighbourhood_id=neighbourhood_id,
+                amenity_type=amenity_type,
+                count=count,
+                year=year,
+            )
+            models.append(model)
+
+        inserted, updated = upsert_by_key(
+            sess, FactAmenities, models, ["neighbourhood_id", "amenity_type", "year"]
+        )
+        return inserted + updated
+
+    if session:
+        return _load(session)
+    with get_session() as sess:
+        return _load(sess)
+
+
+def load_amenity_counts(
+    records: list[AmenityCount],
+    session: Session | None = None,
+) -> int:
+    """Load pre-aggregated amenity counts to fact_amenities table.
+
+    Args:
+        records: List of validated AmenityCount schemas.
+        session: Optional existing session.
+
+    Returns:
+        Number of records loaded (inserted + updated).
+    """
+
+    def _load(sess: Session) -> int:
+        models = []
+        for r in records:
+            model = FactAmenities(
+                neighbourhood_id=r.neighbourhood_id,
+                amenity_type=r.amenity_type.value,
+                count=r.count,
+                year=r.year,
+            )
+            models.append(model)
+
+        inserted, updated = upsert_by_key(
+            sess, FactAmenities, models, ["neighbourhood_id", "amenity_type", "year"]
+        )
+        return inserted + updated
+
+    if session:
+        return _load(session)
+    with get_session() as sess:
+        return _load(sess)