feat: add loaders and dbt models for Toronto housing data

Sprint 4 implementation:

Loaders:
- base.py: Session management, bulk insert, upsert utilities
- dimensions.py: Load time, district, zone, neighbourhood, policy dimensions
- trreb.py: Load TRREB purchase data to fact_purchases
- cmhc.py: Load CMHC rental data to fact_rentals

dbt Project:
- Project configuration (dbt_project.yml, packages.yml)
- Staging models for all fact and dimension tables
- Intermediate models with dimension enrichment
- Marts: purchase analysis, rental analysis, market summary

Closes #16

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

dbt/models/intermediate/int_purchases__monthly.sql

@@ -0,0 +1,62 @@
+-- Intermediate: Monthly purchase data enriched with dimensions
+-- Joins purchases with time and district dimensions for analysis
+
+with purchases as (
+    select * from {{ ref('stg_trreb__purchases') }}
+),
+
+time_dim as (
+    select * from {{ ref('stg_dimensions__time') }}
+),
+
+district_dim as (
+    select * from {{ ref('stg_dimensions__trreb_districts') }}
+),
+
+enriched as (
+    select
+        p.purchase_id,
+
+        -- Time attributes
+        t.date_key,
+        t.full_date,
+        t.year,
+        t.month,
+        t.quarter,
+        t.month_name,
+
+        -- District attributes
+        d.district_key,
+        d.district_code,
+        d.district_name,
+        d.area_type,
+
+        -- Metrics
+        p.sales_count,
+        p.dollar_volume,
+        p.avg_price,
+        p.median_price,
+        p.new_listings,
+        p.active_listings,
+        p.days_on_market,
+        p.sale_to_list_ratio,
+
+        -- Calculated metrics
+        case
+            when p.active_listings > 0
+            then round(p.sales_count::numeric / p.active_listings, 3)
+            else null
+        end as absorption_rate,
+
+        case
+            when p.sales_count > 0
+            then round(p.active_listings::numeric / p.sales_count, 1)
+            else null
+        end as months_of_inventory
+
+    from purchases p
+    inner join time_dim t on p.date_key = t.date_key
+    inner join district_dim d on p.district_key = d.district_key
+)
+
+select * from enriched