refactor(transform): conform geographic dimension hierarchy via city_slug

Propagates the conformed city key (city_slug) from dim_venues through the
full pricing pipeline, eliminating 3 fragile LOWER(TRIM(...)) fuzzy string
joins with deterministic key joins.

Changes (cascading, task-by-task):
- dim_venues: add city_slug computed column (REGEXP_REPLACE slug derivation)
- dim_venue_capacity: join foundation.dim_venues instead of stg_playtomic_venues;
  carry city_slug alongside country_code/city
- fct_daily_availability: carry city_slug from dim_venue_capacity
- venue_pricing_benchmarks: carry city_slug from fct_daily_availability;
  add to venue_stats GROUP BY and final SELECT/GROUP BY
- city_market_profile: join vpb on city_slug = city_slug (was LOWER(TRIM))
- planner_defaults: add city_slug to city_benchmarks CTE; join on city_slug
- pseo_city_pricing: join city_market_profile on city_slug (was LOWER(TRIM))
- pipeline_routes._DAG: dim_venue_capacity now depends on dim_venues, not stg_playtomic_venues

Result: dim_venues.city_slug → dim_cities.(country_code, city_slug) forms a
fully conformed geographic hierarchy with no fuzzy string comparisons.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

transform/sqlmesh_padelnomics/models/serving/venue_pricing_benchmarks.sql

@@ -17,6 +17,7 @@ WITH venue_stats AS (
     da.tenant_id,
     da.country_code,
     da.city,
+    da.city_slug,
     da.price_currency,
     AVG(da.occupancy_rate)                              AS avg_occupancy_rate,
     MEDIAN(da.median_price)                             AS median_hourly_rate,
@@ -29,12 +30,13 @@ WITH venue_stats AS (
   WHERE TRY_CAST(da.snapshot_date AS DATE) >= CURRENT_DATE - INTERVAL '30 days'
     AND da.occupancy_rate IS NOT NULL
     AND da.occupancy_rate BETWEEN 0 AND 1.5
-  GROUP BY da.tenant_id, da.country_code, da.city, da.price_currency
+  GROUP BY da.tenant_id, da.country_code, da.city, da.city_slug, da.price_currency
   HAVING COUNT(DISTINCT da.snapshot_date) >= 3
 )
 SELECT
   country_code,
   city,
+  city_slug,
   price_currency,
   COUNT(*)                                              AS venue_count,
   -- Pricing benchmarks
@@ -54,4 +56,4 @@ SELECT
   SUM(days_observed)                                    AS total_venue_days_observed,
   CURRENT_DATE                                          AS refreshed_date
 FROM venue_stats
-GROUP BY country_code, city, price_currency
+GROUP BY country_code, city, city_slug, price_currency