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/pseo_city_pricing.sql

@@ -41,6 +41,6 @@ FROM serving.venue_pricing_benchmarks vpb
 -- Join city_market_profile to get the canonical city_slug and country metadata
 INNER JOIN serving.city_market_profile c
   ON  vpb.country_code = c.country_code
-  AND LOWER(TRIM(vpb.city)) = LOWER(TRIM(c.city_name))
+  AND vpb.city_slug = c.city_slug
 -- Only cities with enough venues for meaningful pricing statistics
 WHERE vpb.venue_count >= 2