-- pSEO article data: per-country padel market overview.
-- One row per country — consumed by the country-overview.md.jinja template.
-- Aggregates city-level data from pseo_city_costs_de.
--
-- top_city_slugs / top_city_names are ordered lists (up to 5) used to generate
-- internal links from the country hub to its top city pages.

MODEL (
  name serving.pseo_country_overview,
  kind FULL,
  cron '@daily',
  grain country_slug
);

SELECT
  country_code,
  country_name_en,
  country_slug,
  COUNT(*)                                                        AS city_count,
  SUM(padel_venue_count)                                         AS total_venues,
  -- Population-weighted: large cities (Madrid, Barcelona) dominate, not hundreds of small towns
  ROUND(SUM(market_score * population) / NULLIF(SUM(population), 0), 1) AS avg_market_score,
  MAX(market_score)                                              AS top_city_market_score,
  -- Top 5 cities by venue count (prominence), then score for internal linking
  LIST(city_slug ORDER BY padel_venue_count DESC, market_score DESC NULLS LAST)[1:5]     AS top_city_slugs,
  LIST(city_name ORDER BY padel_venue_count DESC, market_score DESC NULLS LAST)[1:5]     AS top_city_names,
  -- Opportunity score aggregates (population-weighted: saturated megacities dominate, not hundreds of small towns)
  ROUND(SUM(opportunity_score * population) / NULLIF(SUM(population), 0), 1) AS avg_opportunity_score,
  MAX(opportunity_score)                                         AS top_opportunity_score,
  -- Top 5 opportunity cities by population (prominence), then opportunity score
  LIST(city_slug ORDER BY population DESC, opportunity_score DESC NULLS LAST)[1:5] AS top_opportunity_slugs,
  LIST(city_name ORDER BY population DESC, opportunity_score DESC NULLS LAST)[1:5] AS top_opportunity_names,
  -- Pricing medians across cities (NULL when no Playtomic coverage in country)
  ROUND(MEDIAN(median_hourly_rate), 0)                           AS median_hourly_rate,
  ROUND(MEDIAN(median_peak_rate), 0)                             AS median_peak_rate,
  ROUND(MEDIAN(median_offpeak_rate), 0)                          AS median_offpeak_rate,
  -- Use the most common currency in the country (MIN is deterministic for single-currency countries)
  MIN(price_currency)                                            AS price_currency,
  SUM(population)                                                AS total_population,
  ROUND(SUM(lat * population) / NULLIF(SUM(population), 0), 4)  AS lat,
  ROUND(SUM(lon * population) / NULLIF(SUM(population), 0), 4)  AS lon,
  CURRENT_DATE                                                   AS refreshed_date
FROM serving.pseo_city_costs_de
GROUP BY country_code, country_name_en, country_slug
-- Only countries with enough cities to be worth a hub page
HAVING COUNT(*) >= 2
