Files
padelnomics/transform/sqlmesh_padelnomics/models/serving/pseo_country_overview.sql
Deeman a00c8727d7 fix(content): slugify transliteration + article links + country overview ranking
- Add @slugify SQLMesh macro (STRIP_ACCENTS + ß→ss) replacing broken
  inline REGEXP_REPLACE that dropped non-ASCII chars (Düsseldorf → d-sseldorf)
- Apply @slugify to dim_venues, dim_cities, dim_locations
- Fix Python slugify() to pre-replace ß→ss before NFKD normalization
- Add language prefix to B2B article market links (/markets/germany → /de/markets/germany)
- Change country overview top-5 ranking: venue count (not raw market_score)
  for top cities, population for top opportunity cities

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-03 10:46:30 +01:00

44 lines
2.5 KiB
SQL

-- 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,
ROUND(AVG(market_score), 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 (NULL-safe: cities without geoname_id match excluded from AVG)
ROUND(AVG(opportunity_score), 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,
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