merge: pipeline diagnostic script + extraction card UX improvements

CHANGELOG.md

@@ -7,6 +7,10 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 ## [Unreleased]
 
 ### Added
+- **Pipeline diagnostic script** (`scripts/check_pipeline.py`) — read-only script that reports row counts at every layer of the pricing pipeline (staging → foundation → serving), date range analysis, HAVING filter impact, and join coverage. Run on prod to diagnose empty serving tables.
+- **Extraction card descriptions** — each workflow card on the admin pipeline page now shows a one-line description explaining what the data source is (e.g. "EU geographic boundaries (NUTS2 polygons) from Eurostat GISCO"). Descriptions defined in `workflows.toml`.
+- **Running state indicator** — extraction cards show a spinner + "Running" label with a blue-tinted border when an extraction is actively running, replacing the plain Run button. Cards also display the start time with "running..." text.
+
 - **Interactive Leaflet maps** — geographic visualization across 4 key placements using self-hosted Leaflet 1.9.4 (GDPR-safe, no CDN):
   - **Markets hub** (`/markets`): country bubble map with circles sized by total venues, colored by avg market score (green ≥ 60, amber 30-60, red < 30). Click navigates to country overview.
   - **Country overview articles**: city bubble map loads after article render, auto-fits bounds, click navigates to city page. Bubbles colored by market score.

infra/supervisor/workflows.toml

@@ -8,54 +8,67 @@
 #   entry    — optional: function name if not "main" (default: "main")
 #   depends_on — optional: list of workflow names that must run first
 #   proxy_mode — optional: "round-robin" (default) or "sticky"
+#   description — optional: human-readable one-liner shown in the admin UI
 
 [overpass]
 module = "padelnomics_extract.overpass"
 schedule = "monthly"
+description = "Padel court locations from OpenStreetMap via Overpass API"
 
 [overpass_tennis]
 module = "padelnomics_extract.overpass_tennis"
 schedule = "monthly"
+description = "Tennis court locations from OpenStreetMap via Overpass API"
 
 [eurostat]
 module = "padelnomics_extract.eurostat"
 schedule = "monthly"
+description = "City population data from Eurostat Urban Audit"
 
 [geonames]
 module = "padelnomics_extract.geonames"
 schedule = "monthly"
+description = "Global city/town gazetteer from GeoNames (pop >= 1K)"
 
 [playtomic_tenants]
 module = "padelnomics_extract.playtomic_tenants"
 schedule = "daily"
+description = "Padel venue directory from Playtomic (names, locations, courts)"
 
 [playtomic_availability]
 module = "padelnomics_extract.playtomic_availability"
 schedule = "daily"
 depends_on = ["playtomic_tenants"]
+description = "Morning availability snapshots — slot-level pricing per venue"
 
 [playtomic_recheck]
 module = "padelnomics_extract.playtomic_availability"
 entry = "main_recheck"
 schedule = "0,30 6-23 * * *"
 depends_on = ["playtomic_availability"]
+description = "Intraday availability rechecks for occupancy tracking"
 
 [census_usa]
 module = "padelnomics_extract.census_usa"
 schedule = "monthly"
+description = "US city/place population from Census Bureau ACS"
 
 [census_usa_income]
 module = "padelnomics_extract.census_usa_income"
 schedule = "monthly"
+description = "US county median household income from Census Bureau ACS"
 
 [eurostat_city_labels]
 module = "padelnomics_extract.eurostat_city_labels"
 schedule = "monthly"
+description = "City code-to-name mapping for Eurostat Urban Audit cities"
 
 [ons_uk]
 module = "padelnomics_extract.ons_uk"
 schedule = "monthly"
+description = "UK local authority population estimates from ONS"
 
 [gisco]
 module = "padelnomics_extract.gisco"
 schedule = "monthly"
+description = "EU geographic boundaries (NUTS2 polygons) from Eurostat GISCO"

scripts/check_pipeline.py

@@ -0,0 +1,200 @@
+"""
+Diagnostic script: check row counts at every layer of the pricing pipeline.
+
+Run on prod via SSH:
+    DUCKDB_PATH=/opt/padelnomics/data/lakehouse.duckdb uv run python scripts/check_pipeline.py
+
+Or locally:
+    DUCKDB_PATH=data/lakehouse.duckdb uv run python scripts/check_pipeline.py
+
+Read-only — never writes to the database.
+"""
+
+import os
+import sys
+
+import duckdb
+
+DUCKDB_PATH = os.environ.get("DUCKDB_PATH", "data/lakehouse.duckdb")
+
+PIPELINE_TABLES = [
+    ("staging", "stg_playtomic_availability"),
+    ("foundation", "fct_availability_slot"),
+    ("foundation", "dim_venue_capacity"),
+    ("foundation", "fct_daily_availability"),
+    ("serving", "venue_pricing_benchmarks"),
+    ("serving", "pseo_city_pricing"),
+]
+
+
+def main():
+    if not os.path.exists(DUCKDB_PATH):
+        print(f"ERROR: {DUCKDB_PATH} not found")
+        sys.exit(1)
+
+    con = duckdb.connect(DUCKDB_PATH, read_only=True)
+
+    print(f"Database: {DUCKDB_PATH}")
+    print(f"DuckDB version: {con.execute('SELECT version()').fetchone()[0]}")
+    print()
+
+    # ── Row counts at each layer ──────────────────────────────────────────
+    print("=" * 60)
+    print("PIPELINE ROW COUNTS")
+    print("=" * 60)
+
+    for schema, table in PIPELINE_TABLES:
+        # SQLMesh may use __<env> suffixed physical tables
+        # Try the logical name first, then scan for physical tables
+        candidates = [f"{schema}.{table}"]
+        try:
+            phys = con.execute(
+                f"SELECT table_schema || '.' || table_name "
+                f"FROM information_schema.tables "
+                f"WHERE table_name LIKE '{table}%' "
+                f"ORDER BY table_name"
+            ).fetchall()
+            for (name,) in phys:
+                if name not in candidates:
+                    candidates.append(name)
+        except Exception:
+            pass
+
+        for fqn in candidates:
+            try:
+                (count,) = con.execute(f"SELECT COUNT(*) FROM {fqn}").fetchone()
+                print(f"  {fqn:50s} {count:>10,} rows")
+            except Exception as e:
+                print(f"  {fqn:50s} ERROR: {e}")
+
+    # ── Date range in fct_daily_availability ──────────────────────────────
+    print()
+    print("=" * 60)
+    print("DATE RANGE: fct_daily_availability")
+    print("=" * 60)
+
+    try:
+        row = con.execute("""
+            SELECT
+                MIN(snapshot_date) AS min_date,
+                MAX(snapshot_date) AS max_date,
+                COUNT(DISTINCT snapshot_date) AS distinct_days,
+                CURRENT_DATE AS today,
+                CURRENT_DATE - INTERVAL '30 days' AS window_start
+            FROM foundation.fct_daily_availability
+        """).fetchone()
+        if row:
+            min_date, max_date, days, today, window_start = row
+            print(f"  Min snapshot_date:   {min_date}")
+            print(f"  Max snapshot_date:   {max_date}")
+            print(f"  Distinct days:       {days}")
+            print(f"  Today:               {today}")
+            print(f"  30-day window start: {window_start}")
+            if max_date and str(max_date) < str(window_start):
+                print()
+                print("  *** ALL DATA IS OUTSIDE THE 30-DAY WINDOW ***")
+                print("  This is why venue_pricing_benchmarks is empty.")
+    except Exception as e:
+        print(f"  ERROR: {e}")
+
+    # ── HAVING filter impact in venue_pricing_benchmarks ──────────────────
+    print()
+    print("=" * 60)
+    print("HAVING FILTER IMPACT (venue_pricing_benchmarks)")
+    print("=" * 60)
+
+    try:
+        row = con.execute("""
+            WITH venue_stats AS (
+                SELECT
+                    da.tenant_id,
+                    da.country_code,
+                    da.city,
+                    COUNT(DISTINCT da.snapshot_date) AS days_observed
+                FROM foundation.fct_daily_availability da
+                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
+            )
+            SELECT
+                COUNT(*) AS total_venues,
+                COUNT(*) FILTER (WHERE days_observed >= 3) AS venues_passing_having,
+                COUNT(*) FILTER (WHERE days_observed < 3) AS venues_failing_having,
+                MAX(days_observed) AS max_days,
+                MIN(days_observed) AS min_days
+            FROM venue_stats
+        """).fetchone()
+        if row:
+            total, passing, failing, max_d, min_d = row
+            print(f"  Venues in 30-day window:          {total}")
+            print(f"  Venues with >= 3 days (PASSING):  {passing}")
+            print(f"  Venues with < 3 days (FILTERED):  {failing}")
+            print(f"  Max days observed:                {max_d}")
+            print(f"  Min days observed:                {min_d}")
+            if total == 0:
+                print()
+                print("  *** NO VENUES IN 30-DAY WINDOW — check fct_daily_availability dates ***")
+    except Exception as e:
+        print(f"  ERROR: {e}")
+
+    # ── Occupancy rate distribution ───────────────────────────────────────
+    print()
+    print("=" * 60)
+    print("OCCUPANCY RATE DISTRIBUTION (fct_daily_availability)")
+    print("=" * 60)
+
+    try:
+        rows = con.execute("""
+            SELECT
+                CASE
+                    WHEN occupancy_rate IS NULL THEN 'NULL'
+                    WHEN occupancy_rate < 0 THEN '< 0 (invalid)'
+                    WHEN occupancy_rate > 1.5 THEN '> 1.5 (filtered)'
+                    WHEN occupancy_rate <= 0.25 THEN '0 – 0.25'
+                    WHEN occupancy_rate <= 0.50 THEN '0.25 – 0.50'
+                    WHEN occupancy_rate <= 0.75 THEN '0.50 – 0.75'
+                    ELSE '0.75 – 1.0+'
+                END AS bucket,
+                COUNT(*) AS cnt
+            FROM foundation.fct_daily_availability
+            GROUP BY 1
+            ORDER BY 1
+        """).fetchall()
+        for bucket, cnt in rows:
+            print(f"  {bucket:25s} {cnt:>10,}")
+    except Exception as e:
+        print(f"  ERROR: {e}")
+
+    # ── dim_venue_capacity join coverage ──────────────────────────────────
+    print()
+    print("=" * 60)
+    print("JOIN COVERAGE: fct_availability_slot → dim_venue_capacity")
+    print("=" * 60)
+
+    try:
+        row = con.execute("""
+            SELECT
+                COUNT(DISTINCT a.tenant_id) AS slot_tenants,
+                COUNT(DISTINCT c.tenant_id) AS capacity_tenants,
+                COUNT(DISTINCT a.tenant_id) - COUNT(DISTINCT c.tenant_id) AS missing_capacity
+            FROM foundation.fct_availability_slot a
+            LEFT JOIN foundation.dim_venue_capacity c ON a.tenant_id = c.tenant_id
+        """).fetchone()
+        if row:
+            slot_t, cap_t, missing = row
+            print(f"  Tenants in fct_availability_slot: {slot_t}")
+            print(f"  Tenants with capacity match:      {cap_t}")
+            print(f"  Tenants missing capacity:         {missing}")
+            if missing and missing > 0:
+                print(f"  *** {missing} tenants dropped by INNER JOIN to dim_venue_capacity ***")
+    except Exception as e:
+        print(f"  ERROR: {e}")
+
+    con.close()
+    print()
+    print("Done.")
+
+
+if __name__ == "__main__":
+    main()

web/src/padelnomics/admin/pipeline_routes.py

@@ -540,6 +540,7 @@ def _load_workflows() -> list[dict]:
             "schedule": schedule,
             "schedule_label": schedule_label,
             "depends_on": config.get("depends_on", []),
+            "description": config.get("description", ""),
         })
     return workflows
 

web/src/padelnomics/admin/templates/admin/partials/pipeline_overview.html

@@ -16,8 +16,9 @@
     {% set wf = row.workflow %}
     {% set run = row.run %}
     {% set stale = row.stale %}
-    <div style="border:1px solid #E2E8F0;border-radius:10px;padding:0.875rem;background:#FAFAFA">
-      <div class="flex items-center gap-2 mb-2">
+    {% set is_running = run and run.status == 'running' and not stale %}
+    <div style="border:1px solid {% if is_running %}#93C5FD{% else %}#E2E8F0{% endif %};border-radius:10px;padding:0.875rem;background:{% if is_running %}#EFF6FF{% else %}#FAFAFA{% endif %}">
+      <div class="flex items-center gap-2 mb-1">
         {% if not run %}
           <span class="status-dot pending"></span>
         {% elif stale %}
@@ -33,6 +34,15 @@
         {% if stale %}
         <span class="badge-warning" style="font-size:10px;padding:1px 6px;margin-left:auto">stale</span>
         {% endif %}
+        {% if is_running %}
+        <span class="btn btn-sm ml-auto"
+              style="padding:2px 8px;font-size:11px;opacity:0.6;cursor:default;pointer-events:none">
+          <svg class="spinner-icon" width="12" height="12" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="3">
+            <path d="M12 2a10 10 0 0 1 10 10" stroke-linecap="round"/>
+          </svg>
+          Running
+        </span>
+        {% else %}
         <button type="button"
                 class="btn btn-sm ml-auto"
                 style="padding:2px 8px;font-size:11px"
@@ -41,9 +51,17 @@
                 hx-swap="outerHTML"
                 hx-vals='{"extractor": "{{ wf.name }}", "csrf_token": "{{ csrf_token() }}"}'
                 hx-confirm="Run {{ wf.name }} extractor?">Run</button>
+        {% endif %}
       </div>
+      {% if wf.description %}
+      <p class="text-xs text-slate" style="margin-top:2px;margin-bottom:4px">{{ wf.description }}</p>
+      {% endif %}
       <p class="text-xs text-slate">{{ wf.schedule_label }}</p>
-      {% if run %}
+      {% if is_running %}
+        <p class="text-xs mt-1" style="color:#2563EB">
+          Started {{ run.started_at[:16].replace('T', ' ') if run.started_at else '—' }} — running...
+        </p>
+      {% elif run %}
         <p class="text-xs mono text-slate-dark mt-1">{{ run.started_at[:16].replace('T', ' ') if run.started_at else '—' }}</p>
         {% if run.status == 'failed' and run.error_message %}
         <p class="text-xs text-danger mt-1" style="font-family:monospace;word-break:break-all">