fix(planner): prevent chart containers from overflowing on small screens

Grid children default to min-width:auto, letting the Chart.js canvas
push the container wider than its grid track. Adding min-width:0 and
overflow:hidden constrains charts to their column width.

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

.env.prod.sops

@@ -3,6 +3,7 @@ APP_NAME=ENC[AES256_GCM,data:ldJf4P0iD9ziMVg=,iv:hiVl2whhd02yZCafzBfbxX5/EU/suvz
 SECRET_KEY=ENC[AES256_GCM,data:hmlXm7NKVVFmeea4DnlrH/oSnsoaMAkUz42oWwFXOXL1XwAh3iemIKHUQOV2G4SPlmjfmEVQD64xbxaJW0OcPQ/8KqhrRYDsy0F/u0h7nmNQdwJrcvzcmbvjgcwU5IITPIr23d/W5PeSJzxhB93uaJ0+zFN2CyHfeewrJKafPfw=,iv:e+ZSLUO+dlt+ET8r/0/pf74UtGIBMkaVoJMWlJn1W5U=,tag:LdDCCrHcJnKLkKL/cY/R/Q==,type:str]
 BASE_URL=ENC[AES256_GCM,data:50k/RqlZ1EHqGM4UkSmTaCsuJgyU4w==,iv:f8zKr2jkts4RsawA97hzICHwj9Quzgp+Dw8AhQ7GSWA=,tag:9KhNvwmoOtDyuIql7okeew==,type:str]
 DEBUG=ENC[AES256_GCM,data:O0/uRF4=,iv:cZ+vyUuXjQOYYRf4l8lWS3JIWqL/w3pnlCTDPAZpB1E=,tag:OmJE9oJpzYzth0xwaMqADQ==,type:str]
+LANDING_DIR=ENC[AES256_GCM,data:rn8u+tGob0vU7kSAtxmrpYQlneesvyO10A==,iv:PuGtdcQBdRbnybulzd6L7JVQClcK3/QjMeYFXZSxGW0=,tag:K2PJPMCWXdqTlQpwP9+DOQ==,type:str]
 #ENC[AES256_GCM,data:xmJc6WTb3yumHzvLeA==,iv:9jKuYaDgm4zR/DTswIMwsajV0s5UTe+AOX4Sue0GPCs=,tag:b/7H9js1HmFYjuQE4zJz8w==,type:comment]
 ADMIN_EMAILS=ENC[AES256_GCM,data:R/2YTk8KDEpNQ71RN8Fm6miLZvXNJQ==,iv:kzmiaBK7KvnSjR5gx6lp7zEMzs5xRul6LBhmLf48bCU=,tag:csVZ0W1TxBAoJacQurW9VQ==,type:str]
 #ENC[AES256_GCM,data:S7Pdg9tcom3N,iv:OjmYk3pqbZHKPS1Y06w1y8BE7CU0y6Vx2wnio9tEhus=,tag:YAOGbrHQ+UOcdSQFWdiCDA==,type:comment]
@@ -63,7 +64,7 @@ sops_age__list_1__map_enc=-----BEGIN AGE ENCRYPTED FILE-----\nYWdlLWVuY3J5cHRpb2
 sops_age__list_1__map_recipient=age1wjepykv3glvsrtegu25tevg7vyn3ngpl607u3yjc9ucay04s045s796msw
 sops_age__list_2__map_enc=-----BEGIN AGE ENCRYPTED FILE-----\nYWdlLWVuY3J5cHRpb24ub3JnL3YxCi0+IFgyNTUxOSBFeHhaOURNZnRVMEwxNThu\nUjF4Q0kwUXhTUE1QSzZJbmpubnh3RnpQTmdvCjRmWWxpNkxFUmVGb3NRbnlydW5O\nWEg3ZXJQTU4vcndzS2pUQXY3Q0ttYjAKLS0tIE9IRFJ1c2ZxbGVHa2xTL0swbGN1\nTzgwMThPUDRFTWhuZHJjZUYxOTZrU00KY62qrNBCUQYxwcLMXFEnLkwncxq3BPJB\nKm4NzeHBU87XmPWVrgrKuf+PH1mxJlBsl7Hev8xBTy7l6feiZjLIvQ==\n-----END AGE ENCRYPTED FILE-----\n
 sops_age__list_2__map_recipient=age1c783ym2q5x9tv7py5d28uc4k44aguudjn03g97l9nzs00dd9tsrqum8h4d
-sops_lastmodified=2026-03-01T20:26:09Z
+sops_lastmodified=2026-03-05T15:55:19Z
-sops_mac=ENC[AES256_GCM,data:IxzU6VehA0iHgpIEqDSoMywKyKONI6jSr/6Amo+g3JI72awJtk6ft0ppfDWZjeHhL0ixfnvgqMNwai+1e0V/U8hSP8/FqYKEVpAO0UGJfBPKP3pbw+tx3WJQMF5dIh2/UVNrKvoACZq0IDJfXlVqalCnRMQEHGtKVTIT3fn8m6c=,iv:0w0ohOBsqTzuoQdtt6AI5ZdHEKw9+hI73tycBjDSS0o=,tag:Guw7LweA4m4Nw+3kSuZKWA==,type:str]
+sops_mac=ENC[AES256_GCM,data:orLypjurBTYmk3um0bDQV3wFxj1pjCsjOf2D+AZyoIYY88MeY8BjK8mg8BWhmJYlGWqHH1FCpoJS+2SECv2Bvgejqvx/C/HSysA8et5CArM/p/MBbcupLAKOD8bTXorKMRDYPkWpK/snkPToxIZZd7dNj/zSU+OhRp5qLGCHkvM=,iv:eBn93z4DSk8UPHgP/Jf/Kz+3KwoKIQ9Et72pbLFcLP8=,tag:79kzPIKp0rtHGhH1CkXqwg==,type:str]
 sops_unencrypted_suffix=_unencrypted
 sops_version=3.12.1

CHANGELOG.md

@@ -6,6 +6,12 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 
 ## [Unreleased]
 
+### Fixed
+- **Pipeline diagnostic script** (`scripts/check_pipeline.py`) — handle DuckDB catalog naming quirk where `lakehouse.duckdb` uses catalog `lakehouse` instead of `local`, causing SQLMesh logical views to break. Script now auto-detects the catalog via `USE`, and falls back to querying physical tables (`sqlmesh__<schema>.<table>__<hash>`) when views fail.
+- **Eurostat gas prices extractor** — `nrg_pc_203` filter missing `unit` dimension (API returns both KWH and GJ_GCV); now filters to `KWH`.
+- **Eurostat labour costs extractor** — `lc_lci_lev` used non-existent `currency` filter dimension; corrected to `unit: EUR`.
+- **Supervisor transform step** — changed `sqlmesh run` to `sqlmesh plan prod --auto-apply` so new/modified models are detected and applied automatically.
+
 ### 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`.

extract/padelnomics_extract/src/padelnomics_extract/eurostat.py

@@ -63,15 +63,15 @@ DATASETS: dict[str, dict] = {
         "time_dim": "time",
     },
     "nrg_pc_203": {
-        # Gas prices for non-household consumers, EUR/GJ, excl. taxes
+        # Gas prices for non-household consumers, EUR/kWh, excl. taxes
-        "filters": {"freq": "S", "nrg_cons": "GJ1000-9999", "currency": "EUR", "tax": "I_TAX"},
+        "filters": {"freq": "S", "nrg_cons": "GJ1000-9999", "unit": "KWH", "currency": "EUR", "tax": "I_TAX"},
         "geo_dim": "geo",
         "time_dim": "time",
     },
     "lc_lci_lev": {
         # Labour cost levels EUR/hour — NACE N (administrative/support services)
-        # Stored in dim_countries for future staffed-scenario calculations.
+        # D1_D4_MD5 = compensation of employees + taxes - subsidies (total labour cost)
-        "filters": {"lcstruct": "D1_D2_A_HW", "nace_r2": "N", "currency": "EUR"},
+        "filters": {"lcstruct": "D1_D4_MD5", "nace_r2": "N", "unit": "EUR"},
         "geo_dim": "geo",
         "time_dim": "time",
     },

infra/supervisor/supervisor.sh

@@ -33,10 +33,10 @@ do
         DUCKDB_PATH="${DUCKDB_PATH:-/data/padelnomics/lakehouse.duckdb}" \
             uv run --package padelnomics_extract extract
 
-        # Transform
+        # Transform — plan detects new/changed models; run only executes existing plans.
         LANDING_DIR="${LANDING_DIR:-/data/padelnomics/landing}" \
         DUCKDB_PATH="${DUCKDB_PATH:-/data/padelnomics/lakehouse.duckdb}" \
-            uv run --package sqlmesh_padelnomics sqlmesh run --select-model "serving.*"
+            uv run sqlmesh -p transform/sqlmesh_padelnomics plan prod --auto-apply
 
         # Export serving tables to analytics.duckdb (atomic swap).
         # The web app detects the inode change on next query — no restart needed.

infra/supervisor/workflows.toml

@@ -70,5 +70,5 @@ description = "UK local authority population estimates from ONS"
 
 [gisco]
 module = "padelnomics_extract.gisco"
-schedule = "monthly"
+schedule = "0 0 1 1 *"
 description = "EU geographic boundaries (NUTS2 polygons) from Eurostat GISCO"

scripts/check_pipeline.py

@@ -8,6 +8,10 @@ Or locally:
     DUCKDB_PATH=data/lakehouse.duckdb uv run python scripts/check_pipeline.py
 
 Read-only — never writes to the database.
+
+Handles the DuckDB catalog naming quirk: when the file is named lakehouse.duckdb,
+the catalog is "lakehouse" not "local". SQLMesh views may reference the wrong catalog,
+so we fall back to querying physical tables (sqlmesh__<schema>.<table>__<hash>).
 """
 
 import os
@@ -27,6 +31,86 @@ PIPELINE_TABLES = [
 ]
 
 
+def _use_catalog(con):
+    """Detect and USE the database catalog so schema-qualified queries work."""
+    catalogs = [
+        row[0]
+        for row in con.execute(
+            "SELECT catalog_name FROM information_schema.schemata"
+        ).fetchall()
+    ]
+    # Pick the non-system catalog (not 'system', 'temp', 'memory')
+    user_catalogs = [c for c in set(catalogs) if c not in ("system", "temp", "memory")]
+    if user_catalogs:
+        catalog = user_catalogs[0]
+        con.execute(f"USE {catalog}")
+        return catalog
+    return None
+
+
+def _find_physical_table(con, schema, table):
+    """Find the SQLMesh physical table name for a logical table.
+
+    SQLMesh stores physical tables as:
+        sqlmesh__<schema>.<schema>__<table>__<hash>
+    """
+    sqlmesh_schema = f"sqlmesh__{schema}"
+    try:
+        rows = con.execute(
+            "SELECT table_schema, table_name "
+            "FROM information_schema.tables "
+            f"WHERE table_schema = '{sqlmesh_schema}' "
+            f"AND table_name LIKE '{schema}__{table}%' "
+            "ORDER BY table_name "
+            "LIMIT 1"
+        ).fetchall()
+        if rows:
+            return f"{rows[0][0]}.{rows[0][1]}"
+    except Exception:
+        pass
+    return None
+
+
+def _query_table(con, schema, table):
+    """Try logical view first, fall back to physical table. Returns (fqn, count) or (fqn, error_str)."""
+    logical = f"{schema}.{table}"
+    try:
+        (count,) = con.execute(f"SELECT COUNT(*) FROM {logical}").fetchone()
+        return logical, count
+    except Exception:
+        pass
+
+    physical = _find_physical_table(con, schema, table)
+    if physical:
+        try:
+            (count,) = con.execute(f"SELECT COUNT(*) FROM {physical}").fetchone()
+            return f"{physical} (physical)", count
+        except Exception as e:
+            return f"{physical} (physical)", f"ERROR: {e}"
+
+    return logical, "ERROR: view broken, no physical table found"
+
+
+def _query_sql(con, sql, schema_tables):
+    """Execute SQL, falling back to rewritten SQL using physical table names if views fail.
+
+    schema_tables: list of (schema, table) tuples used in the SQL, in order of appearance.
+    The SQL must use {schema}.{table} format for these references.
+    """
+    try:
+        return con.execute(sql)
+    except Exception:
+        # Rewrite SQL to use physical table names
+        rewritten = sql
+        for schema, table in schema_tables:
+            physical = _find_physical_table(con, schema, table)
+            if physical:
+                rewritten = rewritten.replace(f"{schema}.{table}", physical)
+            else:
+                raise
+        return con.execute(rewritten)
+
+
 def main():
     if not os.path.exists(DUCKDB_PATH):
         print(f"ERROR: {DUCKDB_PATH} not found")
@@ -36,6 +120,10 @@ def main():
 
     print(f"Database: {DUCKDB_PATH}")
     print(f"DuckDB version: {con.execute('SELECT version()').fetchone()[0]}")
+
+    catalog = _use_catalog(con)
+    if catalog:
+        print(f"Catalog: {catalog}")
     print()
 
     # ── Row counts at each layer ──────────────────────────────────────────
@@ -44,28 +132,11 @@ def main():
     print("=" * 60)
 
     for schema, table in PIPELINE_TABLES:
-        # SQLMesh may use __<env> suffixed physical tables
+        fqn, result = _query_table(con, schema, table)
-        # Try the logical name first, then scan for physical tables
+        if isinstance(result, int):
-        candidates = [f"{schema}.{table}"]
+            print(f"  {fqn:55s} {result:>10,} rows")
-        try:
+        else:
-            phys = con.execute(
+            print(f"  {fqn:55s} {result}")
-                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()
@@ -74,7 +145,9 @@ def main():
     print("=" * 60)
 
     try:
-        row = con.execute("""
+        row = _query_sql(
+            con,
+            """
             SELECT
                 MIN(snapshot_date) AS min_date,
                 MAX(snapshot_date) AS max_date,
@@ -82,7 +155,9 @@ def main():
                 CURRENT_DATE AS today,
                 CURRENT_DATE - INTERVAL '30 days' AS window_start
             FROM foundation.fct_daily_availability
-        """).fetchone()
+        """,
+            [("foundation", "fct_daily_availability")],
+        ).fetchone()
         if row:
             min_date, max_date, days, today, window_start = row
             print(f"  Min snapshot_date:   {min_date}")
@@ -104,7 +179,9 @@ def main():
     print("=" * 60)
 
     try:
-        row = con.execute("""
+        row = _query_sql(
+            con,
+            """
             WITH venue_stats AS (
                 SELECT
                     da.tenant_id,
@@ -124,7 +201,9 @@ def main():
                 MAX(days_observed) AS max_days,
                 MIN(days_observed) AS min_days
             FROM venue_stats
-        """).fetchone()
+        """,
+            [("foundation", "fct_daily_availability")],
+        ).fetchone()
         if row:
             total, passing, failing, max_d, min_d = row
             print(f"  Venues in 30-day window:          {total}")
@@ -145,7 +224,9 @@ def main():
     print("=" * 60)
 
     try:
-        rows = con.execute("""
+        rows = _query_sql(
+            con,
+            """
             SELECT
                 CASE
                     WHEN occupancy_rate IS NULL THEN 'NULL'
@@ -160,7 +241,9 @@ def main():
             FROM foundation.fct_daily_availability
             GROUP BY 1
             ORDER BY 1
-        """).fetchall()
+        """,
+            [("foundation", "fct_daily_availability")],
+        ).fetchall()
         for bucket, cnt in rows:
             print(f"  {bucket:25s} {cnt:>10,}")
     except Exception as e:
@@ -173,14 +256,21 @@ def main():
     print("=" * 60)
 
     try:
-        row = con.execute("""
+        row = _query_sql(
+            con,
+            """
             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()
+        """,
+            [
+                ("foundation", "fct_availability_slot"),
+                ("foundation", "dim_venue_capacity"),
+            ],
+        ).fetchone()
         if row:
             slot_t, cap_t, missing = row
             print(f"  Tenants in fct_availability_slot: {slot_t}")

web/src/padelnomics/static/css/planner.css

@@ -455,6 +455,8 @@
   border-radius: 18px;
   padding: 1rem;
   box-shadow: 0 1px 4px rgba(0,0,0,0.04);
+  min-width: 0;
+  overflow: hidden;
 }
 .chart-container__label {
   font-size: 11px;