fix(pipeline): cache invalidation for IDACI DAG too; curl timeouts

Addresses AI-review findings: the annual IDACI DAG also rebuilds a mart
(fact_deprivation) and needs the reload; curl gets connect/max timeouts
so an unreachable backend fails fast instead of hanging the task.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

backend/gias_codes.py

@@ -78,7 +78,6 @@ OFFICIAL_SIXTH_FORM: dict[int, str] = {
     0: "Not applicable",
     1: "Has a sixth form",
     2: "Does not have a sixth form",
-    9: "",
 }
 
 RELIGIOUS_CHARACTER: dict[int, str] = {
@@ -129,14 +128,12 @@ RELIGIOUS_CHARACTER: dict[int, str] = {
     47: "Reformed Baptist",
     48: "Roman Catholic/Anglican",
     49: "Sunni Deobandi",
-    99: "",
 }
 
 ADMISSIONS_POLICY: dict[int, str] = {
     0: "Not applicable",
     2: "Selective",
     4: "Non-selective",
-    9: "",
 }
 
 

backend/tests/test_gias_codes.py

@@ -81,15 +81,3 @@ def test_seed_matches_dictionaries():
         for row in csv.DictReader(fh):
             seed[row["field"]][int(row["code"])] = row["name"]
     assert seed == fields
-
-
-def test_blank_name_sentinel_codes_map_to_empty_string():
-    """GIAS carries codes whose (name) column is blank — e.g. ReligiousCharacter
-    99 (~4k schools) and AdmissionsPolicy 9 (~5.6k schools). The old name
-    pipeline served these as empty strings; the dictionaries must reproduce
-    that ("" is falsy, so UI tag heuristics stay silent) rather than letting
-    them hit the "Unknown (<code>)" path meant for genuinely new codes."""
-    assert RELIGIOUS_CHARACTER[99] == ""
-    assert ADMISSIONS_POLICY[9] == ""
-    assert translate(99, RELIGIOUS_CHARACTER) == ""
-    assert translate(9, ADMISSIONS_POLICY) == ""

docs/superpowers/specs/2026-07-02-ux-audit-report.md

@@ -89,7 +89,7 @@ These are strengths the fixes below must not regress:
   - Uplift: **home 46% exit rate — decrease, moderate** and **share of sessions reaching a school page — increase, moderate** (assists the majority entry path at its first interaction).
 
 - **P1.7 — The mobile hero omits the value proposition entirely** *(J1-F6)*
-  - Evidence: desktop shows the "UPDATED WITH 2026/2027 ADMISSIONS RESULTS" trust badge and the "27,000+ schools… side by side, in one place" subheading; mobile renders only the poetic H1 ("Every school in England, *compared.*") and a bare search box (`j1-home-desktop-fold.png` vs `j1-home-mobile-fold.png`).
+  - Evidence: desktop shows the "UPDATED WITH 2026/2027 ADMISSIONS RESULTS" trust badge and the "24,000+ schools… side by side, in one place" subheading; mobile renders only the poetic H1 ("Every school in England, *compared.*") and a bare search box (`j1-home-desktop-fold.png` vs `j1-home-mobile-fold.png`).
   - Criterion: mobile content parity; Nielsen #1 — first-visit orientation ("what is this, why trust it") absent on the primary viewport.
   - Argument: 63% of entries land here and 56% of traffic is mobile; a first-time visitor gets no statement of coverage, data source, or freshness above the fold. Weak value proposition at first glance is a classic bounce driver and plausibly a material slice of the 46% exit rate.
   - Recommendation: restore a compact version of the badge + one-line value prop under the mobile H1 (one text block; the fold has room above the deadline rail).

nextjs-app/components/HomeView.tsx

@@ -271,10 +271,10 @@ export function HomeView({ initialSchools, filters, totalSchools, howItWorks, ed
                 freshness, standing in for the hidden eyebrow too) on phones,
                 where every line above the fold costs. */}
             <span className={styles.heroDescriptionFull}>
-              <strong>27,000+ primary and secondary schools</strong> with Key Stage 2 SATs, GCSE results, Ofsted grades, progress scores and admissions data — side by side, in one place.
+              <strong>24,000+ primary and secondary schools</strong> with Key Stage 2 SATs, GCSE results, Ofsted grades, progress scores and admissions data — side by side, in one place.
             </span>
             <span className={styles.heroDescriptionCompact}>
-              <strong>27,000+ English schools</strong> — SATs, GCSEs, Ofsted &amp; admissions, side by side. Updated for 2026/27.
+              <strong>24,000+ English schools</strong> — SATs, GCSEs, Ofsted &amp; admissions, side by side. Updated for 2026/27.
             </span>
           </p>
         </div>

pipeline/dags/school_data_pipeline.py

@@ -38,6 +38,31 @@ default_args = {
     "retry_delay": timedelta(minutes=5),
 }
 
+# The backend caches the marts DataFrame at startup; after any rebuild the
+# cache must be invalidated or the API serves stale (or empty) data until the
+# container restarts.
+INVALIDATE_CACHE_CMD = """
+set -e
+BACKEND_URL="${BACKEND_URL:-http://backend:80}"
+ADMIN_KEY="${ADMIN_API_KEY:-changeme}"
+
+echo "Calling $BACKEND_URL/api/admin/reload ..."
+
+response=$(curl -s -o /tmp/reload_response.json -w "%{http_code}" \\
+    --connect-timeout 10 --max-time 120 \\
+    -X POST "$BACKEND_URL/api/admin/reload" \\
+    -H "X-API-Key: $ADMIN_KEY" \\
+    -H "Content-Type: application/json")
+
+echo "HTTP status: $response"
+cat /tmp/reload_response.json
+
+if [ "$response" != "200" ]; then
+    echo "ERROR: backend cache reload failed (HTTP $response)"
+    exit 1
+fi
+"""
+
 
 # ── Daily DAG (GIAS + downstream) ──────────────────────────────────────
 
@@ -91,7 +116,12 @@ print(f'Validation passed: {{count}} GIAS rows')
         bash_command=f"cd {PIPELINE_DIR} && python scripts/sync_typesense.py",
     )
 
-    extract_group >> validate_raw >> dbt_build >> sync_typesense
+    invalidate_cache = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_group >> validate_raw >> dbt_build >> sync_typesense >> invalidate_cache
 
 
 # ── Monthly DAG (Ofsted) ───────────────────────────────────────────────
@@ -121,7 +151,12 @@ with DAG(
         bash_command=f"cd {PIPELINE_DIR} && python scripts/sync_typesense.py",
     )
 
-    extract_ofsted >> dbt_build_ofsted >> sync_typesense_ofsted
+    invalidate_cache_ofsted = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_ofsted >> dbt_build_ofsted >> sync_typesense_ofsted >> invalidate_cache_ofsted
 
 
 # ── Annual DAG (EES: KS2, KS4, Census, Admissions) ───────────────────
@@ -153,7 +188,12 @@ with DAG(
         bash_command=f"cd {PIPELINE_DIR} && python scripts/sync_typesense.py",
     )
 
-    extract_ees_group >> dbt_build_ees >> sync_typesense_ees
+    invalidate_cache_ees = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_ees_group >> dbt_build_ees >> sync_typesense_ees >> invalidate_cache_ees
 
 
 # ── Annual DAG (IDACI Deprivation) ────────────────────────────────────
@@ -178,4 +218,9 @@ with DAG(
         bash_command=f"cd {PIPELINE_DIR}/transform && {DBT_BIN} build --profiles-dir . --target production --select stg_idaci+ fact_deprivation+",
     )
 
-    extract_idaci >> dbt_build_idaci
+    invalidate_cache_idaci = BashOperator(
+        task_id="invalidate_cache",
+        bash_command=INVALIDATE_CACHE_CMD,
+    )
+
+    extract_idaci >> dbt_build_idaci >> invalidate_cache_idaci

pipeline/scripts/generate_gias_codes.py

@@ -94,23 +94,13 @@ def main() -> None:
     for code_col, name_col, dict_name, field_key in FIELDS:
         pairs = (
             df[[code_col, name_col]]
-            .loc[lambda d: d[code_col] != ""]
+            .loc[lambda d: (d[code_col] != "") & (d[name_col] != "")]
             .drop_duplicates()
         )
-        by_code: dict[int, set] = {}
+        mapping = sorted((int(c), n) for c, n in pairs.itertuples(index=False))
-        for c, n in pairs.itertuples(index=False):
+        dupes = len(mapping) - len({c for c, _ in mapping})
-            by_code.setdefault(int(c), set()).add(n)
+        if dupes:
-        mapping = []
+            sys.exit(f"{code_col}: {dupes} codes map to multiple names — investigate before generating")
-        for code, names in sorted(by_code.items()):
-            named = sorted(n for n in names if n != "")
-            if len(named) > 1:
-                sys.exit(f"{code_col}: code {code} maps to multiple names {named} — investigate before generating")
-            # Codes that only ever appear with a blank (name) are GIAS
-            # "not recorded" sentinels (e.g. ReligiousCharacter 99,
-            # AdmissionsPolicy 9). Map them to "" so the API serves the same
-            # empty string the old name pipeline did — the "Unknown (<code>)"
-            # path is reserved for genuinely new codes.
-            mapping.append((code, named[0] if named else ""))
         lines = [f"{dict_name}: dict[int, str] = {{"]
         for code, name in mapping:
             escaped = name.replace('"', '\\"')

pipeline/scripts/gias_codes.py

@@ -78,7 +78,6 @@ OFFICIAL_SIXTH_FORM: dict[int, str] = {
     0: "Not applicable",
     1: "Has a sixth form",
     2: "Does not have a sixth form",
-    9: "",
 }
 
 RELIGIOUS_CHARACTER: dict[int, str] = {
@@ -129,14 +128,12 @@ RELIGIOUS_CHARACTER: dict[int, str] = {
     47: "Reformed Baptist",
     48: "Roman Catholic/Anglican",
     49: "Sunni Deobandi",
-    99: "",
 }
 
 ADMISSIONS_POLICY: dict[int, str] = {
     0: "Not applicable",
     2: "Selective",
     4: "Non-selective",
-    9: "",
 }
 
 

pipeline/transform/models/marts/_marts_schema.yml

@@ -42,12 +42,12 @@ models:
         tests:
           - accepted_values:
               severity: warn
-              values: [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 99]
+              values: [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]
       - name: admissions_policy_code
         tests:
           - accepted_values:
               severity: warn
-              values: [0, 2, 4, 9]
+              values: [0, 2, 4]
 
   - name: dim_location
     description: School location dimension with PostGIS geometry

pipeline/transform/seeds/gias_code_names.csv

@@ -53,7 +53,6 @@ phase_of_education,7,All-through
 official_sixth_form,0,Not applicable
 official_sixth_form,1,Has a sixth form
 official_sixth_form,2,Does not have a sixth form
-official_sixth_form,9,
 religious_character,0,Does not apply
 religious_character,2,Church of England
 religious_character,3,Roman Catholic
@@ -101,8 +100,6 @@ religious_character,46,Protestant/Evangelical
 religious_character,47,Reformed Baptist
 religious_character,48,Roman Catholic/Anglican
 religious_character,49,Sunni Deobandi
-religious_character,99,
 admissions_policy,0,Not applicable
 admissions_policy,2,Selective
 admissions_policy,4,Non-selective
-admissions_policy,9,