Completes the last-distance-offered feature against the mockup: the
year-by-year record, the same numbers drawn over real streets, and the
reader's own address measured against them.
Serving the history
The first cut deliberately served only the latest year, because a plain
series would draw a trend line straight through gaps that are absences of
publication, not of a cut-off. That reasoning is answered rather than
abandoned: cutoffYearRows classifies every year in the span, and the chart
breaks the line rather than interpolating across it.
A missing year is not one fact but three. It may be unpublished; it may be
a year the school was not oversubscribed; or there may be no record at all.
Collapsing them into "no data" throws away the reassuring case and hides
the important caveat, so each is stated in words in the table.
The claim is held to what the data supports. fact_admissions.oversubscribed
compares FIRST PREFERENCES against places, which does not establish that
every applicant was offered one — so the copy says "places available on
first preferences" and a test asserts the stronger claim never appears.
The trend summary is not a verdict
It names both endpoints and their years and lets the reader conclude. It is
withheld below four published points, and a swing under a tenth of the
earlier figure is reported as "broadly the same" rather than dressed up as
a direction.
The postcode check
This is the only place on the site that answers a question about a family
rather than a school, so most of the care went into what it refuses to say.
postcodes.io returns a centroid covering roughly fifteen addresses, which
against a 500 m cut-off is a fifth of the whole distance — so a margin
inside 100 m returns "too close to call" rather than a place a family does
not have. Unpublished years count as unknown, never as a pass. The limits
are stated before the check is used, not revealed with the answer.
The postcode is geocoded in the browser and never stored.
Both templates
Banded and selective secondaries are exactly where this matters most, so
the detail is shared. The primary page gives it a third tab; the secondary
page is one flat panel by design and renders it inline.
Absence is explained rather than reported. A selective school's missing
figure is explained by how it admits; a consistently undersubscribed school
reads as good news.
Also makes the batch loader's test double honour ORDER BY. It was a no-op,
so "latest row per URN" was really "first row in the fixture" and the test
would have passed with the sort reversed or removed.
Verified: 214 frontend tests, 54 backend, 45/53 e2e green against staging
(the 8 cut-off journeys skip until the DAG runs). Rendered offline against
the real compiled CSS in both themes and at 390px; every new surface clears
WCAG AA, measured on composited pixels.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WDvkyqqHABm4bmth2kjAxE
Adds the cut-off distance a parent actually asks about — "how close do we
need to live?" — end to end: a Singer tap, dbt staging and mart models, an
Airflow DAG, and a tile on both detail templates. 3,597 schools across 57
local authorities carry a figure; the rest are unchanged.
There is no national source for this. Each LA publishes its own cut-offs in
its own format, and the collected CSV is transcribed from PDFs, spreadsheets
and web pages — so most of the work here is deciding what is safe to show.
Data
* tap-uk-school-distance loads the CSV verbatim into raw. Keyed on
(urn, year, school_name), because school_name carries the admission
route: (urn, year) alone collides on 118 keys and a reload would have
silently dropped every band but one.
* stg_school_distance applies a 25 m – 25 km plausibility band. The source
contains 0.0-mile rows (published where a school filled on a higher
criterion), 1-metre cut-offs, and one reading 533 miles — ~4% of rows,
all of which would put a visibly wrong number on a live page.
* fact_admission_distance collapses routes to one row per school per year
using the furthest, and keeps route_count so the page can say the figure
is the widest of several bands rather than the one for a given child.
Serving
* Kept out of fact_admissions: that mart is EES-derived and near-complete
for England, this one covers 57 LAs, and the two refresh independently.
* Latest year only. Coverage is ragged — a school may have 2021 and 2026
and nothing between — so a history array would invite a trend line drawn
through gaps that are absences of publication, not of a cut-off.
* The Admissions section now renders on either source. 3% of the schools
that render have a cut-off and no EES admissions row, and gating on
admissions alone would have hidden the figure on those pages.
Interface
* The year travels with the figure everywhere it appears; a cut-off
detached from its admissions round is not a fact about anything.
* "Not a fixed catchment — it moves every year" sits under every instance,
because that is the inference a parent will otherwise draw.
* Replaces a hardcoded "Historical distance cut-off data is not available
for this school" that appeared on every secondary page, including the
ones whose council does publish it. The absence is now stated only when
it is real, and names the authority that would hold it.
The tint costs the muted tokens their AA margin: measured on the composited
backdrop (not the computed one, which reports the untinted card), --text-muted
falls to 4.09:1 in dark theme. The tile uses --text-secondary instead — 6.50:1
dark, 6.60:1 light.
The DAG is manual, like the other annual ones: councils publish on allocation
day, each on its own timetable, so there is no date worth scheduling against.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WDvkyqqHABm4bmth2kjAxE
Add seven school-identity fields to the detail header (both primary and
secondary views): age range, religious character, nursery and sixth-form
indicators as chips; telephone (tel: link), county and parliamentary
constituency as header details. religious_denomination, age_range and
has_sixth_form were already served; telephone, nursery_provision, county
and parliamentary_constituency are newly wired through the marts query
(with a NULL fallback for un-rebuilt marts, mirroring has_sixth_form) and
the school_info API response.
Remove three UI sections the backend never populated (always null): Year 1
Phonics, the SEN "types of additional needs" breakdown, and the average
class-size card — along with their now-dead props, route plumbing, and the
SenDetail/Phonics types + class_size_avg field.
Extend the e2e detail journey to assert the Phonics section is gone and the
new header fields render when the record carries them.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The KS2 SATs chart drew a single national-average line spanning the
full height of each subject's chart area, positioned at the national
*expected* value. But the area stacks two bars — Expected and Exceeding
— and the higher-standard/greater-depth national is a very different,
much lower figure (e.g. reading higher standard ~29% vs expected ~75%).
So the line crossed the Exceeding bar at the wrong place, making every
school's exceeding result look far below national when it wasn't.
The per-subject higher-standard nationals were already computed in the
fact_ks2_national_averages mart; they just weren't serialized. Fix:
- backend: add reading_high_pct, writing_gd_pct (writing = greater
depth) and maths_high_pct to the national-averages payload.
- SchoolDetailView: pass a nationalExceedingPct per subject, mapping
writing to the greater-depth figure.
- SatsChart: replace the single full-height line with a national marker
on each bar's own track (coral tick + "nat X%" in the bar header), so
Expected and Exceeding each sit against the correct benchmark.
KS2 only; the secondary Attainment 8 chart already uses one line for
one measure and is untouched.
Verified: tsc --noEmit, next build, and backend pytest (national
averages marts, incl. a new test guarding the per-subject nationals).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
M1: admissions rounds are now selected by the active phase tab
(admissionsForPhase) — an all-through school's Year 7 round no longer
masquerades as Reception odds beside pure primaries; honest per-cell and
section fallbacks name the round (Reception / Year 7).
M2: Ofsted sentinel codes (9 = not applicable) never render as judgement
chips, and the sixth-form judgement — previously dropped — now renders
for schools that have one.
M3: 'What this means' is phase- and type-aware: selective schools get
entrance-test framing, secondary faith schools a faith-criteria note, and
the primaries' distance template never appears on the secondary tab
(admissions_policy now exposed in compare school_info).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
New ees_ks4_national stream ingests the EES 'National characteristics
summary data' series (England, state-funded, all pupils). The old mart's
unweighted school means were 7-15 points off every headline measure and
produced an impossible national Progress 8 (-0.27). The API's computed
fallback is gone too: the footnote calls these figures official, so an
unbuilt mart now yields an empty series, never a stand-in.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
The FSM chip anchored against disadvantaged_pct (a different measure,
FSM6+CLA) whenever fsm_pct was null — which it always was, since the
performance df has no fsm_pct. New fact_census_benchmarks mart supplies
pupil-weighted FSM/EAL means per phase; the KS2-column medians that
produced a bogus 50% 'secondary disadvantaged' anchor are gone.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
get_supplementary_data ran ~5 sequential DB round-trips per URN, so
/api/compare scaled at ~37ms/school (measured on staging: 1 school 155ms,
3 schools 220ms, 6 schools 340ms). get_supplementary_data_batch fetches
each table once with WHERE urn IN (...) and groups in Python, collapsing
5*N round-trips to a constant 5. get_supplementary_data is now a thin
wrapper so the detail endpoint is unchanged; the compare endpoint makes
one batched call. Each table degrades independently on failure.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
fact_ks4_national_averages is computed once at dbt build time (covered by
the EES DAG's stg_ees_ks4+ selector). _national_averages_payload now reads
both national-averages marts instead of scanning the performance dataframe
per year on every /api/compare request (~250ms saved per call). Fallback
for the deploy-before-DAG window computes the latest year only.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0146VHeLAWjDVE2B5uU67jCB
- data_loader.load_school_data_as_dataframe now catches a ProgrammingError
whose message mentions has_sixth_form (psycopg2 UndefinedColumn) and
retries with a NULL-AS-has_sixth_form query variant, so the API keeps
serving data (and the app.py column-fallback branch stays reachable)
even before the nightly pipeline has rebuilt marts.dim_school.
- utils.convert_to_native now handles numpy.bool_ so GET /api/schools/{urn}
doesn't 500 once has_sixth_form is a populated bool-dtype column.
- Update the now-stale comment on the app.py age-range fallback branch.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Schools without KS2/KS4 results (special post-16 institutions, sixth-form
centres, PRUs, new schools) come back from the marts LEFT JOIN with NaN in
every numeric column. school_info passed those raw pandas values straight
into JSONResponse, which renders with allow_nan=False, so the detail
endpoint 500d and the frontend turned that into a 404 on every such SEO
landing page.
Run school_info values through convert_to_native (the same treatment
yearly_data already gets), add backend unit tests plus a pytest step in PR
checks, and an e2e journey that finds a results-less school via the search
API and asserts its page renders.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Removes the 'What Parents Say' section and all supporting elements:
Frontend:
- Drop the OfstedParentView type, the parent_view field, the survey
section and the 'X% would recommend' callouts in the primary and
secondary detail views, the Parents nav item, and the parent-view CSS.
Backend:
- Remove the FactParentView model, its loading in data_loader, and
parent_view from the school-details API response.
- Bump SCHEMA_VERSION to 6 and add an idempotent drop step
(DROP TABLE IF EXISTS marts.fact_parent_view) to the CLI migration;
add scripts/sql/drop_fact_parent_view.sql to apply directly to the
dbt-owned marts DBs on staging and prod.
Pipeline:
- Delete the stg_parent_view + fact_parent_view dbt models and their
source/schema entries, the tap-uk-parent-view Meltano extractor, and
the monthly Parent View DAG; drop it from the Dockerfile and the
staging bootstrap docs.
The rest of dbt (which builds every mart the app reads) is untouched.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The rankings endpoint validated year with le=2100, but the database
stores academic-year codes like 201819, so any explicit year selection
returned a 422 and the rankings page rendered its empty state. Widen
the bound to cover the codes and extend the e2e journey to pick a
specific year and assert the table stays populated.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The school detail page only showed the latest admissions year. We store
every year, which is more decision-relevant for parents (the trend and its
consistency matter more than a single noisy year).
Backend now returns the full admissions_history (oldest first) alongside the
existing latest-year object. The primary SchoolDetailView gains a header
toggle ("This year | N-year trend") that swaps the Q&A for an SVG sparkline
of the first-choice offer rate. The toggle only appears when >=2 years carry
an offer rate; otherwise it falls back to the single-year card. Both views
share one CSS-grid cell so switching causes no layout shift.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Frontend
- Dynamic-import Chart.js components on detail/compare views so Chart.js
no longer ships in initial JS.
- Drop force-dynamic on home, compare, rankings so internal data fetches
reuse Next.js's per-call revalidate cache.
- Switch /school/[slug] to ISR with a 7-day revalidate window (school
data updates annually).
- Preconnect to analytics + postcodes.io; remove redundant defer on the
Umami Script tag (afterInteractive already covers it).
- Bump images.minimumCacheTTL to 1 year.
- Extract HowItWorks and Editorial sections as server components passed
to HomeView via slot props so their JSX stays out of the client bundle.
Backend
- Add GZipMiddleware (min 512 bytes).
- Add CacheAndETagMiddleware: per-path Cache-Control with long s-maxage
+ stale-while-revalidate, ETag generation, and 304 on If-None-Match.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
The /api/rankings endpoint returned each row keyed by the metric's
column name (e.g. rwm_high_pct) but never under a generic `value`
field. The frontend RankingItem type and RankingsView both read
ranking.value, so every row rendered "—" for every metric — the
default rwm_expected_pct included.
Add `df["value"] = df[metric]` before JSON serialisation so the
frontend gets the value it has always expected. The raw metric
column is still in the row for any caller that wants it explicitly.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
P1 (backend/data_loader.py): Add load_latest_school_data() which pre-computes
the one-row-per-school latest-year snapshot (groupby, prev-year trend merge)
once at startup instead of on every /api/schools request. get_schools route
now starts from the cached snapshot rather than rebuilding it.
S3 (backend/app.py): Wrap synchronous geocode_single_postcode() call in
asyncio.to_thread() so postcode lookups no longer block the uvicorn event
loop. Admin reload endpoint also uses to_thread for both cache primes.
P2 (nextjs-app/components/HomeView.tsx): Add mapParamsRef guard so switching
back to map view does not re-fetch 500 schools when search params haven't
changed. Reset ref on new searches so fresh data is always fetched.
P3 (nextjs-app/lib/chartSetup.ts): Extract Chart.js registration into a
shared side-effect module. ComparisonChart and PerformanceChart now import
it instead of each calling ChartJS.register() independently.
P4 (backend/database.py): Remove unnecessary db.commit() from the read-only
get_db_session() context manager — saves a DB round-trip on every request.
P5 (backend/database.py): Add pool_recycle=1800 to SQLAlchemy engine to
prevent stale TCP connections from accumulating in long-running processes.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Redesign the School Details page for better parent comprehension:
- New SatsChart component: horizontal cascade bars with ruler scale and
national average marker (teal/coral palette matching site theme)
- Admissions section: visual progress bar showing 1st-preference demand
vs available places, colour-coded by oversubscription status
- Historical data: collapse raw year-by-year table behind a disclosure
element while keeping the performance line chart always visible
- EAL metric: add national average comparison via DeltaChip (backend now
includes eal_pct in national averages endpoint)
- New formatWithSuppression utility for null/suppressed data handling
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The school_info object was missing total_pupils entirely, so the frontend
always fell back to the KS4 exam cohort from yearly_data. Now selects
s.total_pupils (GIAS NumberOfPupils — full school roll) as gias_total_pupils
in the main query and exposes it as total_pupils on school_info.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Replaces computed means from our school dataset with the published DfE
national headline figures for the KS2 chart reference line.
- tap-uk-ees: new EESKs2NationalStream fetches the stable EES data-catalogue
CSV (one row per year, England national total, AllSchools filter)
- dbt staging: stg_ees_ks2_national normalises columns, casts to float,
filters to years >= 201617
- dbt mart: fact_ks2_national_averages — one row per year, official figures
- backend/models: Ks2NationalAverage SQLAlchemy model
- backend/app: /api/national-averages queries the mart for KS2 by_year;
secondary by_year stays computed (no DfE KS4 national dataset yet)
- DAG: extract_ks2_national task added to school_data_annual_ees,
runs in parallel with the main EES extract
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Previously the dashed reference line was a flat horizontal at the latest
year's national average across all historical data, implying the national
figure was constant. Now the backend returns per-year averages in `by_year`
and the chart maps each data year to its own national average, so the
reference line correctly reflects how the national picture changed over time
(including COVID recovery dip/recovery).
- backend: /api/national-averages now includes `by_year` list alongside
existing `year`/`primary`/`secondary` latest-year snapshot
- types: NationalAverages extended with `by_year: NationalAveragesYear[]`
- PerformanceChart: accepts `nationalByYear` prop; builds per-year series
aligned to school data years, falling back to scalar prop if absent
- SchoolDetailView + SecondarySchoolDetailView: pass `nationalAvg.by_year`
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Root cause: the UNION ALL query in data_loader.py produced two rows per
all-through school per year (one KS2, one KS4), with drop_duplicates()
silently discarding the KS4 row. Fixes:
- New dbt mart `fact_performance`: FULL OUTER JOIN of fact_ks2_performance
and fact_ks4_performance on (urn, year). One row per school per year.
All-through schools have both KS2 and KS4 columns populated.
- data_loader.py: replace 175-line UNION ALL with a simple JOIN to
fact_performance. No more duplicate rows or drop_duplicates needed.
- sync_typesense.py: single LATERAL JOIN to fact_performance instead of
two separate KS2/KS4 joins.
- app.py: remove drop_duplicates (no longer needed); add PHASE_GROUPS
constant so all-through/middle schools appear in primary and secondary
filter results (were previously invisible to both); scope result_filters
gender/admissions_policies to secondary schools only.
- HomeView.tsx: isSecondaryView is now majority-based (not "any secondary")
and isMixedView shows both sort option sets for mixed result sets.
- school/[slug]/page.tsx: all-through schools route to SchoolDetailView
(renders both SATs + GCSE sections) instead of SecondarySchoolDetailView
(KS4-only). Dedicated SEO metadata for all-through schools.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Remove 10-mile radius option; cap backend radius max at 5 miles
- Raise backend page_size max to 500 so map can fetch all schools in one call
- HomeView: when map view is active, fetch all schools within radius
(page_size=500) instead of showing only the paginated first page;
falls back to initial SSR schools while loading
- SchoolMap/LeafletMapInner: accept referencePoint prop and render a
distinctive coral circle pin at the search postcode location
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Load-more requests read URL params (postcode, radius, etc.) but page_size
is never in the URL — it's hardcoded in page.tsx. Without it the backend
received page_size=None, hit a TypeError on (page-1)*None, returned 500,
and the silent catch left the user stuck on page 1.
In a dense area (e.g. Wimbledon SW19) 50 schools fit within ~1.8 miles,
so page 1 never shows anything beyond that regardless of selected radius.
Fix:
- Backend: give page_size a safe default of 25 instead of None
- Frontend: explicitly pass initialSchools.page_size in load-more params
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Backend builds sitemap.xml from school data at startup (in-memory)
- POST /api/admin/regenerate-sitemap refreshes it after data updates
- New Airflow DAG (sitemap_generate) runs Sundays 05:00 and calls the endpoint
- Next.js proxies /sitemap.xml to the backend; removes the slow dynamic sitemap.ts
- docker-compose passes BACKEND_URL + ADMIN_API_KEY to Airflow env
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1. Simpler home page: only search box on landing, no filter dropdowns
2. Advanced filters: hidden behind toggle on results page, auto-open if active
3. Per-school phase rendering: each row renders based on its own data
4. Taller 4-line rows with context line (type, age range, denomination, gender)
5. Result-scoped filters: dropdown values reflect current search results
6. Fix blank filter values: exclude empty strings and "Not applicable"
7. Rankings: Primary/Secondary phase tabs with phase-specific metrics
8. Compare: Primary/Secondary tabs with school counts and phase metrics
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Backend: replace INNER JOIN ks2 with UNION ALL (ks2 + ks4) so primary
and secondary schools both appear in the main DataFrame
- Backend: add /api/national-averages endpoint computing means from live
data, replacing the hardcoded NATIONAL_AVG constant on the frontend
- Backend: add phase filter param to /api/schools; return phases from
/api/filters; fix hardcoded "phase": "Primary" in school detail endpoint
- Backend: add KS4 metric definitions (Attainment 8, Progress 8, EBacc,
English & Maths pass rates) to METRIC_DEFINITIONS and RANKING_COLUMNS
- Frontend: SchoolDetailView is now phase-aware — secondary schools show
a GCSE Results section (Att8, P8, E&M, EBacc) instead of SATs; phonics
tab hidden for secondary; admissions says Year 7 instead of Year 3;
history table shows KS4 columns; chart datasets switch for secondary
- Frontend: new MetricTooltip component (CSS-only ⓘ icon) backed by
METRIC_EXPLANATIONS — added to RWM, GPS, SEN, EAL, IDACI, progress
scores and all KS4 metrics throughout SchoolDetailView and SchoolCard
- Frontend: METRIC_EXPLANATIONS extended with KS4 terms (Attainment 8,
Progress 8, EBacc) and previously missing terms (SEN, EHCP, EAL, IDACI)
- Frontend: SchoolCard expands "RWM" to "Reading, Writing & Maths" and
shows Attainment 8 / English & Maths Grade 4+ for secondary schools
- Frontend: FilterBar adds Phase dropdown (Primary / Secondary / All-through)
- Frontend: HomeView hero copy updated; compact list shows phase-aware metric
- Global metadata updated to remove "primary only" framing
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
sync_typesense.py:
- Fix query string replacement: was matching 'ST_X(l.geom) as lng' but
QUERY_BASE uses 'l.longitude as lng' — KS2/KS4 lateral joins were
silently dropped on every sync run
backend:
- Add typesense_url/typesense_api_key settings to config.py
- Add search_schools_typesense() to data_loader.py — queries Typesense
'schools' alias, returns URNs in relevance order with typo tolerance;
falls back to empty list if Typesense is unavailable
- /api/schools: replace pandas str.contains with Typesense search;
results are filtered from the DataFrame and returned in relevance order;
graceful fallback to substring match if Typesense is down
requirements.txt: add typesense==0.21.0, numpy==1.26.4
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Pipeline:
- EES tap: split KS4 into performance + info streams, fix admissions filename
(SchoolLevel keyword match), fix census filename (yearly suffix), remove
phonics (no school-level data on EES), change endswith → in for matching
- stg_ees_ks4: rewrite to filter long-format data and extract Attainment 8,
Progress 8, EBacc, English/Maths metrics; join KS4 info for context
- stg_ees_admissions: map real CSV columns (total_number_places_offered, etc.)
- stg_ees_census: update source reference, stub with TODO for data columns
- Remove stg_ees_phonics, fact_phonics (no school-level EES data)
- Add ees_ks4_performance + ees_ks4_info sources, remove ees_ks4 + ees_phonics
- Update int_ks4_with_lineage + fact_ks4_performance with new KS4 columns
- Annual EES DAG: remove stg_ees_phonics+ from selector
Backend:
- models.py: replace all models to point at marts.* tables with schema='marts'
(DimSchool, DimLocation, KS2Performance, FactOfstedInspection, etc.)
- data_loader.py: rewrite load_school_data_as_dataframe() using raw SQL joining
dim_school + dim_location + fact_ks2_performance; update get_supplementary_data()
- database.py: remove migration machinery, keep only connection setup
- app.py: remove check_and_migrate_if_needed, remove /api/admin/reimport-ks2
endpoints (pipeline handles all imports)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The geocoding pass over ~15k schools takes longer than any reasonable
HTTP timeout. New approach:
- POST /api/admin/reimport-ks2 starts migration in background thread,
returns {"status":"started"} immediately
- GET /api/admin/reimport-ks2/status returns {running, done}
- ks2.py polls status every 30s (max 2h) before returning
- Kestra flow timeout bumped to PT2H
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add geocode query param to /api/admin/reimport-ks2 (defaults true).
ks2.py passes ?geocode=true so postcodes are resolved to lat/lng in
the same migration pass.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- backend: POST /api/admin/reimport-ks2 runs full CSV migration in a thread
- backend/docker-compose: ADMIN_API_KEY env var (default: changeme) so the
key is stable across restarts and the integrator can call the endpoint
- integrator: sources/ks2.py triggers the backend endpoint (900s timeout)
- integrator: flows/ks2.yml Kestra flow (manual trigger, no schedule)
To re-ingest after a DB wipe: trigger the ks2-reimport flow from the
Kestra UI at http://localhost:8080.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds a full data integration pipeline for enriching school profiles with
supplementary data from Ofsted, GIAS, EES, IDACI, and FBIT.
Backend:
- Bump SCHEMA_VERSION to 3; add 8 new DB tables (ofsted_inspections,
ofsted_parent_view, school_census, admissions, sen_detail, phonics,
school_deprivation, school_finance) plus GIAS columns on schools
- Expose all supplementary data via GET /api/schools/{urn}
- Enrich school list responses with ofsted_grade + ofsted_date
Integrator (new service):
- FastAPI HTTP microservice; Kestra calls POST /run/{source}
- 9 source modules: ofsted, gias, parent_view, census, admissions,
sen_detail, phonics, idaci, finance
- 9 Kestra flow YAMLs with scheduled triggers and 3× retry
Frontend:
- SchoolRow: colour-coded Ofsted badge (Outstanding/Good/RI/Inadequate)
- SchoolDetailView: 7 new sections — Ofsted sub-judgements, Parent View
survey bars, Admissions, Pupils & Inclusion / SEN, Phonics, Deprivation
Context, Finances
- types.ts: 8 new interfaces + extended School/SchoolDetailsResponse
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
The frontend expects location_info with coordinates array, but backend was
returning search_location with lat/lng keys. This fix enables the map toggle
to appear for location-based searches.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
On startup, the app now checks if the database schema version matches
the code. If there's a mismatch or no version exists, it automatically
runs a full data migration before starting.
- Add backend/version.py with SCHEMA_VERSION constant
- Add backend/migration.py with extracted migration logic
- Add SchemaVersion model to track DB version
- Add version check functions to database.py
- Update app.py lifespan to use check_and_migrate_if_needed()
- Simplify migrate_csv_to_db.py to use shared logic
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
When searching by location, users can now toggle between list view
(school cards grid) and a split map view showing:
- Interactive map on left with all school markers
- Scrollable school list on right
- Blue marker for search location, default markers for schools
- Clicking a marker highlights and scrolls to the corresponding card
Mobile responsive with stacked layout on smaller screens.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Replace footer note with a contact form that emails contact@schoolcompare.co.uk
via FormSubmit.co. Keep only the data source attribution. Update CSP to allow
form submissions to FormSubmit.co and add responsive styling for the form.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add GA4 measurement ID to config (default: G-J0PCVT14NY)
- Add /api/config endpoint to expose GA ID to frontend
- Update cookie consent with Analytics category (opt-in)
- Load GA4 only after user consents to analytics cookies
- Update CSP to allow Google Analytics domains
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Use direct bracket indexing instead of .get() for pandas Series
row access in calc_distance function to ensure scalar values
are returned for pd.isna() checks.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Display RWM Higher % alongside RWM Expected % on school cards
- Add trend indicators (up/down/stable arrows) showing year-over-year change
- Backend calculates previous year's RWM for trend comparison
- Trend appears on cards and in school detail modal
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
tudor