Corpus validation of the modelling_e2e photovoltaic_supply-as-list fix. Cert
6102-6227-8000-0083-2292 (RdSAP-20.0.0 semi, gas combi + 2× 1.14 kW PV arrays)
crashed from_rdsap_schema_20_0_0 on the measured-array list; the fix routes it
through the dict-tolerant _map_schema_21_pv. PV correctly credited: engine 61
(no PV) → 66 (+5). Built in Elmhurst (evidence: epc.json + summary + worksheet,
fabric+heating; the PV "New Technologies" Panel-details grid deferred): worksheet
55 = engine-on-Elmhurst-inputs 55 exactly → calculator faithful. The +6 engine-vs-
Elmhurst base-dwelling residual is the documented RdSAP-default gap (band-C cavity-
uninsulated suspended-floor semi). Pinned engine 66.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Corpus validation of the modelling_e2e built_form fix. Cert 8742-6624-9300-2780-4926
(SAP-Schema-16.0, ground-floor electric-storage-heater flat) omits built_form; the
mapper now derives it from dwelling_type. built_form is ML-only so the fix is
SAP-neutral: engine 66 = lodged 66 exactly. Built in Elmhurst (evidence: epc.json +
summary + worksheet): worksheet 54, engine-on-Elmhurst-inputs 53 ≈ 54 → calculator
faithful. The +12 engine-vs-Elmhurst is a build/input gap (cert size-1 small cylinder
unrepresentable in Elmhurst's Normal/110L-minimum entry → higher HW + reduced-field
16.0 defaults). Pinned engine 66.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- run_modelling_e2e --from-db re-models from already-persisted inputs (reads
each Property's Effective EPC + planning protections + solar from the DB) and
skips every live fetcher — zero gov-API calls. With --persist it re-writes the
Plan and, for lodged-EPC Properties, the Baseline. Self-contained loop; the
live-fetch path is untouched. Makes local re-runs instant and avoids tripping
the gov API's per-IP rate limit (6000 req / 5 min) during iteration.
- EpcClientService.REQUEST_TIMEOUT 10s -> 30s: a cold per-UPRN search can exceed
10s and the old timeout turned it into a timeout-then-retry; 30s rides it out.
Note: an open perf question remains — modelling is fast in isolation (<0.5s/
property) but a long-lived --persist run shows ~1 min/property; suspected in the
persist path (plan.save / baseline) or connection handling, NOT the API. Left
mid-diagnosis for handover.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Make run_modelling_e2e the single script that does everything for a portfolio,
so the 291-property run needs one invocation with per-property recovery (no
all-or-nothing chunking):
- On --persist, a lodged-EPC Property now also gets its Baseline Performance
row written via PropertyBaselineOrchestrator (per Property, so one bad cert
does not abort the batch). Predicted (EPC-less) Properties have no lodged
figures, so they get a Plan but no baseline row.
- The run CSV gains api_sap (register) vs baseline_sap (calculator) + sap_delta,
so calculator-vs-API divergence is reviewable per property.
Fill the off-catalogue overlay for the measures the live material catalogue
cannot price, so they stop crashing the run:
- double_glazing (£550/window) and secondary_glazing (£400/window): priced
per window (the generator multiplies by single-glazed window count, matching
the legacy window_glazing). Grounded in 2025/26 UK installed costs; per-window
is the right unit for windows (fixed per-unit install dominates) — per-m2 fits
walls/floors, not glazing.
- gas_boiler_upgrade / system_tune_up / system_tune_up_zoned: these are priced
off the heating rate sheet (Products()), with get() reading the catalogue only
for an id — so the overlay entry exists to satisfy that lookup (material_id
stays None, as with ASHP); the rate sheet remains authoritative.
Validated on a 12-property sample (incl. a secondary-glazing case and a
SAP-Schema-16.2 cert): 12/12 baseline rows + plans, 0 errors.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Two-pass org_ref-matched builder for property_overrides (classify via ChatGPT
into the landlord ledger, validate+apply user edits, write idempotently);
ephemeral-Postgres smoke proves the one-property chain without creds.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The FE-owned `material.type` pgEnum cannot carry `secondary_heating_removal`,
so pricing it through the DB catalogue raises a DataError that poisons the
session — the modelling pipeline crashed on any property with a lodged
secondary heater unless the measure was excluded on the Scenario.
Realise the `ProductRepository` docstring's intent (DB catalogue today, a JSON
file for costs the ETL does not yet supply, behind the same port): add a
`CompositeProductRepository` that resolves an override source first, then the
catalogue. Checking the override first keeps that Measure Type away from the DB
entirely; every other type misses the override and falls through unchanged.
- off_catalogue_costs.json prices it at £270 flat per-dwelling — the legacy
`Costs.heater_removal` ported to the new flat model (ADR-0028):
(£25 + £200 baseline) x 1.2 VAT, for the single fixed secondary a cert lodges.
Contingency (0.25) is joined from config, not the file.
- Wire the composite into PostgresUnitOfWork.product and run_modelling_e2e, so
the first-run pipeline and the local runner both honour the overlay.
- Integration test: drop the unrealistic seeded secondary_heating_removal DB
rows (the pgEnum can't hold the type) and assert it is JSON-sourced
(material_id is None, cost £270) end-to-end through a real Unit of Work.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
`profile_corpus_error.py` and `dive_cert.py` compared our PE/CO2 against
the lodged EPC figures using the UK-average RATING cascade, but the EPC
lodges CO2/PE on the postcode DEMAND cascade (SAP 10.2 Appendix U p.124,
now wired into Sap10Calculator.calculate in fc7c4d2d). That confounded the
DEMAND-vs-COST triage: a cert whose demand actually reproduced on local
weather looked "PE off" purely from the climate difference and was
mislabelled DEMAND-side. Switching the PE/CO2 lens to `cert_to_demand_
inputs` (SAP still from the rating cascade) re-classifies the corpus
outside-0.5 set 261/42 -> 211/92 DEMAND/COST — ~50 certs are genuinely
cost-side (e.g. 10091578598: SAP +7.81 but PE +1.6 / CO2 -0.04). Sharpens
the hunt for the subtle widespread SAP term.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
profile_corpus_error.py buckets signed SAP error by raw-API feature and
lists worst over/under-raters with the PE/CO2-vs-cost split (COST-side vs
DEMAND-side triage). dive_cert.py dumps one cert's lodged-vs-ours
SAP/CO2/PE + full intermediate line refs + mapped inputs. Both run on the
committed RdSAP-21.0.1 corpus (no /tmp sample needed). Used to find the
stone-wall, per-part-roof, ground-floor-flat and HP-water fixes this session.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
scripts/run_first_run_e2e.py runs the real Ingestion -> Baseline -> Modelling
pipeline against the DB by composing build_first_run_pipeline + dispatch_first_run
with the live source clients (the Lambda handler can't run locally — its
_source_clients_from_env still raises, #1136). Unlike run_modelling_e2e it runs
real ingestion (persists EPC/spatial/solar) and has no inspect-only mode, so it's
gated behind --confirm (preview otherwise); measure scoping comes only from the
Scenario's exclusions (the pipeline threads no --measures), and the modelling
batch is all-or-nothing, both documented.
Extract the shared env/engine/S3 plumbing into scripts/e2e_common.py (public
load_env/build_engine/s3_parquet_reader) so both runners share one source and
neither imports the other's privates.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The new pipeline left no per-Property record of a run (the old engine set
property.has_recommendations and populated property_details_epc). Restore the
marker: PropertyRepository.mark_modelled sets has_recommendations (true when the
Plan carries measures, mirroring the old engine) and bumps updated_at, so a
first-run under the new process is identifiable as updated_at >= 2026-06-01.
ModellingOrchestrator marks each Property after its Scenarios (true if any
Scenario yielded a measure); run_modelling_e2e's --persist path marks it too
(its compute runs on in-memory fakes, so the DB UoW sets it directly). Adds the
has_recommendations/updated_at columns to the PropertyRow mirror.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Every worklist UPRN now carries schema · engine SAP / lodged · flag. Tally:
64 healthy, 19 MVHR-not-credited (🚩 flag B), 6 heat-pump fuel-39 (🚩 flag A),
4 sparse/NOT MAPPABLE (⛔), 3 Elmhurst-pinned. MVHR is the largest accuracy gap.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Autonomous-run triage of the moderate eng-vs-lodged gaps resolves them into two
patterns, both flagged for owner review (not auto-fixable):
- Heat-pump fuel code 39 mis-priced as gas (over-rates; both gap directions).
- MVHR heat recovery modelled as plain extract loss → systematic UNDER-rating
(~8-12 SAP) on every full-SAP cert carrying a mechanical_vent_system_index_number.
New memory mvhr-heat-recovery-not-modelled; needs the Appendix Q / PCDB MVHR
efficiency model.
findings doc updated with the classification.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
