Fitting sealed glazing units changes two things beyond the pane's U/g
that the cascade reads, which the overlay didn't model — leaving the
double/secondary before→after pins ~0.7 SAP short (xfail):
1. Draught-proofing (RdSAP 10 §8.1). Sealed units draught-proof the panes
they replace, re-lodging the dwelling-level `percent_draughtproofed`
(cert 001431: 84 → 100). The §2 cascade reads that dwelling-level
value, so the overlay now carries it. `_recompute_percent_draughtproofed`
anchors on the lodged before-% — `after = round((round(before%/100 × N)
+ flips) / N × 100)`, N = openable windows (vertical + roof) + doors,
flips = upgraded panes that were not draught-proofed — so it's robust
to incomplete window extraction (unchanged openings are already in the
aggregate). ~0.3 SAP.
2. Frame factor (§6 solar gains). A replacement unit re-lodges its own
FF=0.70, overriding the pane it replaced — the two "single glazing,
known data" panes lodge FF 1.00 / 0.50 (one is 6.6 m²), so leaving them
unchanged understated solar gains by ~+150 kWh space heating. `WindowOverlay`
now carries `frame_factor`, written flat onto the window. ~0.4 SAP.
Wiring: `EpcSimulation.percent_draughtproofed` + `WindowOverlay.frame_factor`
new fields; `apply_simulations` / `_fold_window` write them; the glazing
generator computes both from the upgraded set and cert 001431's after.
Un-xfails `test_{double,secondary}_glazing_overlay_reproduces_the_relodged_after`
— both now pin SAP/CO2/PE to the relodged after within tolerance. Updates
the two `test_glazing_recommendation` overlay expectations for the new
`frame_factor`. 96 modelling tests pass; zero new pyright errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Comment out the remaining workflows to cut GitHub Actions usage, per request:
- integration_tests.yml — rebaselining integration suite (PRs to main)
- deploy_fastapi_backend.yml — FastAPI backend deploy (push to dev/prod);
deploys must be run manually via `sls deploy` while disabled
- protect_releases.yml — main→dev PR-source guardrail
Fully commented (not deleted) so each restores by uncommenting.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Comment out the Docker-based unit-test workflow — it was consuming too many
GitHub Actions minutes. Fully commented (rather than deleted) so it can be
restored by uncommenting.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
37 modelling_e2e properties failed on the 2026-06-23 run with
`NotNullViolation: null value in column "wet_rooms_count" of relation
"epc_property"`.
Root cause: 21.0.1 lodges `wet_rooms_count` as Optional, and
`from_rdsap_schema_21_0_1` passed it straight through
(`wet_rooms_count=schema.wet_rooms_count`). A cert omitting it mapped to
`EpcPropertyData.wet_rooms_count=None`. When a predicted EPC (which deep-copies
a comparable template's EpcPropertyData) inherited that None and was persisted,
it violated the `epc_property.wet_rooms_count` NOT-NULL column — and the calc's
`wet_rooms_count > 0` check would also raise `TypeError` on None.
Fix: coalesce to 0, matching every other mapper (RdSAP "not lodged" → the
calc's minimum 1 wet room). Regression test added.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Skipped cohort certs were previously surfaced only as outputs.result on a
completed subtask, so they were easy to miss. Treat them as a failure too:
once the batch has run to completion (so every modellable property is already
written to DB), raise if there were any per-property errors OR any skipped
certs. The run gets flagged for debugging without discarding the work done.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
When a property failed, the handler recorded only its bare property_id and
raised RuntimeError("failed property_ids: [...]"). That string is what
SubTask.fail persists into the subtask outputs.error column, so a failed run
told you which property failed but never why — forcing a CloudWatch lookup.
The per-property catch now captures property_id, uprn, error_type, and the
error message, and the raised RuntimeError embeds those as JSON so the subtask
outputs column is parseable directly. query_failed_modelling_e2e.py reads that
outputs.error into a new Error column in its report.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A predicted Property (no lodged EPC) got a Plan but nothing else: the synthesised
EPC was never written to epc_property, and Baseline Performance was skipped — so
property 729529 (portfolio 796 / scenario 1268), predicted from its DA16 1QZ
cohort, was "missed" with no predicted-EPC row and no baseline row.
Persist the synthesised EPC in the predicted slot (uow.epc.save(..., source=
"predicted"), ADR-0031) inside the Plan UoW, then run the Baseline orchestrator
for predicted Properties too — it re-hydrates the predicted EPC and establishes
the baseline from it. The earlier "lodged only" guard is dropped: by the write
block the Property always has a persisted EPC (lodged or predicted); one that
could be neither fetched nor predicted raised earlier.
Verified against the DB by invoking the real handler for 729529: predicted
epc_property rows 0->1 and property_baseline_performance rows 0->1. Baseline on
the predicted picture builds cleanly (RHI present, reason pre_sap10). Tests
updated: prediction + broadening paths now assert the predicted-slot epc.save and
the baseline run.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The handler wrote epc/spatial/solar/plan and marked the property modelled, but
never established its Baseline Performance — so no row was created in
property_baseline_performance for any property modelled through the Lambda
(noticed on portfolio 796 / scenario 1268 / property 727218, a lodged property).
Mirror the e2e runner: after the plan UoW commits (so the EPC is persisted for
the orchestrator to re-hydrate), run PropertyBaselineOrchestrator for lodged
properties. Predicted properties have no lodged figures and no persisted EPC, so
they are skipped — consistent with the e2e runner and the ara_first_run Baseline
stage.
Verified 727218's baseline pipeline builds end-to-end in-memory (lodged_performance
→ CalculatorRebaseliner → bill → PropertyBaselinePerformance, reason pre_sap10).
Tests: lodged path asserts the orchestrator runs once; prediction path asserts it
does not.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A Landlord Override's building_part is a positional index (0=main, 1=extension
1…, ADR-0004), but the gov-API EPC can label that slot differently (e.g. lodge
the 2nd part as 'other', not 'extension_1'). The previous fix skipped such
orphaned overrides, silently discarding the landlord's correction. Now the
override falls back onto the EPC's part at that position (via _resolve_part), so
the correction lands; only a position the EPC models no part at is skipped
(no geometry to model a wholly-absent part). Replaces the skip-only behaviour.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Closes out the cohort-broadening work with its decision record and consolidates
the retry plumbing.
ADR-0034 documents broadening the EPC-Prediction cohort to the real unit
postcodes nearest the target (via postcodes.io) when its own postcode holds no
same-type comparable — extending ADR-0031 decision 5. Records why postcodes.io
was chosen over council[] (whole-LA, no property_type in rows), a bulk Code-Point
Open / ONSPD dataset, and the OS Places radius API, and the lazy / nearest-first
early-stop / soft-fail policy. Broadening-specific docstrings now cite 0034.
Retry consolidation: extract the EPC client's call_with_retry into a shared
infrastructure/http_retry.py keyed off a generic TransientHttpError marker, so
the mechanism (exponential backoff, Retry-After) is shared while each client
keeps its own transient policy. EpcRateLimitError now subclasses TransientHttpError
(still an EpcApiError); PostcodesIoClient routes through the same helper, raising
TransientHttpError on 429/5xx and soft-failing to the seed once exhausted (the EPC
client propagates instead). Direct tests for the shared helper; EPC + postcodes.io
suites repointed at the shared sleep.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Two reconciliations to make the modelling_e2e Lambda handler production-ready.
1. Price through the off-catalogue overlay, drop the workarounds
The handler priced through a plain ProductPostgresRepository and excluded
secondary_heating_removal / system_tune_up / system_tune_up_zoned to dodge
ProductNotFound (and a poisoning pgEnum DataError). Those measures are now
priced by catalogue_with_off_catalogue_overrides (already used by the e2e
runner and PostgresUnitOfWork), so the exclusions are removed and ALL measure
types are considered. This also fixes gas-boiler / single-glazed properties,
which Dan's handler never excluded and so still crashed (the standard
system_tune_up option is built unconditionally — the considered-measures
exclusion never actually gated it).
2. Broaden the EPC-Prediction cohort to nearby real postcodes (ADR-0031)
A property with no lodged EPC and no same-type comparable in its own postcode
(e.g. the only flat among houses) used to gate out and fail the subtask. The
gov EPC API cannot search by radius/outcode, so we resolve the real unit
postcodes physically nearest the target via postcodes.io (keyless; already a
trusted in-repo dependency) and walk them nearest-first until enough same-type
comparables surface. New PostcodesIoClient (transient-failure retry with
exponential backoff, soft-failing to the seed so broadening never breaks
prediction) and EpcComparablePropertiesRepository.candidates_near. Wired into
the handler and e2e runner; broadening is lazy (only on gate-out) and memoised
per (postcode, property_type).
Validated live: property 728476 (gas boiler) prices system_tune_up at GBP295;
property 718580 (lone flat in BR6 6BS) now predicts via nearby BR6 postcodes.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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>
tests/orchestration/test_postcode_splitter_orchestrator.py imports
`from moto import mock_aws` (moto 5.x) but moto was absent, so the file
errored at collection. Pin moto[s3,sqs]==5.0.28 (S3+SQS are the only mocked
services); resolves cleanly against the boto3 1.35.44 and cryptography 43.0.3
pins. All 4 tests pass.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
@task_handler never built or passed cloud_logs_url, so every app using
it (incl. modelling_e2e) ran run_subtask with the None default and the
CloudWatch deep-link was never saved onto the SubTask. @subtask_handler
did this correctly.
Extract the URL builder into a shared utilities/aws_lambda/cloud_logs.py
(public cloudwatch_url()), use it from both handlers, and pass the URL
into run_subtask from @task_handler. Add regression tests.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A Landlord Override can reference a building part the lodged or predicted EPC
never carried (e.g. an extension_1 override on a property whose EPC has only
main). apply_simulations indexed parts_by_id[identifier] unguarded, raising
KeyError and aborting the whole property's modelling. Now the orphaned part is
skipped. Recovers 14 of the 22 modelling_e2e failures in portfolio 796.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
@task_handler never built or passed cloud_logs_url, so every app using
it (incl. modelling_e2e) ran run_subtask with the None default and the
CloudWatch deep-link was never saved onto the SubTask. @subtask_handler
did this correctly.
Extract the URL builder into a shared utilities/aws_lambda/cloud_logs.py
(public cloudwatch_url()), use it from both handlers, and pass the URL
into run_subtask from @task_handler. Add regression tests.
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>
Closes the mapper-coverage gaps surfaced by the modelling_e2e prediction-cohort
failures (portfolio 796):
- built_form (SAP-16.0): derive from dwelling_type in _normalize_sap_schema_16_x
(Mid-terrace->4, End-terrace->3, Semi-detached->2, Detached->1; flats->modal 4).
ML-only field (SAP calc never reads it) so SAP- and gate-neutral. 5 flat certs
that omitted built_form now map.
- photovoltaic_supply as a measured-array LIST: routed all pre-21 RdSAP mappers
(17.0/17.1/18.0/19.0/20.0.0) through _map_schema_21_pv, whose list branch is now
dict-tolerant (_pv_array_field reads dict OR dataclass). They capture the PV
arrays like 21.0.x instead of raising "'list' object has no attribute
none_or_no_details" and sinking the whole cohort.
- windows-as-dict (16.x): handled in the normalizer (not just windows-as-list).
Genuinely-sparse certs (omit door_count/habitable/glazed_area) remain fail-loud;
the gate-regressing multiple_glazed_proportion default and the recursive
RdSAP-21.0.0 ADR-0028 alignment are left fail-loud + flagged for review (worklist).
+5 regression tests; component-accuracy gate 26/26; 0 new pyright errors.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
