The printed "candidate measures considered" now matches what the
orchestrator actually offered — on 711795 the lodged cavity wall printed
a cavity-fill candidate the plan (timber-frame effective wall) never saw.
Co-Authored-By: Claude Opus 4.8 <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>
- 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>
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>
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>
Routes run_modelling through prop.effective_epc and dumps each target's
property_overrides before the run, so a landlord wall override moves the
calculated SAP. Records the overlay design in ADR-0032.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Update run_modelling_e2e's docstring so another dev can run it: the Scenario's
exclusions drive measure scoping (--measures/--exclude-measures are overlays),
and flag the secondary_heating_removal catalogue gap that currently requires
--exclude-measures. Replace the stale --measures examples with the real
scenario-driven inspect/persist commands.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The measures a run considers should come from the Scenario, not a CLI flag.
The live scenario table persists exclusions only (no inclusions column), as a
Postgres text-array of exact MeasureType values.
- Scenario gains `exclusions: frozenset[MeasureType]` + `considered_measures()`
(all measures minus the excluded ones, or None when none are excluded).
- ScenarioModel.to_domain parses the `{a,b,c}` exclusions array into
MeasureTypes, raising on a token that is not an exact MeasureType value
(no high-level category expansion), per the strict-enum convention.
- ModellingOrchestrator._plan_for derives the allowlist from the Scenario's
exclusions, combined (intersection) with any explicit considered_measures
override via the new `combine_considered_measures`.
- run_modelling_e2e sources the allowlist from the Scenario; --measures /
--exclude-measures become optional overlays (e.g. the technical
secondary_heating_removal exclusion the catalogue cannot yet stock).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The run only showed the measures the Optimiser selected, so a candidate it
passed over (e.g. an ASHP it found too costly for the target band) and that
measure's cost were invisible.
Add `harness.console.candidate_recommendations` — every Generator Option
with its per-Option cost, before optimisation — and have run_modelling_e2e
print the full menu per property (flagging the selected Options), write a
"cost per measure" section into the markdown, and emit a per-Option
modelling_e2e_candidates.csv.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
`restrict_to_considered_measures` filtered candidates only *after* every
generator had run, so an excluded measure still queried the catalogue.
That crashed properties with a lodged secondary heater: the live
`material.type` enum has no `secondary_heating_removal` value, so the
query raised a psycopg2 `InvalidTextRepresentation` before the allowlist
could drop it.
`_candidate_recommendations` now pairs each generator with the measure
types it can emit and runs it only when the allowlist admits one of them
(None = all), so an excluded measure never reaches the catalogue.
`restrict_to_considered_measures` still trims disallowed Options off the
multi-Option survivors. Add `--exclude-measures` to run_modelling_e2e
(allowlist minus the excluded set) for excluding one measure without
enumerating the rest.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The new gov EPC API (api.get-energy-performance-data..., Bearer auth) returns
403 "Bad authentication header" with EPC_AUTH_TOKEN but 200 with
OPEN_EPC_API_TOKEN — the token name is misleading (it is the Bearer token for
the new API, not the open-data API). Verified live against
/api/domestic/search. Unblocks the live EPC fetch in run_modelling_e2e.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 5 (local run sources the DB, read-only) + slice 6 (optional persist),
landing together as one script rewrite (the persist path is interleaved with
the compute path).
The same local computation now runs whether or not the result is stored:
- Both modes price against the live `material` catalogue (read-only
ProductPostgresRepository over one shared Session) and model against a real
Scenario read from the DB (--scenario-id; its goal_value drives the band,
rejected if null) — so the inspected recommendations are exactly what gets
stored. The JSON sample catalogue is no longer used by this script.
- --measures restricts the run to a comma-separated considered_measures
allowlist (e.g. high_heat_retention_storage_heaters,solar_pv).
- --persist writes the inputs (EPC + spatial + solar) and the *same* computed
Plan via the production repos in one PostgresUnitOfWork, then commits
(idempotent: PlanPostgresRepository replaces by (property_id, scenario_id)).
Gated: --persist requires --scenario-id and --portfolio-id. Default is
inspect-only — no DB writes.
harness.console.run_modelling gains `products` and `scenario` overrides (the
seam the script drives); defaults unchanged, so existing callers are
unaffected. Suite 257 pass + 3 xfail; pyright clean; --help/guard/measure
parsing verified. Not yet executed against the DB (awaiting property_ids +
write-confirm).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Per Property the inspection script now resolves the UPRN's spatial
reference from the Ordnance Survey Open-UPRN parquet in S3
(GeospatialS3Repository over a boto3 ParquetReader) and threads both
levers into run_modelling:
- planning_restrictions: the conservation/listed/heritage flags that gate
the wall + solar measures (ADR-0019/0020).
- solar_insights: a live Google Solar buildingInsights fetch keyed on the
reference coordinates, so the Solar PV Options can fire (ADR-0026).
Mirrors IngestionOrchestrator._fetch's coords->solar flow. Degrades
gracefully per Property: a UPRN S3 doesn't cover -> unrestricted/no-solar;
a point Google has no coverage for (BuildingInsightsNotFoundError) ->
no-solar; both still modelled. --no-solar skips the Google leg. A context
note (restrictions; solar) is printed and written to the md/csv summary.
Verified live: spatial_for + solar fetch round-trip on real UPRNs (S3 via
ambient ~/.aws creds, pyarrow reads parquet bytes). pyright clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Revives the local recommendation-inspection flow for specific Properties.
`scripts/run_modelling_e2e.py` reads each Property's UPRN from the DB
(read-only), fetches the latest EPC live from the gov EPC API by UPRN, runs the
Modelling stage in memory (all Generators → Optimiser → costed, attributed
Plan), and prints a per-Property plan table + writes a Markdown/CSV summary.
Persists nothing — purely for inspection.
The local DB's Properties have no linked ingested EPC (epc_property.property_id
is NULL for all rows; Ingestion's source clients are stubbed, #1136), so the
EPC must be fetched inline rather than read back. Builds the connection from the
`DB_*` env vars in backend/.env and the EPC token from `EPC_AUTH_TOKEN`.
Threads optional solar insights through harness `run_modelling` (so Solar PV
Options can fire once coordinates are wired) and adds the `solar_pv` catalogue
row. Solar + planning restrictions + DB persistence are noted follow-ups.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
