Adds the user-simulated 001431 case (the cert that drove S0380.189/.190)
as an Elmhurst-only e2e fixture: Summary PDF → extractor → mapper →
calculator, every Block-1 SapResult field pinned against the
P960-0001-001431 worksheet at abs=1e-4. All 11 pins pass with zero
residual — the case is clean, confirming the S0380.190 gas-combi fuel
derivation closes the Summary path natively.
Verified the handover's flagged "+0.0007 SAP" was a target artifact, not
a cascade gap: the worksheet displays ECF (257) rounded to 1.6047 and
integer SAP (258)=78; the cascade's continuous SAP is computed from the
UNROUNDED ECF = (255)*(256)/((4)+45) = 660.9750*0.4200/173.0, giving
77.6147 — which matches the worksheet's own unrounded value. Pinning the
continuous SAP from the display-rounded ECF (→ 77.6144) was the wrong
target. Block-1 line refs all match exactly: (211) 10699.7225, (219)
3327.1592, (231) 86.0, (232) 283.2229, (255) 660.9750, (272) 3000.1664,
Σ(98) 8987.7669.
Summary mirrored into the tracked fixtures dir as
Summary_001431_gas_combi.pdf (distinct name — the corpus reuses cert
001431 across every heating variant); source Summary + worksheet tracked
under sap worksheets/golden fixture debugging/ as the pin ground truth.
2302 passed (+11), 0 failed; pyright net-zero on new/changed files.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The newer Elmhurst Summary export lodges a gas combi as §14.0 "Fuel Type"
empty + "Main Heating SAP Code" 104 (EES "BGW"), with no fuel string. The
site-notes mapper left `main_fuel_type=''`, so `cert_to_inputs` raised
`MissingMainFuelType` — blocking the whole gas-combi Summary path
(reproduced on the simulated 001431 case).
SAP 10.2 Table 4b (PDF p.168) rows 101-119 are "Gas boilers (including
mains gas, LPG and biogas)": the code fixes the boiler type/efficiency but
NOT the carrier, so 104 alone can't distinguish mains gas from LPG. The
disambiguator is §15.0 "Water Heating Fuel Type" — a combi/boiler heats
space + water from one appliance — exactly mirroring the existing
liquid-fuel (codes 120-141) fallback. `_elmhurst_gas_boiler_main_fuel`
adopts the §15.0 carrier only when the SAP code is in 101-119 AND §15.0
resolves to a gas/LPG fuel, so a regular boiler + electric immersion
(§15.0 = "Electricity") still strict-raises rather than mis-billing gas
as electric.
2291 passed (+1), 0 failed; pyright net-zero on both files.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The §7 mean-internal-temperature cascade hardcoded the thermal mass parameter
(TMP) to 250 kJ/m²K at all 5 call sites, ignoring construction. RdSAP 10
§5.16 Table 22 (PDF p.48) makes TMP construction-dependent:
100 kJ/m²K — timber frame, cob, park home (regardless of internal
insulation); OR masonry (stone/solid brick/cavity/system
built) WITH internal insulation.
250 kJ/m²K — masonry WITHOUT internal insulation.
A too-high TMP inflates the §7 time constant τ = Cm/(3.6·H) (e.g. 40 h vs
16 h), under-cuts the temperature reduction between heating periods, and
over-states mean internal temperature → over-states space heating.
`_thermal_mass_parameter_kj_per_m2_k(epc)` classifies the MAIN building's
wall via the RdSAP `wall_construction` codes (5/7/8 = timber/cob/park) and
`wall_insulation_type` codes (3/7 = internal); unknown/curtain fall back to
the masonry 250 (no regression on unlisted classes). 17-case parametrised
test covers every Table 22 branch.
Diagnosis (per-line walk vs the user-simulated 001431 worksheet, same
archetype as golden cert 6035): fabric (26-37), internal gains (73), climate
(96)m and HTC (39) all EXACT; the entire +8.78 PE / -1.76 SAP gap was §7 MIT
(92) +0.71 °C, traced to TMP 250 vs Table 22's 100 (solid brick WITH internal
insulation). Fix closes the simulated case to 1e-4 on PE and CO2.
Blast radius: only golden cert 6035 re-pins (solid brick + internal
insulation) — SAP resid -6 → -2, PE +46.42 → +19.16, CO2 +1.07 → +0.42. The
47 dr87 cohort, 6 U985 fixtures and 41-variant heating corpus are all
masonry-no-internal → TMP unchanged at 250, all still pass. 2290 pass
(+17 new), 0 fail; pyright net-zero.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
SAP 10.2 Appendix M1 §3a (p.93) defines PV-eligible demand as
D_PV,m = E_L,m + E_A,m + E_cook,m + E_ES,m + (231)·n_m/365 + E_space,m + E_water,m
where E_L,m is the lighting ELECTRICITY (Appendix L eq L10, = line (232)).
The cascade fed `internal_gains_result.lighting_monthly_w` — the L12 internal
heat GAIN G_L,m = E_L,m × 0.85 ("assuming 15%" of lighting energy does not
become internal heat) — into D_PV, understating it by 15% of lighting on
every PV cert. That depressed the monthly β onsite/export split and
under-credited PV primary energy uniformly across the year.
Same gain-vs-electricity class as the cooking fix S0380.73 (L18 gain vs L20
electricity). Fix: scale the (shape-identical) lighting gain profile to the
annual E_L `lighting_kwh_per_yr` (= (232)), mirroring the (219)m hot-water
scale-to-annual. Magnitude-only, so the shape-weighted lighting CO2/PE
effective factor (Σkwh×f/Σkwh, magnitude-invariant) is unchanged; appliances
need no scaling (G_A = E_A, no 0.85). Diagnosis was empirical first (calc
lighting D_PV 95.1 vs worksheet (232) 111.88, ratio exactly 0.85) then
confirmed against the spec text (L9d/L10/L12, M1 §3a).
Impact (calc − full-precision dr87 worksheet): ALL 47 worksheet certs now
match at <1e-4 on BOTH PE (max |Δ| 0.0000 kWh/m²) and CO2 (max |Δ| 0.0000 kg)
— the convergence target, met cohort-wide. Combined with S0380.187 this
closes the entire gas+PV + ASHP PV residual. Re-pinned 47 worksheet residuals
to 0.0000 and 31 drifted lodged residuals (PV certs). SAP integers unchanged;
chain SAP 1e-4 intact (164 pass). 2273 pass, 0 regressions; pyright net-zero.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The PV onsite/export β-split (SAP 10.2 Appendix M1 §3a, p.93) divides PV
generation by the monthly PV-eligible electricity demand D_PV,m. The cascade
included main and water electricity (when those fuels are electric) but had
no term for SECONDARY space heating. For the 10 cohort-2 gas-main +
electric-secondary + PV certs, the (215)m secondary electric fuel was dropped
from D_PV,m — understating demand in the heating months only, depressing the
monthly β, and under-crediting onsite PV primary energy.
Spec: Appendix M1 §3a counts E_space,m as the dwelling's TOTAL electric
space-heating demand; for a gas-main/electric-secondary dwelling that is the
secondary fuel. Diagnosis was decisive: E_PV (generation) matched the
worksheet exactly every month, the onsite (233a) split diverged ONLY in
heating months (Jun-Sep near-exact), and all 10 affected certs have PV while
all clean gas certs have none. Empirically adding (215)m to D_PV closed cert
3136 onsite 726.9 → 790.3 (worksheet 792.1).
Impact (calc − full-precision dr87 worksheet), the 10 certs:
PE +0.5..+1.5 → +0.02..+0.046 kWh/m²; CO2 −0.5..−1.1 → +0.002..+0.0095 kg.
The whole 47-cert cohort now matches at PE <0.05 / CO2 <0.025. SAP integers
unchanged; chain SAP 1e-4 pins intact (164 pass). The uniform ~0.03 PE remnant
on PV certs is the separate (233a)/(233b) summer-month D_PV discrepancy.
Re-pinned the 10 worksheet + 9 lodged golden residuals (improvements).
2273 pass, 0 regressions; pyright net-zero (file's 32 errors pre-existing).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The existing golden test compares calc PE/CO2 against the integer-rounded
lodged register values (energy_consumption_current / co2_emissions_current),
which conflates real calculator gaps with register rounding. This adds a
parallel pin against each cert's Elmhurst dr87 worksheet (286)/(272) at full
precision — a clean calculator-vs-Elmhurst signal for the 47 worksheet-backed
certs (9 ASHP + 38 cohort-2).
Findings at capture (calc − worksheet, on the worksheet's own decimal TFA):
- 37/47 exact on both PE (<0.05 kWh/m²) and CO2 (<0.02 kg).
- 10 higher-consumption gas certs carry PE +0.5..+1.5 kWh/m² AND
CO2 -0.5..-1.1 kg simultaneously. PE-over + CO2-under on the same
certs is the fingerprint of a small gas→electricity fuel-split
difference (elec PE 1.51 > gas 1.13, but elec CO2 0.136 < gas 0.21),
not a factor-value error — next slice candidate.
An earlier "41/47 PE gaps" reading was a JSON-integer-TFA division artifact;
comparing on the worksheet's decimal TFA (which the calculator also uses)
collapses it to the real 10. Worksheet values frozen as literals (the dr87
PDFs are untracked, so not parsed at test time) per the worksheet_unrounded_sap
convention. Also replaced a pre-existing pytest.approx with abs-diff to keep
the file at zero pyright errors (feedback_abs_diff_over_pytest_approx).
106 passed (was 59); pyright 0 errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
SAP 10.2 worksheet block 12b/13b (367)/(467) for a community heating
electric heat pump (Table 4a code 304 → Table 12 fuel 41 "heat from
electric heat pump"). The HP meters grid electricity, so per Table 12
note (s)/(t) + block 12b/13b footnote (a) its emission/PE factor is the
MONTHLY Table 12d/12e cascade (fuel 41 = standard-electricity profile),
weighted by the network heat profile, then × 1/heat-source-eff (1/COP):
(367)/(467) = [(307)+(310)] / COP × Σ((307+310)_m × factor_m)/Σ(...)
Per-line walk of CH3 (the displayed (367) 0.1535 / (467) 1.5717 are PDF
artifacts; the (373)/(473) totals reconcile only with):
CO2 factor = 0.15040 (monthly Table 12d wtd) vs cascade annual 0.136
PE factor = 1.55692 (monthly Table 12e wtd) vs cascade annual 1.501
Pre-slice the cascade routed code 304 through the non-electric branch
(`_co2_factor_kg_per_kwh(main) × 1/COP` = annual × scaling). New
`_is_heat_network_electric_main` (heat-network main whose fuel has a
Table 12d monthly set — i.e. fuel 41) routes all four factor helpers
(main + HW, CO2 + PE) through the monthly cascade × 1/COP. Non-electric
heat networks (gas 51 / oil 53 / coal 54) have no monthly set → annual
path unchanged (CH1, CH6 untouched).
Closure (CH3 was already SAP+cost EXACT):
CH3 (HP/Elec) CO2 −75.32→+0.0000 (= [(307+310)/3]×(0.1504−0.136)),
PE −249.32→−0.0000 (× (1.5569−1.501)) — FULLY EXACT
Corpus now 40/41 EXACT on all four metrics. Only CH6 remains: its
worksheet lodges a manual DLF=1.0 ("two adjoining dwellings") absent
from the Summary PDF (byte-identical to CH4 bar fuel type) — an
architectural limit, not a cascade gap. 2226 pass + 1 skip + 0 fail
(tolerances 1e-4 all metrics); pyright net-zero 43→43.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
SAP 10.2 worksheet block 12b (CO2) / 13b (PE) for community heating
"CHP and boilers" (SAP code 302). Per unit of network heat fuel
H = (307)+(310) the effective generation factor is:
chp×100/(362)×f_fuel − chp×(361)/(362)×f_disp + (1−chp)×100/(367)×f_fuel
(363)/(463) CHP fuel = chp_frac × 100/heat_eff × f_fuel
(364)/(464) less credit = −chp_frac × elec_eff/heat_eff × f_disp
(368)/(468) boiler fuel = (1−chp_frac) × 100/boiler_eff × f_fuel
f_fuel = Table 12 heat-network fuel factor (the CHP unit and the back-up
boilers burn the same community fuel — verified vs CH2 gas / CH4 oil /
CH6 coal worksheets (363)/(368)); f_disp = Table 12f (PDF p.196) credit
for the CHP-generated electricity. RdSAP 10 §C (p.58) defaults: heat eff
50% (362), electrical eff 25% (361), boiler eff 80% (367); CHP heat frac
0.35 per-cert via community_heating_chp_fraction.
New `_heat_network_code_302_effective_factor` + Table 12f flexible
constants (0.420 CO2 / 2.369 PE) + RdSAP §C efficiency constants, wired
into all four factor helpers (main + HW, CO2 + PE) ahead of the existing
single-fuel / 1-over-heat-source-eff path. The worksheet (368)/(468)
boiler emissions DISPLAY rounded/mis-aligned in the PDF, but the
(373)/(473)/(386)/(486) totals reconcile only with the boiler at the
full Table 12 factor — verified EXACT.
Two spec citations applied:
- Table 12f flexible-operation default for RdSAP community CHP is an
Elmhurst engine choice (Table 12f notes make "standard" the default);
mirrored per [[feedback-software-no-special-handling]] and documented
in SAP_CALCULATOR.md §8.3.
- Table 12 heat-network oil/biodiesel CO2 (codes 53/56) corrected
0.298 → 0.335 per Table 12 (p.189) "assumes 'gas oil'"; the code-302
oil cascade (CH4) was the first to exercise it. PE 1.180 was already
correct. No other variant uses these codes (no regression).
Closures (CO2 + PE only — the CHP credit does not touch cost/SAP):
CH2 (CHP/Gas) CO2 −1411.49→+0.0000, PE +1331.23→+0.0000 EXACT
CH4 (CHP/Oil) CO2 −4378.24→−0.0000, PE +319.81→−0.0000 EXACT
CH6 (CHP/Coal) CO2/PE re-pinned (+2411.54 / +5023.48) — its worksheet
lodges a manual DLF=1.0 the Summary doesn't carry, so
cascade DLF=1.45 over-scales H; same root as the CH6
SAP −7.49 / cost +£172 (separate DLF front).
CH2/CH4 are now CO2+PE-exact but still carry the heat-network cost/SAP
residual (+0.5277 SAP / −£12.16 cost, exposed by S0380.175 — cost-side,
untouched here). CH3 unchanged (code 304 community-HP COP front).
Corpus state: 37 variants EXACT on all four metrics (incl. CH1);
remaining residuals are CH2/CH4 cost+SAP, CH3 CO2+PE (HP COP), CH6
all-metric (DLF quirk). 2223 pass + 1 skip + 0 fail (tolerances 1e-4 all
metrics per S0380.181); pyright net-zero 43→43.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
SAP 10.2 Appendix C §C3.2 (PDF p.51), verbatim: "CO2 emissions and
Primary Energy associated with the electricity used for pumping water
through the distribution system are allowed for by adding electrical
energy equal to 1% of the energy required for space and water heating."
Worksheet line (313) = 0.01 × [(307)+(310)]; its CO2 (372) and PE (472)
bill on the Table 12d/12e monthly factors for fuel code 50 ("electricity
for pumping in distribution network"), weighted by the monthly heat
profile per worksheet footnote (a). (307)m/(310)m = (space_demand +
hw_output) / efficiency (the cascade models a heat network's generator
efficiency as 1/DLF).
This un-defers the (372)/(472) front the post-S0380.179 handover flagged
"don't guess until the factor source is identified": the source is
§C3.2 + Table 12d/12e code 50, NOT an empirical constant. The apparent
0.1994/0.2114 "factor" is an Elmhurst DISPLAY artifact — the worksheet
shows the (372) energy column as 0.01×(307) (space only) while computing
emissions on 0.01×(307+310) per the §C3.2 text. Verified EXACT line-by-
line against the CH2 corpus worksheet: (372)=23.6007 CO2 (rating),
(472)=208.2267 PE (demand).
New `_heat_network_distribution_electricity` helper (gated on
`_is_heat_network_main`) precomputes the energy + effective CO2/PE
factors; three new CalculatorInputs fields + calculator.py CO2/PE
summation terms (0.0/None → no-op for individually-heated certs).
Closures:
CH1 (Boilers/Gas) CO2 −23.60→−0.00, PE −208.23→+0.00 — FULLY EXACT
CH3 (HP/Elec) CO2 −98.92→−75.32, PE −457.54→−249.32 (distribution
component closed; code-304 community-HP COP remains)
CH2/CH4/CH6 gain their (372)/(472) component (CO2 +23.6, PE
+208.2); dominant CHP displaced-electricity credit
residual (Table 12f + block 12b/13b) is next slice.
No regression on the other 36 corpus variants (helper returns None off
heat-network mains) + golden + U985 fixtures. 2223 pass + 1 skip + 0
fail; pyright net-zero 43→43.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The calculator tests lived under domain/sap10_calculator/{tests,worksheet/
tests,rdsap/tests,climate/tests,validation/tests}, none of which are in
pytest.ini testpaths — so CI (which collects tests/) never ran them. Relocate
all five dirs to tests/domain/sap10_calculator/{,worksheet,rdsap,climate,
validation}, mirroring the tests/domain/property_baseline/ convention, so the
cascade-pin / golden / e2e conformance suites run in CI.
Mechanics:
- git mv preserves history (110 files).
- Flattening the trailing /tests keeps each file's depth-to-repo-root
identical, so all 16 repo-root parents[4] fixture refs stay valid. Only
test_pcdb_etl.py's parents[1] (→ pcdb data) and one hardcoded absolute
golden-fixture path in test_cert_to_inputs.py needed rebasing.
- Cross-imports rewritten domain.sap10_calculator.worksheet.tests →
tests.domain.sap10_calculator.worksheet (21 files incl. the external
importer backend/documents_parser/tests/test_summary_pdf_mapper_chain.py).
- Golden-fixture path strings in test_summary_pdf_mapper_chain.py +
scripts/fetch_cohort2_api_jsons.py updated to the new location (the JSONs
moved with the rdsap tests).
load_cells / gitignored worksheet xlsx: the xlsx-pinned tests (test_dimensions
/ ventilation / water_heating) read 2026-05-19-17-18 RdSap10Worksheet.xlsx,
which is gitignored (.gitignore `*.xlsx`) and so absent in CI. _xlsx_loader.
load_cells now pytest.skip()s when the file is absent, so those tests run
locally and skip cleanly in CI instead of erroring — no new CI failures from
the move, and the gitignore policy is respected.
Verified: tests/domain/sap10_calculator + backend/documents_parser +
tests/domain/property_baseline = 2248 pass, 1 skipped; pyright resolves the
new import paths with zero import-resolution errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
ADR-0014 BillDerivation prices a per-end-use EnergyBreakdown
(HEATING / HOT_WATER / LIGHTING / PUMPS_FANS / APPLIANCES / COOKING).
SapResult already carried the first four but not appliances or cooking,
so a downstream SapResult→EnergyBreakdown adapter had to stub those two
at 0 kWh — understating the bill by the whole unregulated electricity
load. Surface them so the property_baseline side can wire the sections.
Adds two output-only fields to CalculatorInputs + SapResult, threaded
exactly like lighting_kwh_per_yr:
appliances_kwh_per_yr — SAP 10.2 Appendix L L13/L14/L16a annual E_A
(sum of the §5 (68) monthly appliances kWh)
cooking_kwh_per_yr — SAP 10.2 Appendix L L20 (p.91) ELECTRICITY
estimate E_cook = 138 + 28×N
Both values already existed in cert_to_inputs.py (appliances_monthly_kwh,
cooking_monthly_kwh) — reused, not recomputed.
Fuel attribution: cooking_kwh_per_yr is the L20 ELECTRICITY figure (the
field docstring says so), distinct from the L18 cooking heat GAIN
(35 + 7N W) the §5 internal-gains cascade uses. The bill adapter should
treat cooking as an electricity carrier; a gas-cooker split, if ever
needed, is a separate follow-up.
HARD CONSTRAINT honoured — output-only, zero rating drift. Appliances +
cooking are unregulated and are NOT fed into ECF / total_fuel_cost /
CO2 / primary energy / sap_score. Every golden-fixture, Elmhurst e2e
SapResult pin, section cascade pin, and heating-corpus residual stays
byte-identical (1165 rated pins green). The synthetic CalculatorInputs
fixtures set the new fields non-zero on purpose so the existing cost/PE
reconciliation assertions act as leak detectors.
New focused test asserts both fields are populated (non-zero) and
threaded unchanged onto SapResult, with cooking equal to the L20
electricity figure (138 + 28×occupancy) to 1e-9. pyright net-zero
111 → 111.
Note: 11 pre-existing failures in test_appendix_u.py / test_table_32.py
arrived with the recently absorbed PR and are unrelated to this change
(they fail identically on the clean branch); flagged separately.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
PR feedback: prefer an abstract base the calculator inherits from over a
structural Protocol. Define `SapCalculator(ABC)` in the calculator package
(the engine owns its own contract) and have `Sap10Calculator` inherit it;
a future methodology is another subclass. Placing the ABC with the engine —
not in property_baseline — keeps the dependency pointing consumer -> engine
(sap10_calculator imports nothing from property_baseline). Consistent with
the repo's existing port convention (FuelRatesRepository(ABC)).
CalculatorRebaseliner keeps its reference to SapCalculator type-only (under
TYPE_CHECKING), so the module still does not import the calculator at
runtime. Test fakes now inherit the ABC since structural conformance no
longer applies.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 5a: the promotion. Replaces StubRebaseliner in production and collapses the
shadow runner into the rebaseliner (ADR-0013 amendment).
- CalculatorRebaseliner runs Sap10Calculator on every Property:
* sap_version < 10.2 -> Effective Performance IS the calculator output
(band via Epc.from_sap_score, CO2 kg->t, PEUI rounded), reason "pre_sap10".
* sap_version >= 10.2 -> Effective = lodged (API figures on-target), and the
calculator only logs divergence (SAP>0.5, PEUI/CO2 1%) as a validation signal.
* a calculator raise propagates -> batch aborts (ADR-0012); fix the cert at once.
- Rebaseliner.rebaseline gains property_id (for the divergence log).
- LoggingCalculatorShadow / the calculator_shadow seam removed from the
orchestrator; its divergence-comparison logic now lives in the rebaseliner.
- StubRebaseliner kept (signature updated) for orchestrator/repo unit tests.
The SapResult->EnergyBreakdown adapter + BillDerivation wiring (to populate the
bill block) follow once the appliances/cooking SapResult fields land.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 3 of Bill Derivation. sap_code_to_fuel(code) maps a SAP 10.2 / Table 32
fuel code to the canonical billing Fuel — bounded to the ~47 Table 32 codes (the
carrier, orthogonal to the PCDB product index, so all PCDB heat pumps share one
electricity code). Mains gas / LPG / oil+bioliquids / coal / smokeless / wood /
electricity (standard + off-peak) / heat-network groupings; an unmapped code
(dual fuel, grid-export) raises UnmappedSapCode rather than guessing.
Also: ADR-0014 deferred/TODO section records the stubbed appliances+cooking
(pending the SapResult fields), the off-peak day/night split, the heat-network
rate gap, and regional rates / ETL.
The SapResult -> EnergyBreakdown adapter (next slice) is gated on the
appliances/cooking fields landing on SapResult.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 2 of Bill Derivation. BillDerivation(fuel_rates).derive(breakdown) takes a
delivered-energy breakdown (per-section EnergyLine(section, fuel, kwh) +
exported_kwh) and produces a Bill: per-section kWh + cost, standing charges,
SEG credit, and total.
- Each end-use line billed at its fuel's unit rate.
- Standing charge added ONCE per distinct fuel used (a meter, not an end use);
off-gas fuels carry 0 so contribute nothing — no metered/unmetered special case.
- SEG export credit subtracted.
- Deterministic (ADR-0006); raises UnpricedFuel (via FuelRates) on an unpriced
fuel (e.g. heat network) rather than billing at a wrong default.
Pure domain — no calculator dependency; the SapResult->EnergyBreakdown adapter
is slice 3.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Slice 1 of Bill Derivation — the reference-data foundation that later slices
price the calculator's per-end-use kWh against:
- Fuel enum (canonical billing fuels; the join key between the calculator's
SAP-code fuels and the rates snapshot). COAL + HEAT_NETWORK are members with
no national rate.
- FuelRates value object: unit_rate_p_per_kwh / standing_charge_p_per_day /
seg_export_p_per_kwh; raises UnpricedFuel on a fuel it has no rate for rather
than billing at a wrong default.
- FuelRatesRepository port (ADR-0011 Repo-reads-stored-reference-data) +
StaticFileFuelRatesRepository reading a committed JSON snapshot.
- Snapshot fuel_rates_2026_q2.json: GB national, Apr-Jun 2026 Ofgem cap
(gas/electricity) + DESNZ/NEP May 2026 (off-gas). Carries the full researched
data; the value object exposes single-rate fuels this slice. Off-peak
(day/night), house coal and heat network raise UnpricedFuel until later slices.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Wire Sap10Calculator into PropertyBaselineOrchestrator as a non-load-bearing
shadow runner. For each property it scores the Effective EPC beside the
load-bearing Lodged/Effective write, catches any strict-raise -> log.error
(never aborts the batch), and on success log.warning's divergence from Lodged:
SAP |continuous - lodged| > 0.5; PEUI/CO2 > 1% relative (CO2 after kg->tonnes).
Every line is tagged with sap_version so SAP-10.2 signal separates from
older-spec drift (ADR-0010 Validation Cohort).
Per ADR-0013, Calculated SAP10 Performance is not a persisted third value-set:
effective = calculated in every baselining scenario, so the calculator IS the
mechanism that produces Effective Performance (the Rebaseliner). It runs in
shadow only while being hardened; when overrides/estimation land it is promoted
to drive Effective and the failure posture flips to abort (ADR-0012, calculator
now load-bearing). No table change.
- ADR-0013 + CONTEXT (Calculated SAP10 Performance / Effective Performance /
Rebaselining) record the decision.
- CalculatorShadow port + LoggingCalculatorShadow + Calculator protocol.
- FakeCalculatorShadow for orchestrator unit tests.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This branch's objective is the SAL ingestion handler
(applications/SAL/handler.py) and its dependency tree. Drop work
that crept in but is unreferenced by it:
- EPC feature: domain/epc, infrastructure/epc (gov_uk + historical
clients), tests/infrastructure/epc
- datatypes/epc edits (instantaneous_wwhrs Optional) reverted to main
- asset_list/app.py local data-file/column tweak reverted to main
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Aligns the composition with its entry point (the `ara_first_run` lambda +
`AraFirstRunTriggerBody`): clearer what the file does.
- orchestration/first_run_pipeline.py → ara_first_run_pipeline.py
- FirstRunPipeline → AraFirstRunPipeline; FirstRunCommand → AraFirstRunCommand
- test files renamed to match
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Final slice of ADR-0012: collapse the per-property read round-trips a batch
made (Baseline hydrated ~8 queries x 30 properties one at a time) into a
handful of per-table IN queries.
- EpcPostgresRepository: extracted a shared `_compose(rows)` from `get` (the
windows + floor-dim fetches are now passed in, not fetched inline), so both
`get` and the new `get_for_properties(property_ids)` build EpcPropertyData
from pre-fetched rows. `get_for_properties` fetches each child table once
(`WHERE epc_property_id IN ...`), groups in memory, and composes — load-whole
per ADR-0002.
- PropertyRepository.get_many(property_ids) -> Properties: one query for the
property rows + one bulk EPC hydration, composed in input order.
- BaselineOrchestrator / IngestionOrchestrator read the batch via get_many
instead of N x get.
- Ports + fakes gain the bulk methods.
The #1129 round-trip fidelity test stays green (the compose extraction is
behaviour-preserving). New tests: bulk hydration correctness + round-trips are
constant w.r.t. batch size (one-per-table, proven by query count). 123 pass;
pyright strict clean; AAA.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Replaces the handler's whole-pipeline Session (one transaction across all
three stages, connection pinned during Ingestion's external IO) with a
Unit-of-Work per stage (ADR-0012, added here). Each stage runs its batch in
one unit and commits once; any property raising aborts the batch and the
subtask fails noisily.
- BaselineOrchestrator(unit_of_work, rebaseliner): one unit for the batch,
commit once. Raise on a pre-SAP10 property leaves the unit uncommitted.
- IngestionOrchestrator(unit_of_work, epc_fetcher, geospatial_repo,
solar_fetcher): fetch/write split — phase 1 fetches the whole batch (EPC /
coords / solar) with NO unit open; phase 2 writes in one unit and commits.
The connection is never held during external IO. Geospatial S3 repo stays
injected (reference data, not transactional).
- Handler: module-scoped engine (pool reused across warm invocations) + a UoW
factory; whole-pipeline `with Session` gone. `build_first_run_pipeline`
composes on the factory. Source clients still behind the raising seam.
- ADR-0012 records the decision (per-stage boundary, all-or-nothing batch,
idempotent re-run, fetch/write split, module-scoped engine). Modelling stub
left untouched (no-op, no DB) per the ADR.
Tests: orchestrators on a shared FakeUnitOfWork (assert persisted batch +
exactly-once commit + no-commit-on-raise). New real-DB E2E integration test:
real PostgresUnitOfWork, Ingestion writes the EPC → Baseline reads it back
through the repo → re-run replaces, not duplicates (1 EPC row, 1 baseline row
after two runs). 121 pass in tests/; pyright strict clean; AAA.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Re-runs of a First Run batch re-save a property's data; that must replace,
not duplicate (ADR-0012 idempotent batch writes).
- `EpcPostgresRepository.save` deletes the property's existing EPC graph
(parent + all child tables, floor-dims via their building parts) before
inserting, when a `property_id` is given. Anonymous saves still insert.
- `BaselinePostgresRepository.save` deletes the existing row for the
`property_id` before inserting — no more unique-constraint violation on
re-save; also what the re-score-on-override path needs.
- Solar already upserts, so it's unchanged.
The #1129 round-trip fidelity test stays green (delete-first is a no-op on
a first save). 2 new tests (re-save replaces, not duplicates). pyright
strict clean; AAA.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
First slice of the per-stage batch-transaction refactor (ADR-0012). A
UnitOfWork is the single transaction a stage runs its batch in: a context
manager exposing the DB repos bound to one session, committing once on
`commit()` and rolling back on exception or exit-without-commit
(all-or-nothing per batch, fail noisily).
- `UnitOfWork` (port): `property` / `epc` / `solar` / `baseline` repos +
`commit()` / `rollback()`; `__exit__` rolls back uncommitted work.
- `PostgresUnitOfWork(session_factory)`: opens a Session from an injected
factory (a module-scoped engine + sessionmaker in prod, so the pool is
reused across warm invocations), binds the Postgres repos to it, closes
on exit.
Not yet wired into any orchestrator — that lands in the Baseline /
Ingestion refactor slices. 3 tests against ephemeral PG (commit durable
across units; exception rolls back; no-commit persists nothing). pyright
strict clean; AAA.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Completes the First Run spine. Replaces the #1130 stub FirstRunPipeline
with the real three-stage composition and wires it into the handler.
- `FirstRunPipeline.run(command)` sequences Ingestion → Baseline →
Modelling, threading **only** `property_ids` between stages (and
`scenario_ids` into Modelling, off the command — never a prior stage's
output). Stages are injected behind thin `IngestionStage` /
`BaselineStage` / `ModellingStage` Protocols (the EpcFetcher/SolarFetcher
idiom), so the handler owns wiring and tests substitute fakes (ADR-0011).
- `ModellingOrchestrator` stub + `ScenarioRepository` / `MaterialsRepository`
seam ports — `run(property_ids, scenario_ids)` reads through repos, does
no scoring yet. Method shapes deferred to the Modelling per-service grills
(Scenario / Scenario Phase / Snapshot / Optimised Package / Plans are rich
— not pre-empted here).
- Handler delegates to the real pipeline via `build_first_run_pipeline`
(Postgres-backed repos off the session). The Ingestion source clients
(EPC API / Google Solar / geospatial S3) are isolated behind one
`_source_clients_from_env` seam that raises until the deploy/Terraform
config settles — out of scope for this slice. Subtask complete/failed +
CloudWatch URL still come from `@subtask_handler`.
Integration test (the criterion's centrepiece): wires REAL Ingestion +
REAL Baseline + stub Modelling through a shared fake EPC repo, with a
repo-backed PropertyRepo composing the Property from that slice. Proves
Baseline reads the very EPC Ingestion persisted — the through-repos
hand-off, no in-memory coupling. Plus a composition test pinning stage
order + only-property_ids threading.
TDD, one test → one impl. pyright strict clean; AAA layout. 116 pass in
the tests/ tree, no regressions.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Stage 2 of First Run. Establishes each Property's Baseline Performance
from persisted source data and writes it back — reads only from repos,
never a Fetcher or HTTP (ADR-0003), so it is byte-identical whether
Ingestion ran milliseconds ago or last week.
Domain (`domain/baseline/`):
- `Performance` VO — the four rated quantities: SAP / EPC Band / CO2 /
Primary Energy Intensity. `lodged_performance(epc)` reads them off the
EPC's recorded fields (PEUI = `energy_consumption_current`).
- `BaselinePerformance` (ADR-0004) — the paired `lodged` + `effective`
Performance + `rebaseline_reason`, plus the no-derivation part of the
energy block (`space_heating_kwh` / `water_heating_kwh`, off the RHI,
deterministic per ADR-0006). Both halves always populated.
- `Rebaseliner` port + `StubRebaseliner`: the re-score-on-override seam
(ADR-0011). SAP10 certs pass through (effective == lodged, reason
"none"); a pre-SAP10 cert raises `RebaselineNotImplemented` rather
than fabricating a plausible-but-wrong "none" — ML rebaselining is not
wired yet. Mirrors the repo's strict-raise culture.
Persistence: new `BaselineRepository` port + `BaselinePostgresRepository`
+ flat-column `baseline_performance` SQLModel (one row per Property). Per
ADR-0004's amendment this is a standalone table, NOT columns on the
retiring `property_details_epc`. Production migration is FE-owned
(Drizzle) — docs/migrations/baseline-performance-table.md.
Docs (grill-with-docs): corrected CONTEXT.md Lodged/Effective Performance
to Primary Energy Intensity (the term collided with its own _Avoid_ entry
under "heat demand") + fixed stale RHI field names; amended ADR-0004
Consequences for the standalone-table decision.
Fuel split + bills (rest of EPC Energy Derivation) deferred to a
follow-up — they need a Fuel Rates source (Ofgem-cap ETL) that does not
exist yet.
TDD, one test -> one impl: 7 tests (lodged read, rebaseliner pass-through
+ raise, orchestrator establish-and-persist + pre-SAP10 raise, Postgres
round-trip + absent). pyright strict clean; AAA layout.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Stage-2 entry point for the First Run use case. Adds the
`ara_first_run` Lambda package mirroring the `postcode_splitter`
template, its typed trigger contract, and a stub `FirstRunPipeline`.
- `AraFirstRunTriggerBody`: thin command of five fields — `task_id`,
`sub_task_id` (UUID, lifecycle), `portfolio_id`, `property_ids`,
`scenario_ids` (int business IDs). No `model_config` override, so
Pydantic's default `extra="ignore"` lets the FastAPI backend add
fields without breaking deployed lambdas. UPRNs / Scenario defs are
deliberately off the event — read from source-of-truth tables.
- Thin `handler.py`: validate-and-delegate only, via a named
`dispatch_first_run` seam (testable without the Lambda runtime).
Subtask status (in-progress/complete/failed) + CloudWatch log URL
come for free from the existing `@subtask_handler()` decorator.
- `FirstRunPipeline` (orchestration/) stub: `run(command)` receives the
validated command. Declares a structural `FirstRunCommand` Protocol
(the three business fields) that `AraFirstRunTriggerBody` satisfies,
so orchestration needs no application-layer import — rhymes with the
`EpcFetcher`/`SolarFetcher` Protocols on IngestionOrchestrator
(ADR-0011). Full Ingestion→Baseline→Modelling composition lands in
#1136.
- Dockerfile / requirements.txt / local_handler/ mirror postcode_splitter.
TDD: 7 new tests (trigger-body validation incl. forward-compat +
id-types, pipeline seam, handler delegation). pyright strict clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Stage 1 of the pipeline: per property, read its UPRN from the property row,
fetch its EPC, resolve coordinates from the Geospatial reference repo, thread
those into the Solar fetcher, and persist EPC + solar via repos. Fetchers never
call each other — the orchestrator threads the coordinate (ADR-0011). Coordinates
are reference data (deterministic from UPRN), resolved transiently to drive the
solar fetch rather than persisted per-property.
Depends on thin EpcFetcher/SolarFetcher Protocols (EpcClientService and
GoogleSolarApiClient satisfy them structurally). Unit-tested against fakes — no
DB, gov API, or network: persists EPC, threads coords into solar, skips
UPRN-less properties and skips solar when coordinates are absent. pyright clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add Coordinates value object + GeospatialRepository port + GeospatialS3Repository
adapter. Resolves a Property's lon/lat from the partitioned Ordnance Survey
Open-UPRN parquet (filename_meta -> partition -> UPRN row). A Repo, not a
Fetcher (ADR-0011): no live OS API call. The parquet reader is injected, so it's
unit-tested against fixture parquets with no S3/network; returns None when the
UPRN is uncovered or absent. pyright strict clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Move the EpcClientService package (client + _retry + exceptions + tests) from
the dying backend/ tree to infrastructure/epc_client/ as the New-EPC-API Fetcher;
update the two callers (address2UPRN, a script). All 14 client tests pass.
Add SolarRepository port + SolarPostgresRepository persisting Google Solar
building insights as JSONB (solar_building_insights table), one row per Property.
The EPC repo half of this slice already landed in #1129. pyright strict clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add the Ara modelling aggregate root (ADR-0002): domain/property/ with
PropertyIdentity, SiteNotes, Property, Properties. Property.source_path
implements the two disjoint source paths + Recency Tie-Break (ADR-0001;
survey wins on an equal date); effective_epc resolves to the surveyed data
(Site Notes path) or the public EPC (epc_with_overlay path — Landlord
Overrides overlay is a later slice). Pure dataclasses, no infrastructure imports.
PropertyRepository port + PropertyPostgresRepository hydrate the aggregate
whole from a defensive view of the FE-owned 'property' table (identity columns)
plus the EPC slice via EpcRepository.get_for_property. Reads only from repos
(ADR-0003). 8 domain + 1 hydration test; pyright strict clean.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Add epc_renewable_heat_incentive table (space_heating_kwh, water_heating_kwh +
the three insulation-impact kWh fields), wired into EpcPostgresRepository
save/get. This is the P0 gap: RenewableHeatIncentive carries the baseline
space-heating/hot-water kWh that EPC Energy Derivation consumes.
The round-trip test now asserts full deep-equality (dropped the
renewable_heat_incentive exclusion) and passes for RdSAP 21.0.0 + 21.0.1.
DB migration for the new table documented in
docs/migrations/epc-property-round-trip-fidelity.md.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Relocate EpcPropertyModel + child tables from the dying backend/ tree to
infrastructure/postgres/epc_property_table.py (re-export shim keeps
documents_parser working). Add EpcRepository port + EpcPostgresRepository with
a full reverse mapper (epc_property tables -> EpcPropertyData).
Round-trip test surfaced two fidelity gaps:
1. Union[int,str] SAP code fields were str()-coerced on save, losing the int
(API) vs str (Site Notes) distinction. Now stored as JSONB (type-preserving).
2. The schema was a partial projection. Closed the cheap gaps on the model
(heating shower/bath counts, roof_construction_type, curtain_wall_age,
addendum, mechanical_vent_duct_insulation_level, SAP 10.2 §2 ventilation
fields + a ventilation_present flag). Structural gaps tracked as follow-ups;
renewable_heat_incentive (P0, #1137) excluded from the assertion until landed.
Round-trip passes for RdSAP-Schema-21.0.0 and 21.0.1; pyright strict clean.
Migration inventory for the DB: docs/migrations/epc-property-round-trip-fidelity.md
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
