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Khalim Conn-Kowlessar d8a3702902 Slice 69: 1:1 windows expansion in cohort 000474 (5 → 7 entries) 
Closes the `sap_windows: LEN 7 vs 5` divergence by replacing the
cohort hand-built's glazing-type-collapsed 5-window encoding with 7
SapWindow entries mirroring the Summary §11 1:1 — the same row
breakdown the Elmhurst mapper extracts. Per-window curtain-transform
U_eff aggregates to the same total as before:

  Group g=0.72/U=2.0: 6.22 m² across 4 rows (was 3 rows × wider W)
  Group g=0.76/U=2.8: 5.50 m² across 3 rows (was 2 rows × wider W)

Cascade output is unchanged — all 11 cohort 000474 SapResult pins
remain GREEN at 1e-4. The per-bp window apportionment from Slice 59
(`_window_bp_index` in heat_transmission_from_cert) handles both the
prior int-zero `window_location` and the new "Main"/"Nth Extension"
str locations the mapper surfaces; cohort 000474 has uniform per-bp
wall U so the apportionment is heat-loss-invariant either way.

Surfaces a previously-hidden gap: now that the LEN matches, the
diff test reveals **49 per-window sub-field divergences** between
the cohort `make_window` helper (API-style int codes for
`glazing_type`, `window_type`, `window_wall_type`, `glazing_gap`,
`data_source`, bool `permanent_shutters_present`, None
`frame_factor`) and the Elmhurst mapper (Summary-style strings for
the same fields + `frame_factor=0.7`).

That's the next chunk to address — most likely path: normalise the
Elmhurst mapper to produce API-style int codes for the window
descriptive fields, so both mappers produce the same dataclass
shape. The cascade reads `window_transmission_details.u_value` /
`solar_transmittance` + `window_width` × `window_height` +
`orientation` + `window_location` — none of the descriptive
divergences listed above affect SAP output.

Diff count: 1 → 49 (surface, not regression). Cohort cascade pins
green; pyright 0 errors on the fixture.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-25 17:04:38 +00:00
..
domain Slice 69: 1:1 windows expansion in cohort 000474 (5 → 7 entries) 2026-05-25 17:04:38 +00:00
fetchers added potential file scaffolding: 2026-05-15 10:56:53 +00:00
repos added potential file scaffolding: 2026-05-15 10:56:53 +00:00
utils added potential file scaffolding: 2026-05-15 10:56:53 +00:00
README.md added potential file scaffolding: 2026-05-15 10:56:53 +00:00

README.md

Shared packages

Workspace packages consumed by services/*. Each package is its own Python distribution with its own pyproject.toml; services import via the workspace dependency mechanism ({ workspace = true }).

Package Purpose
domain/ Shared domain types — Property, BaselinePerformance, Plan, Scenario, EpcPropertyData, etc. No persistence, no IO, no business logic.
repos/ Persistence layer — one repo per aggregate. Owns the SQL. Depends on domain.
fetchers/ External API clients (gov EPC, Ofgem, Google Solar, etc.). Depend on domain for response shapes.
utils/ Cross-cutting infra — logging, S3, CloudWatch URL builders, SQS task helpers.

Adding a new shared package

Only when a real second consumer materialises. Don't pre-shatter (repos-epc, repos-property, ...) — split when a deployment needs to drop a dep, not before.

See ../ara_backend_design.md §11 for the broader monorepo layout and ../CONTEXT.md for the domain glossary that names the types living in domain/.