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Extract per-Property row construction behind a shape helper 🟪
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Khalim Conn-Kowlessar
parent
9c1e79efc6
commit
65fb4fabad
1 changed files with 58 additions and 59 deletions
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@ -180,66 +180,65 @@ class ExportSheet:
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rows: tuple[dict[str, Any], ...]
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_COLUMNS: tuple[str, ...] = (
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_ID_COLUMNS + _ALL_MEASURE_COLUMNS + _SAVINGS_COLUMNS + _TOTAL_COLUMNS + _PLAN_COLUMNS
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)
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def _shape_row(prop: PropertyScenarioData) -> dict[str, Any]:
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"""One Property's wide row: identity + Effective-EPC descriptive fields, the
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measures pivoted onto their cost columns, the savings rolled up, and the
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Plan's post-works figures (ADR-0065)."""
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row: dict[str, Any] = {
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"property_id": prop.property_id,
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"landlord_property_id": _blank(prop.landlord_property_id),
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"uprn": _blank(prop.uprn),
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"address": _blank(prop.address),
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"postcode": _blank(prop.postcode),
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"property_type": _blank(prop.property_type),
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"walls": _blank(prop.walls),
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"roof": _blank(prop.roof),
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"floor": _blank(prop.floor),
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"windows": _blank(prop.windows),
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"heating": _blank(prop.heating),
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"hot_water": _blank(prop.hot_water),
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"lighting": _blank(prop.lighting),
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"total_floor_area": _blank(prop.total_floor_area),
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"number_of_rooms": _blank(prop.number_of_rooms),
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"lodgement_date": _blank(prop.lodgement_date),
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"is_expired": _blank(prop.is_expired),
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"current_epc_rating": _blank(prop.current_epc_rating),
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"current_sap_points": _blank(prop.current_sap_points),
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}
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# Every measure column is present, blank unless this Property has it, so all
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# scenario sheets share one contract (ADR-0065).
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for column in _ALL_MEASURE_COLUMNS:
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row[column] = ""
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for measure in prop.measures:
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column = _measure_column(measure)
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if column in _ALL_MEASURE_COLUMNS:
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row[column] = measure.estimated_cost
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# Roll the selected measures' attributed impact up to the Property.
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row["sap_points"] = _sum([m.sap_points for m in prop.measures])
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row["co2_equivalent_savings"] = _sum([m.co2_equivalent_savings for m in prop.measures])
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row["kwh_savings"] = _sum([m.kwh_savings for m in prop.measures])
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row["energy_cost_savings"] = _sum([m.energy_cost_savings for m in prop.measures])
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row["total_retrofit_cost"] = _sum([m.estimated_cost for m in prop.measures])
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# The default Plan's post-works figures, passed through as persisted.
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row["post_sap_points"] = _blank(prop.post_sap_points)
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row["post_epc_rating"] = _blank(prop.post_epc_rating)
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row["cost_of_works"] = _blank(prop.cost_of_works)
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row["contingency_cost"] = _blank(prop.contingency_cost)
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row["co2_savings"] = _blank(prop.co2_savings)
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row["energy_bill_savings"] = _blank(prop.energy_bill_savings)
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row["energy_consumption_savings"] = _blank(prop.energy_consumption_savings)
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row["valuation_increase"] = _blank(prop.valuation_increase)
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return row
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def shape_scenario_sheet(
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properties: Sequence[PropertyScenarioData],
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) -> ExportSheet:
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"""Shape one Scenario's Properties into a wide export sheet (ADR-0065)."""
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columns: tuple[str, ...] = (
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_ID_COLUMNS
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+ _ALL_MEASURE_COLUMNS
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+ _SAVINGS_COLUMNS
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+ _TOTAL_COLUMNS
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+ _PLAN_COLUMNS
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)
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rows: list[dict[str, Any]] = []
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for prop in properties:
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row: dict[str, Any] = {
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"property_id": prop.property_id,
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"landlord_property_id": _blank(prop.landlord_property_id),
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"uprn": _blank(prop.uprn),
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"address": _blank(prop.address),
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"postcode": _blank(prop.postcode),
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"property_type": _blank(prop.property_type),
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"walls": _blank(prop.walls),
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"roof": _blank(prop.roof),
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"floor": _blank(prop.floor),
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"windows": _blank(prop.windows),
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"heating": _blank(prop.heating),
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"hot_water": _blank(prop.hot_water),
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"lighting": _blank(prop.lighting),
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"total_floor_area": _blank(prop.total_floor_area),
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"number_of_rooms": _blank(prop.number_of_rooms),
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"lodgement_date": _blank(prop.lodgement_date),
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"is_expired": _blank(prop.is_expired),
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"current_epc_rating": _blank(prop.current_epc_rating),
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"current_sap_points": _blank(prop.current_sap_points),
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}
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# Every measure column is present, blank unless this Property has it, so
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# all scenario sheets share one contract (ADR-0065).
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for column in _ALL_MEASURE_COLUMNS:
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row[column] = ""
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for measure in prop.measures:
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column = _measure_column(measure)
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if column in _ALL_MEASURE_COLUMNS:
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row[column] = measure.estimated_cost
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# Roll the selected measures' attributed impact up to the Property.
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row["sap_points"] = _sum([m.sap_points for m in prop.measures])
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row["co2_equivalent_savings"] = _sum(
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[m.co2_equivalent_savings for m in prop.measures]
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)
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row["kwh_savings"] = _sum([m.kwh_savings for m in prop.measures])
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row["energy_cost_savings"] = _sum(
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[m.energy_cost_savings for m in prop.measures]
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)
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row["total_retrofit_cost"] = _sum([m.estimated_cost for m in prop.measures])
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# The default Plan's post-works figures, passed through as persisted.
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row["post_sap_points"] = _blank(prop.post_sap_points)
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row["post_epc_rating"] = _blank(prop.post_epc_rating)
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row["cost_of_works"] = _blank(prop.cost_of_works)
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row["contingency_cost"] = _blank(prop.contingency_cost)
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row["co2_savings"] = _blank(prop.co2_savings)
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row["energy_bill_savings"] = _blank(prop.energy_bill_savings)
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row["energy_consumption_savings"] = _blank(prop.energy_consumption_savings)
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row["valuation_increase"] = _blank(prop.valuation_increase)
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rows.append(row)
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return ExportSheet(columns=columns, rows=tuple(rows))
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rows = tuple(_shape_row(prop) for prop in properties)
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return ExportSheet(columns=_COLUMNS, rows=rows)
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