Goal-aligned dispatch reads one enum-keyed table 🟪

Review findings on PR #1527:

- The 'which goals are goal-aligned' set lived in two adjacent if-chains
  (_objective_for and _require_budget_for_goal_aligned) that had to stay in
  sync — a new goal-aligned goal added to one but not the other would slip
  the budget guard. Both now read a single _GOAL_ALIGNED_OBJECTIVES table.
- The goal strings are the canonical PortfolioGoal enum values, not
  re-declared string constants, so goal-value drift can't silently degrade
  a goal to max-SAP; _target_sap reads the enum too.
- _scored_candidate_groups takes objective without a default (its only
  caller passes it).
- scoring.py: 'cached: float | None' -> Optional[float] per the CLAUDE.md
  'Use Optional over | None' rule.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

domain/modelling/scoring/scoring.py

@@ -15,7 +15,7 @@ truthful. The whole-package re-score (role 2) is `PackageScorer.score` directly.
 """
 
 from dataclasses import dataclass
-from typing import Callable, Sequence
+from typing import Callable, Optional, Sequence
 
 from datatypes.epc.domain.epc_property_data import EpcPropertyData
 from domain.modelling.scoring.package_scorer import PackageScorer, Score
@@ -99,7 +99,7 @@ def independent_option_signals(
     scored: list[tuple[EpcSimulation, float]] = []
     signals: list[float] = []
     for option in options:
-        cached: float | None = next(
+        cached: Optional[float] = next(
             (signal for overlay, signal in scored if overlay == option.overlay),
             None,
         )

orchestration/modelling_orchestrator.py

@@ -26,6 +26,7 @@ from domain.modelling.scoring.package_scorer import PackageScorer, Score
 from domain.modelling.plan import Plan, PlanMeasure
 from domain.modelling.recommendation import MeasureOption, Recommendation
 from domain.modelling.generators.roof_recommendation import recommend_roof_insulation
+from domain.modelling.portfolio_goal import PortfolioGoal
 from domain.modelling.scenario import Scenario
 from domain.modelling.scoring.scoring import (
     MeasureImpact,
@@ -50,14 +51,6 @@ from repositories.product.product_repository import ProductRepository
 from repositories.solar.solar_repository import SolarRepository
 from repositories.unit_of_work import UnitOfWork
 
-# The PortfolioGoal value that targets a SAP band (cf.
-# backend.app.db.models.portfolio.PortfolioGoal.INCREASING_EPC). The
-# goal-aligned goals (ADR-0062) set no target: they maximise their own metric
-# within the Scenario budget.
-_INCREASING_EPC_GOAL: Final[str] = "Increasing EPC"
-_REDUCING_CO2_GOAL: Final[str] = "Reducing CO2 emissions"
-_ENERGY_SAVINGS_GOAL: Final[str] = "Energy Savings"
-
 # Best-practice install sequence for the role-3 attribution cascade (ADR-0016):
 # walls → roof → ventilation → floor, per the legacy `Recommendations` class.
 # Ventilation sits after the fabric that triggers it so its (negative) marginal
@@ -405,7 +398,7 @@ def _scored_candidate_groups(
     planning_restrictions: PlanningRestrictions,
     solar_potential: Optional[SolarPotential],
     considered_measures: Optional[frozenset[MeasureType]],
-    objective: Callable[[Score], float] = sap_rating,
+    objective: Callable[[Score], float],
 ) -> list[list[ScoredOption]]:
     """One group per Recommendation: each Option scored independently against
     the baseline (role-1 warm-start signal, ADR-0016), in the goal objective's
@@ -438,20 +431,6 @@ def _scored_candidate_groups(
     return groups
 
 
-def _require_budget_for_goal_aligned(scenario: Scenario) -> None:
-    """A goal-aligned Scenario is 'reduce as much as possible within this
-    budget' — undefined without one (unconstrained, it would recommend every
-    beneficial measure). Fail the misconfiguration loudly (ADR-0062)."""
-    if scenario.budget is None and scenario.goal in (
-        _REDUCING_CO2_GOAL,
-        _ENERGY_SAVINGS_GOAL,
-    ):
-        raise ValueError(
-            f"scenario {scenario.id} has goal {scenario.goal!r} but no budget; "
-            "goal-aligned scenarios require a budget"
-        )
-
-
 def _carbon_reduction(score: Score) -> float:
     """The Reducing-CO2 objective: annual kg CO2 below zero-point, negated so
     higher is better (a saved kg scores +1)."""
@@ -470,23 +449,50 @@ def _bill_saving(bill_derivation: BillDerivation) -> Callable[[Score], float]:
     return objective
 
 
+# The goal-aligned goals (ADR-0062): each maximises its own metric within the
+# Scenario budget and sets no SAP target. One table is the single source of
+# "which goals are goal-aligned" — both the objective dispatch and the
+# budget-required guard read it, so a new goal-aligned goal cannot be added to
+# one without the other. Each entry builds its objective from the plan's
+# BillDerivation (the carbon objective ignores it; the bill objective needs it).
+# A goal absent from the table optimises SAP, as every goal did before.
+_GOAL_ALIGNED_OBJECTIVES: Final[
+    dict[str, Callable[[BillDerivation], Callable[[Score], float]]]
+] = {
+    PortfolioGoal.REDUCING_CO2_EMISSIONS.value: lambda _bill_derivation: (
+        _carbon_reduction
+    ),
+    PortfolioGoal.ENERGY_SAVINGS.value: _bill_saving,
+}
+
+
+def _require_budget_for_goal_aligned(scenario: Scenario) -> None:
+    """A goal-aligned Scenario is 'reduce as much as possible within this
+    budget' — undefined without one (unconstrained, it would recommend every
+    beneficial measure). Fail the misconfiguration loudly (ADR-0062)."""
+    if scenario.budget is None and scenario.goal in _GOAL_ALIGNED_OBJECTIVES:
+        raise ValueError(
+            f"scenario {scenario.id} has goal {scenario.goal!r} but no budget; "
+            "goal-aligned scenarios require a budget"
+        )
+
+
 def _objective_for(
     scenario: Scenario, bill_derivation: BillDerivation
 ) -> Callable[[Score], float]:
     """The metric the Scenario's goal maximises (ADR-0062), as an Optimiser
     objective (higher is better). Goals without an aligned metric optimise
     SAP, as every goal did before."""
-    if scenario.goal == _REDUCING_CO2_GOAL:
-        return _carbon_reduction
-    if scenario.goal == _ENERGY_SAVINGS_GOAL:
-        return _bill_saving(bill_derivation)
-    return sap_rating
+    build_objective = _GOAL_ALIGNED_OBJECTIVES.get(scenario.goal)
+    if build_objective is None:
+        return sap_rating
+    return build_objective(bill_derivation)
 
 
 def _target_sap(scenario: Scenario) -> Optional[float]:
     """The SAP rating the Optimiser repairs toward — the floor of the goal
     band for an INCREASING_EPC goal, else None (no SAP target)."""
-    if scenario.goal != _INCREASING_EPC_GOAL:
+    if scenario.goal != PortfolioGoal.INCREASING_EPC.value:
         return None
     return float(Epc(scenario.goal_value).sap_lower_bound())