Model/tests/orchestration/test_first_run_without_database.py

"""First Run end-to-end with NO database — in-memory fakes only.

The same `AraFirstRunPipeline` the Postgres integration test drives, but wired
against a `FakeUnitOfWork` instead of a `PostgresUnitOfWork`: Ingestion ->
Baseline -> Modelling run start-to-finish, hand off through in-memory repos, and
produce an inspectable multi-measure Plan without a `Session` ever being opened.
This is the harness the owner runs to sense-check recommendations interactively.
"""

from __future__ import annotations

import dataclasses
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Optional

from datatypes.epc.domain.epc import Epc
from datatypes.epc.domain.epc_property_data import EpcPropertyData
from domain.modelling.scenario import Scenario
from domain.property.property import Property, PropertyIdentity
from domain.property_baseline.rebaseliner import StubRebaseliner
from domain.sap10_calculator.calculator import Sap10Calculator
from orchestration.ara_first_run_pipeline import AraFirstRunPipeline
from orchestration.ingestion_orchestrator import IngestionOrchestrator
from orchestration.modelling_orchestrator import ModellingOrchestrator
from orchestration.property_baseline_orchestrator import PropertyBaselineOrchestrator
from repositories.fuel_rates.fuel_rates_static_file_repository import (
    FuelRatesStaticFileRepository,
)
from repositories.geospatial.geospatial_repository import GeospatialRepository
from harness.plan_table import format_plan_table
from repositories.product.product_json_repository import ProductJsonRepository
from tests.domain.sap10_calculator.worksheet._elmhurst_worksheet_000490 import (
    build_epc as _build_uninsulated_cavity_and_floor_epc,
)
from tests.orchestration.fakes import (
    FakeEpcRepo,
    FakePlanRepository,
    FakePropertyRepo,
    FakeScenarioRepository,
    FakeUnitOfWork,
)

_CATALOGUE = Path(__file__).resolve().parent / "fixtures/product_catalogue.json"


@dataclass
class _Command:
    portfolio_id: int
    property_ids: list[int]
    scenario_ids: list[int]


class _FetcherReturning:
    def __init__(self, epc: EpcPropertyData) -> None:
        self._epc = epc

    def get_by_uprn(self, uprn: int) -> Optional[EpcPropertyData]:
        return self._epc


class _NoCoordinates(GeospatialRepository):
    def coordinates_for(self, uprn: int):  # type: ignore[no-untyped-def]
        return None  # skip the solar leg


class _UnusedSolarFetcher:
    def get_building_insights(
        self, longitude: float, latitude: float
    ) -> dict[str, Any]:  # pragma: no cover
        return {}


def _uninsulated_lodged_epc() -> EpcPropertyData:
    # 000490: an uninsulated cavity wall + suspended floor (loft already 300mm),
    # so the wall + floor Generators fire and the ventilation Dependency follows.
    # The calculator fixture carries no lodged recorded-performance, so we fill it
    # in (as a real lodged EPC would) — it already carries the RHI block — so the
    # Baseline stage can run inside the full pipeline.
    epc = _build_uninsulated_cavity_and_floor_epc()
    return dataclasses.replace(
        epc,
        energy_rating_current=57,
        current_energy_efficiency_band=Epc.D,
        co2_emissions_current=3.0,
        energy_consumption_current=300,
    )


def test_first_run_produces_a_multi_measure_plan_without_a_database() -> None:
    # Arrange — an in-memory Property (no EPC yet; Ingestion supplies it), a
    # default Increasing-EPC Scenario, and a file-backed product catalogue.
    epc_repo = FakeEpcRepo()
    plan_repo = FakePlanRepository()
    property_repo = FakePropertyRepo(
        {
            10: Property(
                identity=PropertyIdentity(
                    portfolio_id=1,
                    postcode="A0 0AA",
                    address="1 Some Street",
                    uprn=12345,
                )
            )
        },
        epc_repo=epc_repo,
    )
    unit: FakeUnitOfWork = FakeUnitOfWork(
        property=property_repo,
        epc=epc_repo,
        scenario=FakeScenarioRepository(
            {
                7: Scenario(
                    id=7,
                    goal="Increasing EPC",
                    goal_value="C",
                    budget=None,
                    is_default=True,
                )
            }
        ),
        product=ProductJsonRepository(_CATALOGUE),
        plan=plan_repo,
    )

    pipeline = AraFirstRunPipeline(
        ingestion=IngestionOrchestrator(
            unit_of_work=lambda: unit,
            epc_fetcher=_FetcherReturning(_uninsulated_lodged_epc()),
            geospatial_repo=_NoCoordinates(),
            solar_fetcher=_UnusedSolarFetcher(),
        ),
        baseline=PropertyBaselineOrchestrator(
            unit_of_work=lambda: unit,
            rebaseliner=StubRebaseliner(),
            fuel_rates=FuelRatesStaticFileRepository(),
        ),
        modelling=ModellingOrchestrator(
            unit_of_work=lambda: unit,
            calculator=Sap10Calculator(),
            fuel_rates=FuelRatesStaticFileRepository(),
        ),
    )

    # Act — the whole First Run, no Session ever opened.
    pipeline.run(_Command(portfolio_id=1, property_ids=[10], scenario_ids=[7]))

    # Assert — a Plan was persisted in memory for (property 10, scenario 7),
    # with at least one Plan Measure and a post-retrofit SAP no worse than baseline.
    plan = plan_repo.saved[(10, 7)]
    print("\n" + format_plan_table(plan))  # visible under `pytest -s` for sense-checking
    assert len(plan.measures) >= 1
    assert plan.post_sap_continuous >= plan.baseline.sap_continuous