EOS/tests/test_optimize_run_result.py

"""Offline regression tests for per-run optimization results and atomic publication."""

from asyncio import Lock
from types import SimpleNamespace
from typing import Any
from unittest.mock import AsyncMock, Mock

import pytest

from akkudoktoreos.core import ems as ems_module
from akkudoktoreos.core.emsettings import EnergyManagementMode
from akkudoktoreos.optimization.genetic0.genetic0params import (
    Genetic0OptimizationParameters,
)
from akkudoktoreos.optimization.optimization import OptimizationAlgorithm
from akkudoktoreos.utils.datetimeutil import to_datetime


@pytest.fixture
def offline_ems(monkeypatch):
    """Run the actual EMS orchestration with no real adapters or prediction IO."""
    cls = ems_module.EnergyManagement
    for name in (
        "_start_datetime",
        "_observation_datetime",
        "_last_run_datetime",
        "_plan",
        "_optimization_solution",
        "_genetic_solution",
        "_genetic0_solution",
    ):
        monkeypatch.setattr(cls, name, None)
    monkeypatch.setattr(cls, "_stage", ems_module.EnergyManagementStage.IDLE)
    monkeypatch.setattr(cls, "_run_lock", Lock())
    monkeypatch.setattr(ems_module, "CacheEnergyManagementStore", Mock())
    return SimpleNamespace(
        config=SimpleNamespace(
            general=SimpleNamespace(timezone="Europe/Berlin"),
            ems=SimpleNamespace(mode=EnergyManagementMode.OPTIMIZATION),
            optimization=SimpleNamespace(
                algorithm=OptimizationAlgorithm.GENETIC,
                genetic=SimpleNamespace(generations=3, seed=17, interval_sec=3600, individuals=31),
                genetic0=SimpleNamespace(generations=5, seed=29),
            ),
            server=SimpleNamespace(verbose=False),
        ),
        prediction=SimpleNamespace(update_data=AsyncMock()),
        adapter=SimpleNamespace(update_data=AsyncMock()),
        set_start_datetime=cls.set_start_datetime,
    )


@pytest.mark.asyncio
@pytest.mark.parametrize("algorithm", list(OptimizationAlgorithm))
@pytest.mark.parametrize("explicit_start", [False, True])
async def test_implicit_genetic_start_uses_site_timezone(
    offline_ems, monkeypatch, set_other_timezone, algorithm, explicit_start
):
    set_other_timezone("UTC")
    now = to_datetime("2026-09-16T22:47:23Z", in_timezone="UTC")

    def frozen_datetime(value=None, **kwargs):
        return to_datetime(now if value is None else value, **kwargs)

    monkeypatch.setattr(ems_module, "to_datetime", frozen_datetime)
    offline_ems.config.optimization.genetic.interval_sec = 900
    await ems_module.EnergyManagement.run(
        offline_ems,
        mode=EnergyManagementMode.PREDICTION,
        algorithm=algorithm,
        start_datetime=now if explicit_start else None,
    )
    start = ems_module.EnergyManagement._start_datetime
    observed = ems_module.EnergyManagement._observation_datetime
    assert start is not None and observed is not None
    assert observed.timestamp() == now.timestamp()
    if algorithm == OptimizationAlgorithm.GENETIC:
        assert start.minute == 45
        assert start.hour == (22 if explicit_start else 0)
        assert start.day == (16 if explicit_start else 17)
        assert start.timezone_name == ("UTC" if explicit_start else "Europe/Berlin")
    else:
        assert start.minute == 0
        assert start.hour == 22
        assert start.day == 16
        assert start.timezone_name == "UTC"


@pytest.mark.asyncio
@pytest.mark.parametrize("algorithm", list(OptimizationAlgorithm))
@pytest.mark.parametrize("selection", ["configured", "explicit"])
@pytest.mark.parametrize("supplied", [False, True])
@pytest.mark.parametrize("timezone, expected_hour", [("UTC", 8), ("Europe/Berlin", 10)])
async def test_optimization_routes_only_selected_algorithm(
    monkeypatch, offline_ems, algorithm, selection, supplied, timezone, expected_hour
):
    """Configuration selection and explicit overrides retain isolated async paths."""
    selected_name = "Genetic" if algorithm == OptimizationAlgorithm.GENETIC else "Genetic0"
    suffix = "genetic" if algorithm == OptimizationAlgorithm.GENETIC else "genetic0"
    other_suffix = "genetic0" if suffix == "genetic" else "genetic"
    sentinel_parameters = object()
    sentinel_result, sentinel_plan = object(), object()
    solution = SimpleNamespace(
        optimization_solution=AsyncMock(return_value=sentinel_result),
        energy_management_plan=Mock(return_value=sentinel_plan),
    )
    constructors = {}
    preparers = {}
    for prefix in ("Genetic", "Genetic0"):
        constructor = Mock()
        constructor.return_value.optimize_ems.return_value = solution
        constructors[prefix] = constructor
        monkeypatch.setattr(ems_module, prefix + "Optimization", constructor)
        prepare = AsyncMock(return_value=sentinel_parameters)
        preparers[prefix] = prepare
        monkeypatch.setattr(
            getattr(ems_module, prefix + "OptimizationParameters"), "prepare", prepare
        )
    kwargs: dict[str, Any] = {
        "start_datetime": to_datetime("2026-09-16T10:00:00+02:00", in_timezone=timezone)
    }
    if selection == "configured":
        offline_ems.config.optimization.algorithm = algorithm
    else:
        offline_ems.config.optimization.algorithm = OptimizationAlgorithm(other_suffix.upper())
        kwargs["algorithm"] = algorithm
    if supplied:
        kwargs[suffix + "_parameters"] = sentinel_parameters
        kwargs[suffix + "_generations"] = 7
        kwargs[suffix + "_seed"] = 43
        if algorithm == OptimizationAlgorithm.GENETIC:
            kwargs["genetic_individuals"] = 11
    run_result = await ems_module.EnergyManagement.run(offline_ems, **kwargs)
    assert run_result is solution
    selected = constructors[selected_name]
    expected_config = getattr(offline_ems.config.optimization, suffix)
    selected.assert_called_once_with(
        verbose=False, fixed_seed=43 if supplied else expected_config.seed
    )
    expected_arguments: dict[str, Any] = {
        "start_hour": expected_hour,
        "parameters": sentinel_parameters,
        "ngen": 7 if supplied else expected_config.generations,
    }
    if algorithm == OptimizationAlgorithm.GENETIC:
        expected_arguments["individuals"] = 11 if supplied else None
    selected.return_value.optimize_ems.assert_called_once_with(**expected_arguments)
    other_name = "Genetic0" if selected_name == "Genetic" else "Genetic"
    constructors[other_name].assert_not_called()
    preparers[other_name].assert_not_awaited()
    if supplied:
        preparers[selected_name].assert_not_awaited()
    else:
        preparers[selected_name].assert_awaited_once_with()
    solution.optimization_solution.assert_awaited_once_with()
    solution.energy_management_plan.assert_called_once_with()
    cls = ems_module.EnergyManagement
    assert getattr(cls, "_" + suffix + "_solution") is solution
    assert getattr(cls, "_" + other_suffix + "_solution") is None
    assert cls.optimization_solution() is sentinel_result
    assert cls.plan() is sentinel_plan
    assert cls.stage() == ems_module.EnergyManagementStage.IDLE
    offline_ems.prediction.update_data.assert_awaited_once_with(
        force_enable=False, force_update=False
    )
    assert offline_ems.adapter.update_data.await_count == 2


@pytest.mark.asyncio
@pytest.mark.parametrize("mode", [EnergyManagementMode.DISABLED, EnergyManagementMode.PREDICTION])
async def test_non_optimization_modes_never_optimize(monkeypatch, offline_ems, mode):
    constructors = [Mock(), Mock()]
    monkeypatch.setattr(ems_module, "GeneticOptimization", constructors[0])
    monkeypatch.setattr(ems_module, "Genetic0Optimization", constructors[1])
    offline_ems.config.ems.mode = mode
    await ems_module.EnergyManagement.run(offline_ems)
    for constructor in constructors:
        constructor.assert_not_called()
    assert offline_ems.prediction.update_data.await_count == (
        mode == EnergyManagementMode.PREDICTION
    )
    assert offline_ems.adapter.update_data.await_count == (mode == EnergyManagementMode.PREDICTION)
    assert ems_module.EnergyManagement.plan() is None


@pytest.mark.asyncio
@pytest.mark.parametrize("prefix", ["Genetic", "Genetic0"])
async def test_missing_preparation_does_not_dispatch_controls(monkeypatch, offline_ems, prefix):
    constructor = Mock()
    monkeypatch.setattr(ems_module, prefix + "Optimization", constructor)
    prepare = AsyncMock(return_value=None)
    monkeypatch.setattr(getattr(ems_module, prefix + "OptimizationParameters"), "prepare", prepare)
    await ems_module.EnergyManagement.run(
        offline_ems, algorithm=OptimizationAlgorithm(prefix.upper())
    )
    prepare.assert_awaited_once_with()
    constructor.assert_not_called()
    assert offline_ems.adapter.update_data.await_count == 1  # acquisition only
    assert ems_module.EnergyManagement.plan() is None
    assert ems_module.EnergyManagement.stage() == ems_module.EnergyManagementStage.IDLE


@pytest.mark.asyncio
@pytest.mark.parametrize("start_hour", [None, 11])
async def test_legacy_optimize_explicitly_uses_genetic0(monkeypatch, start_hour):
    """Even with GENETIC configured, /optimize must never become the new optimizer."""
    from akkudoktoreos.server import eos
    from akkudoktoreos.server.rest.error import EOSProblem

    fake = SimpleNamespace(
        run=AsyncMock(return_value=None), genetic0_solution=Mock(return_value=None)
    )
    monkeypatch.setattr(eos, "get_ems", lambda: fake)
    parameters = Genetic0OptimizationParameters.model_validate(
        {
            "ems": {
                "pv_prognose_wh": [0.0, 100.0],
                "gesamtlast": [100.0, 100.0],
                "strompreis_euro_pro_wh": [0.0003, 0.0003],
                "einspeiseverguetung_euro_pro_wh": 0.00008,
                "preis_euro_pro_wh_akku": 0.0,
            },
            "pv_akku": None,
            "eauto": None,
            "inverter": None,
        }
    )
    with pytest.raises(EOSProblem):
        await eos.fastapi_optimize(parameters=parameters, start_hour=start_hour, ngen=2)
    kwargs = fake.run.await_args.kwargs
    assert kwargs["mode"] == EnergyManagementMode.OPTIMIZATION
    assert kwargs["algorithm"] == OptimizationAlgorithm.GENETIC0
    assert kwargs["genetic0_parameters"] is parameters
    assert kwargs["genetic0_generations"] == 2
    assert "genetic_parameters" not in kwargs
    assert (
        kwargs["start_datetime"] is None
        if start_hour is None
        else kwargs["start_datetime"].hour == 11
    )


@pytest.mark.asyncio
@pytest.mark.parametrize("phase", ["optimizer", "conversion", "plan"])
async def test_failed_legacy_http_run_never_reports_previous_solution(
    monkeypatch, offline_ems, phase
):
    import json
    from pathlib import Path
    from types import MethodType

    from httpx import ASGITransport, AsyncClient

    from akkudoktoreos.optimization.genetic0.genetic0solution import Genetic0Solution
    from akkudoktoreos.server import eos

    cls = ems_module.EnergyManagement
    data = json.loads(
        (Path(__file__).parent / "testdata/genetic0/optimize_result_1.json").read_text()
    )
    previous = Genetic0Solution.model_validate(data)
    monkeypatch.setattr(cls, "_genetic0_solution", previous)
    constructor = Mock()
    error = RuntimeError("synthetic " + phase + " failure")
    native = SimpleNamespace(
        optimization_solution=AsyncMock(return_value=object()),
        energy_management_plan=Mock(return_value=object()),
    )
    constructor.return_value.optimize_ems.return_value = native
    if phase == "optimizer":
        constructor.return_value.optimize_ems.side_effect = error
    elif phase == "conversion":
        native.optimization_solution.side_effect = error
    else:
        native.energy_management_plan.side_effect = error
    monkeypatch.setattr(ems_module, "Genetic0Optimization", constructor)
    offline_ems.run = MethodType(cls.run, offline_ems)
    offline_ems.genetic0_solution = cls.genetic0_solution
    monkeypatch.setattr(eos, "get_ems", lambda: offline_ems)
    async with AsyncClient(
        transport=ASGITransport(app=eos.app, raise_app_exceptions=False), base_url="http://test"
    ) as client:
        response = await client.post("/optimize?ngen=1", json=data["parameters"])
    constructor.return_value.optimize_ems.assert_called_once()
    # This diagnostic proves a failure is the stale-success bug, not invalid input.
    if response.status_code == 200:
        assert response.json()["start_solution"] == previous.start_solution
        assert response.json()["result"]["total_balance"] == previous.result.total_balance
    assert response.status_code >= 400, (
        "The failing optimizer returned HTTP 200 with the previous solution"
    )


@pytest.mark.asyncio
@pytest.mark.parametrize("prefix", ["Genetic", "Genetic0"])
@pytest.mark.parametrize("phase", ["conversion", "plan"])
async def test_conversion_failure_preserves_consistent_previous_results(
    monkeypatch, offline_ems, prefix, phase
):
    cls = ems_module.EnergyManagement
    previous_specific, previous_generic, previous_plan = object(), object(), object()
    suffix = prefix.lower()
    monkeypatch.setattr(cls, "_" + suffix + "_solution", previous_specific)
    monkeypatch.setattr(cls, "_optimization_solution", previous_generic)
    monkeypatch.setattr(cls, "_plan", previous_plan)
    conversion = AsyncMock(return_value=object())
    solution = SimpleNamespace(optimization_solution=conversion, energy_management_plan=Mock())
    if phase == "conversion":
        conversion.side_effect = RuntimeError("synthetic conversion failure")
    else:
        solution.energy_management_plan.side_effect = RuntimeError("synthetic plan failure")
    constructor = Mock()
    constructor.return_value.optimize_ems.return_value = solution
    monkeypatch.setattr(ems_module, prefix + "Optimization", constructor)
    supplied_parameters: dict[str, Any] = {suffix + "_parameters": object()}
    result = await cls.run(
        offline_ems,
        algorithm=OptimizationAlgorithm(prefix.upper()),
        **supplied_parameters,
    )
    assert result is None
    conversion.assert_awaited_once_with()
    assert solution.energy_management_plan.call_count == (phase == "plan")
    assert offline_ems.adapter.update_data.await_count == 1
    assert (
        getattr(cls, "_" + suffix + "_solution"),
        cls.optimization_solution(),
        cls.plan(),
        cls.stage(),
    ) == (
        previous_specific,
        previous_generic,
        previous_plan,
        ems_module.EnergyManagementStage.IDLE,
    ), (
        "Failed conversion published a new algorithm result beside the old plan and left EMS in OPTIMIZATION"
    )


@pytest.mark.asyncio
async def test_legacy_endpoint_uses_run_return_value_not_last_cached_solution(monkeypatch):
    import json
    from pathlib import Path

    from akkudoktoreos.optimization.genetic0.genetic0solution import Genetic0Solution
    from akkudoktoreos.server import eos

    data = json.loads(
        (Path(__file__).parent / "testdata/genetic0/optimize_result_1.json").read_text()
    )
    produced = Genetic0Solution.model_validate(data)
    fake = SimpleNamespace(
        run=AsyncMock(return_value=produced),
        genetic0_solution=Mock(side_effect=AssertionError("must use this run's result")),
    )
    monkeypatch.setattr(eos, "get_ems", lambda: fake)
    result = await eos.fastapi_optimize(parameters=produced.parameters, ngen=1)
    assert result.start_solution == produced.start_solution
    assert result.result.total_balance == produced.result.total_balance
    fake.genetic0_solution.assert_not_called()