# ============================================================
# EX-07 / EX-08 分析视图黄金测试
# ============================================================
from __future__ import annotations

from server.aps_domain.analytics import (
    build_compare_table,
    build_kpi_dashboard,
    matrix_from_flex_rows,
)
from server.aps_domain.flex import run_flex_schedule
from server.engines import get_engine
from server.engines.base import EngineParams
from server.state.seed import seed_world
from server.timeutil import add_minutes, fmt_date, today0


class _MemStore:
    def __init__(self, data):
        self.data = data

    def next_id(self, kind: str) -> int:
        key = f"_c_{kind}"
        self.data[key] = self.data.get(key, 5000) + 1
        return self.data[key]

    def save(self):
        pass


def _run_fixed(world):
    start = fmt_date(add_minutes(today0(), 24 * 60))
    params = EngineParams(orderIds=[], engineType="RULE", strategyTemplate="COMPREHENSIVE",
                          planningHorizonDays=14, startDate=start)
    counters: dict[str, int] = {}

    def next_id(kind: str) -> int:
        counters[kind] = counters.get(kind, 0) + 1
        return counters[kind]

    get_engine("RULE").solve(world, params, next_id)


def test_kpi_dashboard_aggregates():
    store = _MemStore(seed_world())
    _run_fixed(store.data)
    run_flex_schedule(store, sort_mode="BOTTLENECK", actor="test")
    dash = build_kpi_dashboard(store.data)
    assert len(dash["cards"]) >= 5
    assert dash["fixed"] and dash["fixed"].get("versionNo")
    assert dash["flex"] and dash["flex"].get("versionNo")
    assert "total" in dash["conflicts"]


def test_compare_table_has_best_and_deltas():
    store = _MemStore(seed_world())
    table = build_compare_table(store.data, track="flex")
    assert table["sections"]
    sec = table["sections"][0]
    assert len(sec["columns"]) == 5
    assert {column["sortMode"] for column in sec["columns"]} == {
        "ASC", "DESC", "BOTTLENECK", "KITTING_FIRST", "SKILL_FIRST",
    }
    assert sec["recommendation"]
    row = next(r for r in sec["rows"] if r["metric"] == "totalTardiness")
    assert row["bestIdx"] is not None
    assert row["deltas"][row["bestIdx"]] in (0, 0.0)


def test_flex_matrix_excludes_degraded_best_kpi_and_marks_trial_only():
    rows = [
        {"sortMode": "SKILL_FIRST", "label": "技能优先", "strategyStatus": "DEGRADED",
         "strategyEvidence": [{"code": "NO_SKILL_LEVEL_VARIATION"}],
         "totalTardiness": 0, "conflictCount": 0, "avgUtilization": 90,
         "onTimeCount": 10, "orderCount": 10, "vlCount": 10},
        {"sortMode": "ASC", "label": "正排", "strategyStatus": "READY",
         "totalTardiness": 12, "conflictCount": 1, "avgUtilization": 80,
         "onTimeCount": 9, "orderCount": 10, "vlCount": 10},
    ]
    matrix = matrix_from_flex_rows(
        rows,
        data_quality={
            "productionReady": False,
            "warnings": [{"message": "设备能力仅覆盖 1/41 台设备"}],
        },
    )
    assert len(matrix["columns"]) == 2
    assert matrix["columns"][0]["strategyStatus"] == "DEGRADED"
    assert matrix["recommendation"] == "正排"
    assert matrix["recommendationId"] == "ASC"
    assert matrix["eligibleRecommendationIds"] == ["ASC"]
    assert matrix["productionReady"] is False
    assert matrix["recommendationStatus"] == "TRIAL_ONLY"
    assert "数据待补" in matrix["recommendationReason"]


def test_flex_matrix_without_ready_strategy_is_unavailable():
    rows = [
        {"sortMode": "KITTING_FIRST", "label": "齐套优先", "strategyStatus": "PARTIAL",
         "totalTardiness": 5, "conflictCount": 0, "avgUtilization": 80,
         "onTimeCount": 9, "orderCount": 10, "vlCount": 10},
        {"sortMode": "SKILL_FIRST", "label": "技能优先", "strategyStatus": "DEGRADED",
         "totalTardiness": 0, "conflictCount": 0, "avgUtilization": 90,
         "onTimeCount": 10, "orderCount": 10, "vlCount": 10},
    ]
    matrix = matrix_from_flex_rows(rows, data_quality={"productionReady": False})
    assert matrix["recommendationStatus"] == "UNAVAILABLE"
    assert matrix["recommendation"] is None
    assert matrix["recommendationId"] is None
    assert matrix["eligibleRecommendationIds"] == []
    assert "没有 strategyStatus=READY" in matrix["recommendationReason"]


def test_flex_matrix_excludes_partial_schedule_result_even_when_strategy_is_ready():
    rows = [
        {"sortMode": "ASC", "label": "正排", "strategyStatus": "READY",
         "resultStatus": "PARTIAL", "totalTardiness": 0, "conflictCount": 0,
         "avgUtilization": 95, "onTimeCount": 10, "orderCount": 10, "vlCount": 5},
        {"sortMode": "DESC", "label": "倒排", "strategyStatus": "READY",
         "resultStatus": "WITH_CONFLICTS", "totalTardiness": 10, "conflictCount": 2,
         "avgUtilization": 80, "onTimeCount": 8, "orderCount": 10, "vlCount": 10},
    ]
    matrix = matrix_from_flex_rows(rows, data_quality={"productionReady": False})
    assert matrix["recommendationId"] == "DESC"
    assert matrix["eligibleRecommendationIds"] == ["DESC"]
    assert matrix["recommendationStatus"] == "TRIAL_ONLY"

    only_partial = matrix_from_flex_rows(rows[:1], data_quality={"productionReady": False})
    assert only_partial["recommendationId"] is None
    assert only_partial["recommendationStatus"] == "UNAVAILABLE"


def test_compare_table_propagates_flex_data_quality():
    table = build_compare_table(seed_world(), track="flex")
    section = table["sections"][0]
    assert section["productionReady"] is False
    assert section["recommendationStatus"] == "TRIAL_ONLY"
    assert section["recommendationId"] in section["eligibleRecommendationIds"]