146 lines
5.9 KiB
Python
146 lines
5.9 KiB
Python
# ============================================================
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# EX-07 / EX-08 分析视图黄金测试
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# ============================================================
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from __future__ import annotations
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from server.agent_core.intent import parse_fast
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from server.aps_domain.analytics import (
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build_compare_table,
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build_kpi_dashboard,
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matrix_from_flex_rows,
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)
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from server.aps_domain.flex import run_flex_schedule
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from server.engines import get_engine
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from server.engines.base import EngineParams
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from server.state.seed import seed_world
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from server.timeutil import add_minutes, fmt_date, today0
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class _MemStore:
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def __init__(self, data):
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self.data = data
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def next_id(self, kind: str) -> int:
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key = f"_c_{kind}"
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self.data[key] = self.data.get(key, 5000) + 1
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return self.data[key]
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def save(self):
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pass
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def _run_fixed(world):
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start = fmt_date(add_minutes(today0(), 24 * 60))
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params = EngineParams(orderIds=[], engineType="RULE", strategyTemplate="COMPREHENSIVE",
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planningHorizonDays=14, startDate=start)
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counters: dict[str, int] = {}
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def next_id(kind: str) -> int:
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counters[kind] = counters.get(kind, 0) + 1
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return counters[kind]
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get_engine("RULE").solve(world, params, next_id)
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def test_kpi_dashboard_aggregates():
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store = _MemStore(seed_world())
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_run_fixed(store.data)
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run_flex_schedule(store, sort_mode="BOTTLENECK", actor="test")
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dash = build_kpi_dashboard(store.data)
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assert len(dash["cards"]) >= 5
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assert dash["fixed"] and dash["fixed"].get("versionNo")
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assert dash["flex"] and dash["flex"].get("versionNo")
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assert "total" in dash["conflicts"]
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def test_compare_table_has_best_and_deltas():
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store = _MemStore(seed_world())
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table = build_compare_table(store.data, track="flex")
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assert table["sections"]
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sec = table["sections"][0]
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assert len(sec["columns"]) == 5
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assert {column["sortMode"] for column in sec["columns"]} == {
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"ASC", "DESC", "BOTTLENECK", "KITTING_FIRST", "SKILL_FIRST",
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}
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assert sec["recommendation"]
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row = next(r for r in sec["rows"] if r["metric"] == "totalTardiness")
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assert row["bestIdx"] is not None
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assert row["deltas"][row["bestIdx"]] in (0, 0.0)
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def test_intent_analytics_phrases():
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world = seed_world()
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assert parse_fast("打开KPI仪表盘", world).intent == "query.kpi"
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assert parse_fast("方案对比表", world).intent == "scenario.compare"
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def test_flex_matrix_excludes_degraded_best_kpi_and_marks_trial_only():
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rows = [
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{"sortMode": "SKILL_FIRST", "label": "技能优先", "strategyStatus": "DEGRADED",
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"strategyEvidence": [{"code": "NO_SKILL_LEVEL_VARIATION"}],
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"totalTardiness": 0, "conflictCount": 0, "avgUtilization": 90,
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"onTimeCount": 10, "orderCount": 10, "vlCount": 10},
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{"sortMode": "ASC", "label": "正排", "strategyStatus": "READY",
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"totalTardiness": 12, "conflictCount": 1, "avgUtilization": 80,
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"onTimeCount": 9, "orderCount": 10, "vlCount": 10},
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]
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matrix = matrix_from_flex_rows(
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rows,
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data_quality={
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"productionReady": False,
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"warnings": [{"message": "设备能力仅覆盖 1/41 台设备"}],
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},
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)
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assert len(matrix["columns"]) == 2
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assert matrix["columns"][0]["strategyStatus"] == "DEGRADED"
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assert matrix["recommendation"] == "正排"
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assert matrix["recommendationId"] == "ASC"
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assert matrix["eligibleRecommendationIds"] == ["ASC"]
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assert matrix["productionReady"] is False
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assert matrix["recommendationStatus"] == "TRIAL_ONLY"
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assert "数据待补" in matrix["recommendationReason"]
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def test_flex_matrix_without_ready_strategy_is_unavailable():
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rows = [
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{"sortMode": "KITTING_FIRST", "label": "齐套优先", "strategyStatus": "PARTIAL",
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"totalTardiness": 5, "conflictCount": 0, "avgUtilization": 80,
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"onTimeCount": 9, "orderCount": 10, "vlCount": 10},
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{"sortMode": "SKILL_FIRST", "label": "技能优先", "strategyStatus": "DEGRADED",
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"totalTardiness": 0, "conflictCount": 0, "avgUtilization": 90,
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"onTimeCount": 10, "orderCount": 10, "vlCount": 10},
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]
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matrix = matrix_from_flex_rows(rows, data_quality={"productionReady": False})
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assert matrix["recommendationStatus"] == "UNAVAILABLE"
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assert matrix["recommendation"] is None
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assert matrix["recommendationId"] is None
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assert matrix["eligibleRecommendationIds"] == []
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assert "没有 strategyStatus=READY" in matrix["recommendationReason"]
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def test_flex_matrix_excludes_partial_schedule_result_even_when_strategy_is_ready():
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rows = [
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{"sortMode": "ASC", "label": "正排", "strategyStatus": "READY",
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"resultStatus": "PARTIAL", "totalTardiness": 0, "conflictCount": 0,
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"avgUtilization": 95, "onTimeCount": 10, "orderCount": 10, "vlCount": 5},
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{"sortMode": "DESC", "label": "倒排", "strategyStatus": "READY",
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"resultStatus": "WITH_CONFLICTS", "totalTardiness": 10, "conflictCount": 2,
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"avgUtilization": 80, "onTimeCount": 8, "orderCount": 10, "vlCount": 10},
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]
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matrix = matrix_from_flex_rows(rows, data_quality={"productionReady": False})
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assert matrix["recommendationId"] == "DESC"
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assert matrix["eligibleRecommendationIds"] == ["DESC"]
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assert matrix["recommendationStatus"] == "TRIAL_ONLY"
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only_partial = matrix_from_flex_rows(rows[:1], data_quality={"productionReady": False})
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assert only_partial["recommendationId"] is None
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assert only_partial["recommendationStatus"] == "UNAVAILABLE"
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def test_compare_table_propagates_flex_data_quality():
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table = build_compare_table(seed_world(), track="flex")
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section = table["sections"][0]
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assert section["productionReady"] is False
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assert section["recommendationStatus"] == "TRIAL_ONLY"
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assert section["recommendationId"] in section["eligibleRecommendationIds"]
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