# ============================================================
# 偏好多特征规则归纳黄金测试（plan.md §8.3 / 矩阵 66 行剩余项）
# 覆盖：特征抽取（订单结构/客户等级/约束压力）、分箱规则归纳、
#       特征命中与冷启动回退、旧样本向后兼容、可解释中文文案。
# ============================================================
from __future__ import annotations

from datetime import UTC, datetime, timedelta
from pathlib import Path

from server.knowledge.preferences import PreferenceStore, extract_features


def _store(tmp_path: Path) -> PreferenceStore:
    return PreferenceStore(str(tmp_path / "pref.json"))


def _sample_with_features(strategy: str, features: dict, *, source: str = "schedule.run") -> dict:
    return {"strategy": strategy, "source": source, "actor": "u1",
            "projectId": "p1", "at": "2026-08-02 08:00", "features": dict(features)}


def test_extract_features_from_world():
    """Extract order mix, urgency, customer tier, and conflict pressure."""
    today = datetime.now(UTC).astimezone().date()
    world = {
        "productionOrders": [
            {"productCode": "P1", "customerLevel": "VIP", "priority": 1,
             "dueDate": (today + timedelta(days=1)).isoformat()},  # inside the half-horizon urgency window
            {"productCode": "P1", "customerLevel": "A", "priority": 5,
             "dueDate": (today + timedelta(days=14)).isoformat()},
            {"productCode": "P2", "customerLevel": "B", "priority": 5,
             "dueDate": today.isoformat()},  # due today is urgent
            {"productCode": "P3", "customerLevel": "B", "priority": 5,
             "dueDate": ""},
        ],
        "scheduleParams": {"planningHorizonDays": 14},
        "conflicts": [{"id": 1}, {"id": 2}, {"id": 3}],
    }
    feats = extract_features(world)
    assert feats["orderCount"] == 4
    assert feats["vipRatio"] == 0.25                      # 1/4 VIP
    assert feats["urgencyRatio"] == 0.5                   # 2/4 急单
    assert feats["mixCount"] == 3
    assert feats["hardConflictCount"] == 3


def test_induced_rules_bins_high_urgency_prefers_delivery_first(tmp_path: Path):
    """规则归纳：高急单/多品种特征箱 → 交期优先。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample_with_features("DELIVERY_FIRST", {"orderCount": 25, "urgencyRatio": 0.8, "mixCount": 9}),
        _sample_with_features("DELIVERY_FIRST", {"orderCount": 30, "urgencyRatio": 0.9, "mixCount": 12}),
        _sample_with_features("DELIVERY_FIRST", {"orderCount": 22, "urgencyRatio": 0.7, "mixCount": 10}),
    ]
    rules = ps.induced_rules("p1")
    assert rules["orderCount"]["high"]["strategy"] == "DELIVERY_FIRST"
    assert rules["orderCount"]["high"]["count"] == 3
    assert rules["urgencyRatio"]["high"]["strategy"] == "DELIVERY_FIRST"
    strategy, votes, used = ps.preferred_strategy_with_features(
        {"orderCount": 26, "urgencyRatio": 0.85}, project_id="p1")
    assert strategy == "DELIVERY_FIRST"
    assert votes["DELIVERY_FIRST"] > 0
    assert len(used) >= 2                                 # 两条特征规则命中


def test_feature_rule_overrides_global_frequency(tmp_path: Path):
    """特征规则应胜过全局频次（多特征回归的价值：场景自适应）。"""
    ps = _store(tmp_path)
    # 全局上 CAPACITY_BALANCE 最多（4 条），但低品种小单场景全部选 DELIVERY_FIRST
    for i in range(4):
        ps.samples.append(_sample_with_features("CAPACITY_BALANCE",
                                                {"orderCount": 40, "mixCount": 20}))
    for i in range(3):
        ps.samples.append(_sample_with_features("DELIVERY_FIRST",
                                                {"orderCount": 2, "mixCount": 1}))
    global_strategy, _ = ps.preferred_strategy(project_id="p1")
    assert global_strategy == "CAPACITY_BALANCE"
    strategy, _, used = ps.preferred_strategy_with_features(
        {"orderCount": 1, "mixCount": 1}, project_id="p1")
    assert strategy == "DELIVERY_FIRST"
    assert used                                                   # 规则命中而非全局回退


def test_fallback_when_no_rule_matches(tmp_path: Path):
    """无特征样本/无规则命中 → 回退全局时间衰减偏好（冷启动兼容）。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample_with_features("COMPREHENSIVE", {"orderCount": 3}),
        _sample_with_features("DELIVERY_FIRST", {"orderCount": 3}),
    ]
    # 未知特征（不在分箱表）→ 不命中任何规则 → 回退全局
    strategy, _, used = ps.preferred_strategy_with_features(
        {"unknownFeature": 99}, project_id="p1")
    assert strategy in ("COMPREHENSIVE", "DELIVERY_FIRST")
    assert used == []
    # 完全没有特征样本 → induced_rules 空 + 回退
    ps.samples = [{"strategy": "A", "source": "schedule.run", "actor": "u1",
                   "projectId": "p1", "at": "2026-08-02 08:00"}]
    assert ps.induced_rules("p1") == {}
    strategy, _, used = ps.preferred_strategy_with_features(
        {"orderCount": 1}, project_id="p1")
    assert strategy == "A" and used == []


def test_adopt_signal_weights_double_in_rules(tmp_path: Path):
    """规则得分：采用(scenario.apply) 权重 2 > 试排(schedule.run) 权重 1。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample_with_features("A", {"orderCount": 2}, source="schedule.run"),
        _sample_with_features("B", {"orderCount": 2}, source="scenario.apply"),
    ]
    rules = ps.induced_rules("p1")
    rule = rules["orderCount"]["low"]
    assert rule["strategy"] == "B"                        # 1 次采用(权重2) > 1 次试排(权重1)
    assert rule["score"] == 2.0
    assert abs(rule["support"] - 2 / 3) < 0.01          # 0.67（舍入 2 位）


def test_explain_features_chinese_and_rules(tmp_path: Path):
    """特征版解释：中文依据 + 规则明细（可进证据链）。"""
    ps = _store(tmp_path)
    ps.samples = [
        _sample_with_features("DELIVERY_FIRST", {"orderCount": 25, "urgencyRatio": 0.8}),
        _sample_with_features("DELIVERY_FIRST", {"orderCount": 30, "urgencyRatio": 0.9}),
    ]
    expl = ps.explain_features({"orderCount": 26, "urgencyRatio": 0.85}, project_id="p1")
    assert expl["strategy"] == "DELIVERY_FIRST"
    assert "依据订单结构与约束压力" in expl["reason"]
    assert "orderCount" in expl["reason"]
    assert expl["rules"] and expl["rules"][0]["bin"] in ("low", "med", "high")
    # 无特征样本时回退普通解释并附空规则
    ps.samples = []
    expl2 = ps.explain_features({"orderCount": 26}, project_id="p1")
    assert expl2["rules"] == [] and expl2["confidence"] == "cold"