#!/usr/bin/env python3
"""任务A 交付验收脚本 — forecast_deviation 预测偏差规则（酣客entity1 / 博海entity2）

做四件事（可复跑，幂等）：
  1. 经生产 API（管理员 JWT）为 entity1 / entity2 各建 1 条 forecast_deviation 规则
  2. 回查 API 列表 + 直查 DB 实证规则存在（含 rule_id / kpi / params）
  3. 触发测试：给 entity1 规则构造一期「预测偏差超阈值」场景（带标记的临时 KPIValue）
     → 调 POST /api/cma/alert-rules/run-forecast-deviation → 断言 pending 预警生成
  4. 清理：删除临时 KPIValue 与该次生成的预警，回查归零（生产不留假数据）

用法：cd /root/cma-management/backend && venv/bin/python3 scripts/verify_forecast_deviation_rules_e2e.py
"""
import json
import sys
import urllib.request
import urllib.error

import os  # noqa: E402  (凭据加载器需要)
# ---- 管理员凭据同源加载（2026-09-14 cma-defaultcred-code-fix）----
# 生产凭据只存 600 密钥文件；禁止在脚本/文档/日志里硬编码口令。
# 顺序：$CMA_ADMIN_ENV → wecom-ops 主副本（ops 轮换落点，权威） → 本 profile 副本。
def _admin_creds():
    """返回 (user, password, 来源文件)；未找到 → 显式报错退出（不静默退回默认口令）"""
    for p in (os.environ.get("CMA_ADMIN_ENV"),
              "/root/.hermes/profiles/wecom-ops/.secrets/cma-admin.env",
              "/root/.hermes/profiles/wecom-fullstack/.secrets/cma-admin.env"):
        if p and os.path.isfile(p):
            kv = {}
            for line in open(p, encoding="utf-8"):
                line = line.strip()
                if "=" in line and not line.startswith("#"):
                    k, v = line.split("=", 1)
                    kv[k.strip()] = v.strip().strip('"').strip("'")
            if kv.get("CMA_ADMIN_USER") and kv.get("CMA_ADMIN_PASS"):
                return kv["CMA_ADMIN_USER"], kv["CMA_ADMIN_PASS"], p
    raise SystemExit("[错误] 未找到 CMA 管理员凭据：请设 $CMA_ADMIN_ENV，或准备 600 权限密钥文件 "
                     ".secrets/cma-admin.env（键名 CMA_ADMIN_USER / CMA_ADMIN_PASS）")


ADMIN_USER, ADMIN_PASS, CRED_SRC = _admin_creds()
print(f"[creds] 来源={CRED_SRC} 账号={ADMIN_USER}（口令不回显）")

BASE = "http://127.0.0.1:8010"
ADMIN = {"username": ADMIN_USER, "password": ADMIN_PASS}
MARK = "【系统验证临时数据-验证后删除】"

# 规则目标：酣客 → 应收账款周转天数(F_AR_DAYS, id=6，有 2026-09 预测日志)
#           博海 → 营收(BH_REVENUE, id=421)
TARGETS = [
    {"entity_id": 1, "kpi_id": 6, "kpi_label": "F_AR_DAYS"},
    {"entity_id": 2, "kpi_id": 421, "kpi_label": "BH_REVENUE"},
]
RULE_TYPE = "forecast_deviation"
PARAMS = {"threshold_pct": 15, "red_ratio": 2}  # >15% 黄，>30% 红（实现按 threshold×2 定红）


def http(method, path, token=None, body=None, timeout=30):
    url = BASE + path
    data = json.dumps(body).encode() if body is not None else None
    req = urllib.request.Request(url, data=data, method=method)
    req.add_header("Content-Type", "application/json")
    if token:
        req.add_header("Authorization", f"Bearer {token}")
    try:
        with urllib.request.urlopen(req, timeout=timeout) as r:
            return r.status, json.loads(r.read().decode() or "{}")
    except urllib.error.HTTPError as e:
        return e.code, {"detail": e.read().decode()[:300]}


def login(entity_id):
    st, r = http("POST", "/api/cma/auth/login", body={**ADMIN, "entity_id": entity_id})
    assert st == 200, f"登录 entity{entity_id} 失败: {st} {r}"
    return r["token"], r.get("entity_name")


def main():
    ok = True

    # ── 1+2. 建规则 ────────────────────────────────────────────
    print("=== 1. 创建 forecast_deviation 规则 ===")
    created = {}
    for t in TARGETS:
        eid = t["entity_id"]
        token, ename = login(eid)
        st, rules = http("GET", f"/api/cma/alert-rules?rule_type={RULE_TYPE}", token=token)
        assert st == 200, f"列规则失败: {st} {rules}"
        exist = [r for r in rules.get("data", []) if r["kpi_id"] == t["kpi_id"] and r["rule_type"] == RULE_TYPE]
        if exist:
            rid = exist[0]["id"]
            print(f"  entity{eid}({ename}) {t['kpi_label']}: 已存在 rule_id={rid}（幂等跳过）")
        else:
            st, r = http("POST", "/api/cma/alert-rules", token=token, body={
                "kpi_id": t["kpi_id"],
                "rule_type": RULE_TYPE,
                "trigger_on": "actual",
                "enabled": 1,
                "params": PARAMS,
            })
            assert st == 200, f"建规则失败 entity{eid}: {st} {r}"
            rid = r["data"]["id"]
            print(f"  entity{eid}({ename}) {t['kpi_label']}: 新建 rule_id={rid} params={r['data']['params']}")
        created[eid] = rid

    # ── 3. DB 回查 ─────────────────────────────────────────────
    print("=== 2. DB 回查实证 ===")
    sys.path.insert(0, ".")
    from app.database import get_session_local
    from app.models import KPIDefinition, KPIValue, KPIAlert, KpiForecastLog
    from app.api.alert_rules import AlertRule
    db = get_session_local()()
    try:
        for eid, rid in created.items():
            row = db.query(AlertRule).filter(AlertRule.id == rid).first()
            kpi = db.query(KPIDefinition).filter(KPIDefinition.id == row.kpi_id).first()
            print(f"  rule_id={row.id} entity_id={row.entity_id} kpi_id={row.kpi_id}"
                  f"({kpi.kpi_code if kpi else '?'}) type={row.rule_type} enabled={row.enabled} params={row.params}")
            assert row.entity_id == eid and row.rule_type == RULE_TYPE
            assert row.enabled == 1

        # ── 4. 触发测试（entity1）─────────────────────────────
        print("=== 3. 触发测试（构造偏差场景, entity1）===")
        t1 = TARGETS[0]
        rid = created[1]
        rule = db.query(AlertRule).filter(AlertRule.id == rid).first()
        log = (db.query(KpiForecastLog)
               .filter(KpiForecastLog.entity_id == 1, KpiForecastLog.kpi_id == rule.kpi_id)
               .order_by(KpiForecastLog.created_at.desc()).first())
        forecast = float(log.forecast_value)
        # 构造：实际值 = 预测值的一半 → 偏差 100% > 15% → red（>30%）
        actual = round(forecast / 2, 2)
        temp = KPIValue(kpi_id=rule.kpi_id, entity_id=1, period=log.period,
                        actual_value=actual, source_type="manual", data_status="pending", remark=MARK)
        db.add(temp)
        db.commit()
        db.refresh(temp)
        print(f"  临时KPIValue id={temp.id} period={log.period} 预测={forecast} 实际={actual}")

        token1, _ = login(1)
        st, r = http("POST", "/api/cma/alert-rules/run-forecast-deviation", token=token1, timeout=60)
        assert st == 200, f"触发失败: {st} {r}"
        print(f"  run-forecast-deviation → {r}")

        db.expire_all()
        # MySQL REPEATABLE READ：API 在另一进程提交，本 session 需结束旧事务快照才能读到
        db.rollback()
        alerts = db.query(KPIAlert).filter(
            KPIAlert.entity_id == 1, KPIAlert.kpi_id == rule.kpi_id,
            KPIAlert.alert_type == "forecast", KPIAlert.status == "pending",
        ).order_by(KPIAlert.id.desc()).all()
        assert alerts, "未生成预测偏差预警 → 触发测试 FAIL"
        a = alerts[0]
        alert_id = a.id
        print(f"  ✅ 预警生成: id={a.id} level={a.alert_level} type={a.alert_type}")
        print(f"     message={a.alert_message}")
        assert a.alert_level == "red", f"偏差100%应为红灯, 实际={a.alert_level}"

        # ── 5. 清理 ────────────────────────────────────────────
        print("=== 4. 清理临时数据（生产不留假数据）===")
        temp_id = temp.id
        db.rollback()
        a_row = db.query(KPIAlert).filter(KPIAlert.id == alert_id).first()
        temp_row = db.query(KPIValue).filter(KPIValue.id == temp_id).first()
        if a_row:
            db.delete(a_row)
        if temp_row:
            db.delete(temp_row)
        db.commit()
        left_v = db.query(KPIValue).filter(KPIValue.remark == MARK).count()
        left_a = db.query(KPIAlert).filter(KPIAlert.id == alert_id).count()
        print(f"  回查: 临时KPIValue剩余={left_v} / 本次预警剩余={left_a}")
        assert left_v == 0 and left_a == 0

        print("=== 5. 规则终态（交付物保留）===")
        for eid, rid in created.items():
            row = db.query(AlertRule).filter(AlertRule.id == rid).first()
            print(f"  entity{eid}: rule_id={row.id} kpi_id={row.kpi_id} type={row.rule_type} enabled={row.enabled}")
    finally:
        db.close()

    print("\nALL PASS" if ok else "\nFAILED")
    return 0


if __name__ == "__main__":
    sys.exit(main())