# -*- coding: utf-8 -*-
"""iAOP 边缘采集网关 —— 主入口。

用法：
    python main.py --config config/gateway.example.yaml --point-dict point_dict.csv [--dry-run]

流程（模板化封装，对齐 PRD 5.1 用户操作流程）：
    实施工程师导入 DCS 点表 CSV → 自动校验（缺失字段/量纲/重复点号）
    → 加载模板配置（协议/周期/背压阈值/Kafka）→ 网关启动只读采集
    → Kafka 流式上行 + spool 断点续传 → 实时健康度上报。
"""
from __future__ import annotations

import argparse
import logging
import sys
import time
from typing import List, Tuple

import yaml

# 允许直接以脚本方式运行（python main.py）时仍能解析包内模块
from point_dict import load_point_dict_csv, validate_point_dict_file
from point_dict.loader import PointDict

logger = logging.getLogger("edge_gateway.main")


def parse_args(argv: List[str]) -> argparse.Namespace:
    parser = argparse.ArgumentParser(description="iAOP 边缘采集网关（模板化封装）")
    parser.add_argument("--config", required=True, help="采集配置 YAML（模板参数化）")
    parser.add_argument("--point-dict", required=True, help="点位字典 CSV（客户 DCS 点表）")
    parser.add_argument("--dry-run", action="store_true",
                        help="仅加载配置并校验点位字典，不启动采集")
    parser.add_argument("--rounds", type=int, default=0,
                        help="采集轮数上限（0=无限，调试用）")
    parser.add_argument("--verbose", action="store_true", help="输出调试日志")
    return parser.parse_args(argv)


def build_engine(config: dict, point_dict: PointDict):
    """按模板配置组装采集引擎（驱动路由 → spool → metrics → 引擎）。"""
    from collector import CollectorEngine, HealthMetrics, SpoolStore

    collector_cfg = config.get("collector", {})
    spool = SpoolStore(
        spool_dir=collector_cfg.get("spool_dir", "./spool"),
        cache_limit_bytes=int(collector_cfg.get("cache_limit_bytes", 512 * 1024 * 1024)),
    )
    metrics = HealthMetrics()

    # 组装驱动插槽：[(protocol, driver, device_prefixes)]
    driver_slots: List[Tuple[str, object, List[str]]] = []
    from drivers import from_template

    for item in collector_cfg.get("drivers", []):
        protocol = item.get("protocol")
        if not protocol:
            raise ValueError("collector.drivers[].protocol 必填")
        driver = from_template(protocol, item.get("config", {}))
        driver_slots.append((protocol, driver, item.get("device_prefixes", [])))

    if not driver_slots:
        # 模板配置未声明驱动时默认走模拟驱动（本地联调），避免空跑
        from drivers import SimulatorDriver

        driver_slots.append(("simulator", SimulatorDriver(), []))

    engine = CollectorEngine(
        point_dict=point_dict,
        driver_slots=driver_slots,
        spool=spool,
        metrics=metrics,
        interval_ms=int(collector_cfg.get("interval_ms", 1000)),
        max_pending=int(collector_cfg.get("max_pending", 100_000)),
    )
    return engine, spool, metrics


def build_sink(config: dict, spool) -> object:
    """按模板配置组装 Kafka 上行通道。"""
    from upstream import KafkaSink

    kafka_cfg = config.get("kafka", {})
    return KafkaSink(
        bootstrap_servers=kafka_cfg.get("bootstrap_servers", "127.0.0.1:9092"),
        topic_prefix=kafka_cfg.get("topic_prefix", "iaop"),
        spool=spool,
        batch_size=int(kafka_cfg.get("batch_size", 500)),
    )


def main(argv: List[str]) -> int:
    args = parse_args(argv)
    logging.basicConfig(
        level=logging.DEBUG if args.verbose else logging.INFO,
        format="%(asctime)s %(levelname)s %(name)s: %(message)s",
    )

    # 1) 加载模板配置
    with open(args.config, "r", encoding="utf-8") as fh:
        config = yaml.safe_load(fh) or {}

    # 2) 加载 + 自动校验点位字典（缺失字段/量纲/重复点号）
    report = validate_point_dict_file(args.point_dict)
    logger.info("点位字典校验: %s", report.summary())
    if not report.ok:
        for issue in report.issues[:20]:
            logger.error("  [%s] %s", issue.code, issue.message)
        if len(report.issues) > 20:
            logger.error("  ... 共 %d 条问题", len(report.issues))
        print(f"点位字典校验失败：{report.summary()}")
        return 2

    point_dict = load_point_dict_csv(args.point_dict)
    logger.info("点位字典加载完成：%d 个测点", len(point_dict))

    if args.dry_run:
        print("dry-run 通过：配置与点位字典校验 OK，未启动采集")
        return 0

    # 3) 组装并启动
    engine, spool, metrics = build_engine(config, point_dict)
    sink = build_sink(config, spool)

    # 断点续传：启动时先重发上次未确认记录
    pending = spool.pending_records(limit=10 ** 9)
    if pending:
        logger.info("检测到 %d 条未确认 spool 记录，启动续传", len(pending))
        sink.publish(pending)

    engine.start(sink=sink)
    logger.info("采集网关已启动：%d 测点 @ %dms，Kafka=%s",
                len(point_dict), engine.interval_ms, config.get("kafka", {}).get("bootstrap_servers"))

    try:
        rounds = 0
        while True:
            time.sleep(5)
            rounds += 5
            snap = metrics.snapshot()
            logger.info("健康度: 轮次=%d 样本=%d 丢失率=%.4f%% P99=%.3fs 可用性=%.4f%%",
                        snap["total_rounds"], snap["total_samples"],
                        snap["loss_rate"] * 100, snap["p99_latency_sec"],
                        snap["availability"] * 100)
            if args.rounds and rounds >= args.rounds:
                break
    except KeyboardInterrupt:
        pass
    finally:
        engine.stop()
        sink.close()
        snap = metrics.snapshot()
        print(f"SLA 达标(P99≤1.8s/丢失率≤0.02%/可用性≥99.8%): {metrics.meets_sla()}")
        print(f"健康度快照: {snap}")
    return 0


if __name__ == "__main__":
    sys.exit(main(sys.argv[1:]))