# -*- coding: utf-8 -*-
r'''塌陷窗口分析器：专门看"连接总数 <= 3"的那些窗口里发生了什么。

== 为什么需要专门看窗口 ==

总体中位数两次都会被稳态主导（都是 61 秒 / 1.2 秒），区分不出 A/B 好坏。
真正的差别只在 QUIC 塌陷的那几分钟里体现：
  A 组 quic8+h2 2：塌陷时只剩 2 条在扛
  B 组 quic6+h2 4：塌陷时还有 4 条

所以核心指标是：
  * 「连接总数 <= 3」的采样占比（= 风险暴露时间）
  * 这些窗口里公网可用率

用法:
    python _build/rp_collapse.py <标签> <conns文件> <health文件>
'''
from __future__ import annotations

import sys
from datetime import datetime
from pathlib import Path

# 塌陷判定：总连接数 <= 这个值就算"容量很薄"
COLLAPSE_TOTAL = 3


def parse_ts(path: str, cols: int):
    rows = []
    for line in Path(path).read_text(encoding="utf-8", errors="replace").splitlines():
        parts = line.split("\t")
        if len(parts) < cols:
            continue
        try:
            t = datetime.strptime(parts[0].strip(), "%Y-%m-%d %H:%M:%S")
        except ValueError:
            continue
        rows.append((t, parts))
    return rows


def main() -> int:
    if len(sys.argv) < 4:
        print("用法: rp_collapse.py <标签> <conns> <health>")
        return 2
    label, conns_path, health_path = sys.argv[1], sys.argv[2], sys.argv[3]

    conns = parse_ts(conns_path, 3)
    health = parse_ts(health_path, 3)
    if not conns:
        print("  %s: 连接采样为空" % label)
        return 1

    # ---- 连接数统计 ----
    samples = []
    for t, p in conns:
        try:
            q = int(p[1])
        except ValueError:
            q = None
        try:
            h = int(p[2])
        except ValueError:
            h = None
        samples.append((t, q, h))

    valid = [(t, q, h) for t, q, h in samples if q is not None and h is not None]
    if not valid:
        print("  %s: 没有有效的连接采样" % label)
        return 1

    span = (valid[-1][0] - valid[0][0]).total_seconds()
    total_list = [q + h for _t, q, h in valid]

    collapse = [(t, q, h) for t, q, h in valid if q + h <= COLLAPSE_TOTAL]
    collapse_secs = len(collapse) * 60.0        # 每 60 秒一个采样
    collapse_pct = len(collapse) * 100.0 / len(valid)

    print("=" * 62)
    print("  %s" % label)
    print("  采样窗口 %.0f 分钟（%d 个连接采样）" % (span / 60, len(valid)))
    print("=" * 62)
    print()
    print("  连接数分布:")
    from collections import Counter
    cnt = Counter(total_list)
    for k in sorted(cnt, reverse=True):
        bar = "#" * min(cnt[k], 50)
        print("    总数 %2d : %3d 次  %s" % (k, cnt[k], bar))
    print()
    print("  平均连接数: %.2f" % (sum(total_list) / len(total_list)))
    print()

    # ---- 塌陷窗口 ----
    print("  ── 塌陷窗口（连接总数 <= %d）──" % COLLAPSE_TOTAL)
    print("    出现 %d 次采样 = 约 %.0f 秒 = 占窗口的 %.1f%%"
          % (len(collapse), collapse_secs, collapse_pct))
    if collapse:
        print("    明细:")
        for t, q, h in collapse:
            print("      %s   quic=%s http2=%s  合计=%d"
                  % (t.strftime("%H:%M:%S"), q, h, q + h))

    # ---- 塌陷窗口内的公网可用率 ----
    print()
    print("  ── 塌陷窗口内的公网可用率 ──")
    if not collapse or not health:
        print("    （窗口内没有健康样本）")
    else:
        # 把塌陷时刻扩展成 ±60 秒的窗口，再取落在里面的健康样本
        windows = [(t.timestamp() - 60, t.timestamp() + 60) for t, _q, _h in collapse]
        inside = []
        for t, p in health:
            ts = t.timestamp()
            if any(a <= ts <= b for a, b in windows):
                inside.append((t, p[1]))
        if inside:
            ok = sum(1 for _t, c in inside if c == "200")
            print("    窗口覆盖到 %d 个健康样本，成功 %d = %.1f%%"
                  % (len(inside), ok, ok * 100.0 / len(inside)))
            bad = [(t, c) for t, c in inside if c != "200"]
            if bad:
                print("    失败明细:")
                for t, c in bad:
                    print("      %s  码=%s" % (t.strftime("%H:%M:%S"), c))
        else:
            print("    （窗口内没有健康样本）")

    # ---- 总体可用率 ----
    if health:
        ok = sum(1 for _t, p in health if p[1] == "200")
        print()
        print("  ── 总体公网可用率（对照）──")
        print("    %d/%d = %.2f%%" % (ok, len(health), ok * 100.0 / len(health)))

    # ---- 一句话结论 ----
    print()
    print("  ── 一句话 ──")
    print("    风险暴露（总数<=%d）: %.1f%%   窗口内可用率: %s"
          % (COLLAPSE_TOTAL, collapse_pct,
             ("%.1f%%" % (sum(1 for _t, c in inside if c == "200") * 100.0 / len(inside))
              if collapse and health and inside else "无数据")))
    return 0


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