清理误提交的测试数据目录 + 扩展 .gitignore

_build/rp_collapse.py

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+# -*- 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())