# -*- coding: utf-8 -*-
"""
并排对比两个(或多个)机器的 数据.jsonl，定位谁慢、慢在哪个阶段。

用法:
  python temp/compare_jsonl.py 2号机器数据.jsonl 3号机器数据.jsonl
  python temp/compare_jsonl.py a.jsonl b.jsonl c.jsonl ...
"""
import json
import sys
from datetime import datetime


def parse_dt(s):
    try:
        return datetime.fromisoformat(s)
    except (ValueError, TypeError):
        return None


def analyze(path):
    """读一个 jsonl，返回汇总指标。"""
    s = {
        "n": 0, "ok": 0, "err": 0, "no_sub": 0,
        "dur": 0.0, "elapsed": 0.0,
        "stage": {"split_frame": 0.0, "merge": 0.0, "getsrt": 0.0},
        "ocr": 0, "n_ocr": 0,
        "starts": [], "ends": [],
    }
    try:
        f = open(path, encoding="utf-8")
    except FileNotFoundError:
        return None
    with f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            try:
                r = json.loads(line)
            except json.JSONDecodeError:
                continue
            s["n"] += 1
            st = r.get("status")
            if st == "success":
                s["ok"] += 1
            elif st == "no_subtitle":
                s["no_sub"] += 1
            else:
                s["err"] += 1
            try:
                s["dur"] += float(r.get("duration") or 0)
            except (TypeError, ValueError):
                pass
            el = r.get("elapsed_seconds")
            if el:
                try:
                    s["elapsed"] += float(el)
                except (TypeError, ValueError):
                    pass
            sd = r.get("stage_durations") or {}
            for k in s["stage"]:
                try:
                    s["stage"][k] += float(sd.get(k) or 0)
                except (TypeError, ValueError):
                    pass
            ic = r.get("image_counts") or {}
            toc = ic.get("total_ocr_count")
            if toc:
                try:
                    s["ocr"] += int(toc)
                    s["n_ocr"] += 1
                except (TypeError, ValueError):
                    pass
            ds = parse_dt(r.get("process_start"))
            de = parse_dt(r.get("process_end"))
            if ds:
                s["starts"].append(ds)
            if de:
                s["ends"].append(de)
    return s


def derive(s):
    """从汇总算出对比指标。"""
    d = {}
    n = max(1, s["n"])
    d["记录数"] = s["n"]
    d["成功率%"] = round(s["ok"] / n * 100, 1)
    d["视频总时长h"] = round(s["dur"] / 3600, 1)
    # 墙钟跨度 + 实时倍率
    span = 0.0
    if s["starts"] and s["ends"]:
        span = (max(s["ends"]) - min(s["starts"])).total_seconds()
    d["墙钟跨度h"] = round(span / 3600, 2)
    d["实时倍率x"] = round(s["dur"] / span, 2) if span > 0 else 0
    d["视频/天"] = round(s["n"] / span * 86400) if span > 0 else 0
    d["有效并发"] = round(s["elapsed"] / span, 1) if span > 0 else 0
    # 平均每视频各阶段秒数
    d["抽帧s/视频"] = round(s["stage"]["split_frame"] / n, 1)
    d["拼接s/视频"] = round(s["stage"]["merge"] / n, 1)
    d["getsrt s/视频"] = round(s["stage"]["getsrt"] / n, 1)
    total_stage = sum(s["stage"].values()) or 1
    d["抽帧占比%"] = round(s["stage"]["split_frame"] / total_stage * 100)
    d["拼接占比%"] = round(s["stage"]["merge"] / total_stage * 100)
    d["getsrt占比%"] = round(s["stage"]["getsrt"] / total_stage * 100)
    d["平均OCR次/视频"] = round(s["ocr"] / s["n_ocr"]) if s["n_ocr"] else 0
    d["平均耗时s/视频"] = round(s["elapsed"] / n, 1)
    return d


def main():
    paths = sys.argv[1:]
    if len(paths) < 2:
        print("用法: python temp/compare_jsonl.py a.jsonl b.jsonl [c.jsonl ...]")
        return

    cols, names = [], []
    for p in paths:
        s = analyze(p)
        if s is None:
            print(f"找不到文件: {p}")
            return
        cols.append(derive(s))
        names.append(p.replace("数据.jsonl", "").replace(".jsonl", "") or p)

    keys = list(cols[0].keys())
    w = max(14, max(len(n) for n in names) + 2)
    print("=" * (18 + w * len(cols)))
    print(f"{'指标':<16}" + "".join(f"{n:>{w}}" for n in names))
    print("-" * (18 + w * len(cols)))
    for k in keys:
        print(f"{k:<16}" + "".join(f"{str(c[k]):>{w}}" for c in cols))
    print("=" * (18 + w * len(cols)))

    # 自动点评(两台时)
    if len(cols) == 2:
        a, b = cols
        slow_i = 0 if a["实时倍率x"] < b["实时倍率x"] else 1
        fast_i = 1 - slow_i
        print(f"\n【分析】{names[slow_i]} 更慢(实时倍率 "
              f"{cols[slow_i]['实时倍率x']}x vs {cols[fast_i]['实时倍率x']}x)")
        # 找慢在哪个阶段
        for stage, key in [("抽帧", "抽帧s/视频"), ("拼接", "拼接s/视频"), ("getsrt(OCR)", "getsrt s/视频")]:
            sv, fv = cols[slow_i][key], cols[fast_i][key]
            if fv and sv > fv * 1.3:
                print(f"  ▸ {stage} 慢: {sv}s vs {fv}s (慢 {sv/fv:.1f}x)")
        if cols[slow_i]["有效并发"] < cols[fast_i]["有效并发"] * 0.8:
            print(f"  ▸ 并发低: {cols[slow_i]['有效并发']} vs {cols[fast_i]['有效并发']}"
                  f"(CPU/内存/OCR 排队?)")
        if cols[slow_i]["平均OCR次/视频"] > cols[fast_i]["平均OCR次/视频"] * 1.3:
            print(f"  ▸ OCR 次数多: {cols[slow_i]['平均OCR次/视频']} vs "
                  f"{cols[fast_i]['平均OCR次/视频']}(视频更长/composite更多)")


if __name__ == "__main__":
    main()