初始提交：抖音视频批量采集流水线
App 端免签名接口（设备注册 + detail + CDN 直链），一体化流水线 下载→抽音→传COS→记录→删本地，AI 作品四档判定，四份文档： README（使用指南）、PROGRESS（批次进度）、RE（逆向全过程）、AI（判定规则）。 Co-Authored-By: Claude Code <noreply@anthropic.com>
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scripts/jsonl_to_xlsx.py
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scripts/jsonl_to_xlsx.py
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#!/usr/bin/env python3
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"""把 jsonl 清洗并导出为 xlsx。
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同时认两种输入：
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records.jsonl 流水线产物，字段全（标题/作者/标签/时长/COS 地址/raw）
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manifest.jsonl 老格式，只有 cos_mp4 / cos_mp3 / duration
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records.jsonl 内嵌了 raw，单行可能几十 KB、整个文件几百 MB，所以这里
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一律逐行流式读，任何时候都不把整个文件读进内存。选中的列也只留需要的
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那几个字段，raw 不会进内存驻留。
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清洗动作（每一项都会报告剔除了多少）：
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1. 丢弃无法解析的行（被 Ctrl-C 打断可能留下半行）
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2. 丢弃缺字段 / 字段类型不对的行
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3. 丢弃时长非正数的行
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4. 丢弃 URL 前缀不符合预期的行
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5. 按 mp4 地址去重，保留首次出现
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用法:
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python jsonl_to_xlsx.py
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python jsonl_to_xlsx.py -i records.jsonl -o "抖音-四川话.xlsx"
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python jsonl_to_xlsx.py -i records.jsonl --columns cos_mp4,cos_mp3,duration_sec
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python jsonl_to_xlsx.py --list-columns
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"""
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from __future__ import annotations
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# 移到 scripts/ tests/ 后，直接运行时脚本目录成了 sys.path[0]，
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# 把项目根加回来，import douyin / pipeline 才找得到。
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import sys as _sys
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from pathlib import Path as _Path
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_sys.path.insert(0, str(_Path(__file__).resolve().parent.parent))
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import argparse
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import json
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import sys
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from pathlib import Path
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from typing import Any, Dict, Iterator, List
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EXPECTED_PREFIX = "cos://asr-dig-data-1253181912/0005/zh/"
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# 列名 -> (表头, 取值函数)。取值函数只碰需要的字段，raw 不会被带进来。
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COLUMNS: Dict[str, tuple] = {
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"aweme_id": ("视频ID", lambda r: str(r.get("aweme_id") or "")),
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"title": ("标题", lambda r: r.get("title") or ""),
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"desc": ("原始描述", lambda r: r.get("desc") or ""),
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"tags": ("标签", lambda r: " ".join(r.get("tags") or [])),
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"author": ("作者", lambda r: (r.get("author") or {}).get("nickname", "")),
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"author_uid": ("作者UID", lambda r: (r.get("author") or {}).get("uid", "")),
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"create_time": ("发布时间", lambda r: r.get("create_time_str") or ""),
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"duration_sec": ("时长(秒)", _dur := (lambda r: r.get("duration_sec",
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r.get("duration")))),
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"duration": ("时长(秒)", _dur),
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"cos_mp4": ("cosmp4地址", lambda r: r.get("cos_mp4") or ""),
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"cos_mp3": ("cosmp3地址", lambda r: r.get("cos_mp3") or ""),
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"size_mp4": ("mp4字节数", lambda r: r.get("size_mp4") or 0),
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"size_mp3": ("mp3字节数", lambda r: r.get("size_mp3") or 0),
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"play": ("播放数", lambda r: (r.get("stats") or {}).get("play", 0)),
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"digg": ("点赞数", lambda r: (r.get("stats") or {}).get("digg", 0)),
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"comment": ("评论数", lambda r: (r.get("stats") or {}).get("comment", 0)),
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"source_url": ("原始链接", lambda r: r.get("source_url") or ""),
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}
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DEFAULT_COLUMNS = ["cos_mp4", "cos_mp3", "duration_sec"]
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FULL_COLUMNS = ["aweme_id", "title", "author", "create_time", "tags",
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"duration_sec", "cos_mp4", "cos_mp3"]
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NUMERIC = {"duration_sec", "duration", "size_mp4", "size_mp3",
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"play", "digg", "comment"}
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def iter_lines(path: Path) -> Iterator[str]:
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with open(path, "r", encoding="utf-8", errors="replace") as f:
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for line in f:
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line = line.strip()
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if line:
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yield line
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def clean(path: Path, prefix: str, columns: List[str]):
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"""流式清洗，只保留选中的列。"""
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rows: List[List[Any]] = []
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seen: set = set()
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dropped = {"解析失败": 0, "字段缺失": 0, "时长非法": 0, "地址异常": 0, "重复": 0}
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total = 0
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dur_idx = next((i for i, c in enumerate(columns)
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if c in ("duration_sec", "duration")), None)
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for line in iter_lines(path):
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total += 1
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try:
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r = json.loads(line)
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except ValueError:
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dropped["解析失败"] += 1
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continue
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mp4, mp3 = r.get("cos_mp4"), r.get("cos_mp3")
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dur = r.get("duration_sec", r.get("duration"))
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if not isinstance(mp4, str) or not isinstance(mp3, str) or dur is None:
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dropped["字段缺失"] += 1
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continue
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if not isinstance(dur, (int, float)) or isinstance(dur, bool) or dur <= 0:
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dropped["时长非法"] += 1
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continue
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if not mp4.startswith(prefix) or not mp3.startswith(prefix):
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dropped["地址异常"] += 1
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continue
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if mp4 in seen:
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dropped["重复"] += 1
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continue
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seen.add(mp4)
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row = [COLUMNS[c][1](r) for c in columns]
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if dur_idx is not None:
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row[dur_idx] = float(row[dur_idx])
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rows.append(row)
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return rows, dropped, total, dur_idx
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def write_xlsx(rows, headers, out: Path, sheet: str, dur_idx) -> None:
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from openpyxl import Workbook
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from openpyxl.styles import Alignment, Font, PatternFill
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from openpyxl.utils import get_column_letter
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wb = Workbook()
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ws = wb.active
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ws.title = sheet
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ws.append(headers)
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head_font = Font(bold=True, color="FFFFFF")
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head_fill = PatternFill("solid", fgColor="4472C4")
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for c in range(1, len(headers) + 1):
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cell = ws.cell(row=1, column=c)
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cell.font = head_font
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cell.fill = head_fill
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cell.alignment = Alignment(horizontal="center", vertical="center")
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for r in rows:
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ws.append(r)
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# 时长保留 3 位小数，与 ffprobe 输出精度一致
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if dur_idx is not None:
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for row in ws.iter_rows(min_row=2, min_col=dur_idx + 1, max_col=dur_idx + 1):
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for cell in row:
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cell.number_format = "0.000"
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for i, head in enumerate(headers):
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widest = max((len(str(r[i])) for r in rows), default=10)
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width = min(max(len(head) + 4, widest + 2), 60)
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ws.column_dimensions[get_column_letter(i + 1)].width = width
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ws.freeze_panes = "A2" # 表头固定
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ws.auto_filter.ref = ws.dimensions # 开筛选
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wb.save(out)
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def main(argv: list[str] | None = None) -> int:
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ap = argparse.ArgumentParser(description="jsonl -> xlsx")
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ap.add_argument("-i", "--input", default="records/records.jsonl")
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ap.add_argument("-o", "--output", default="exports/抖音-四川话.xlsx")
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ap.add_argument("--sheet", default="抖音-四川话")
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ap.add_argument("--prefix", default=EXPECTED_PREFIX)
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ap.add_argument("--columns", default="",
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help=f"逗号分隔的列，默认 {','.join(DEFAULT_COLUMNS)}；"
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"用 full 展开为常用全字段")
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ap.add_argument("--list-columns", action="store_true", help="列出可用列名后退出")
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args = ap.parse_args(argv)
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if args.list_columns:
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print("可用列：")
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for k, (head, _) in COLUMNS.items():
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print(f" {k:<14} {head}")
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return 0
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if not args.columns:
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columns = list(DEFAULT_COLUMNS)
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elif args.columns.strip() == "full":
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columns = list(FULL_COLUMNS)
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else:
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columns = [c.strip() for c in args.columns.split(",") if c.strip()]
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bad = [c for c in columns if c not in COLUMNS]
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if bad:
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print(f"[错误] 未知列名 {bad}，用 --list-columns 看可选项", file=sys.stderr)
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return 2
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src = Path(args.input)
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if not src.exists():
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print(f"[错误] 找不到 {src}", file=sys.stderr)
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return 2
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rows, dropped, total, dur_idx = clean(src, args.prefix, columns)
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print(f"读入 {total} 行")
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if sum(dropped.values()):
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for k, v in dropped.items():
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if v:
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print(f" 剔除 {k}: {v}")
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else:
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print(" 清洗检查全部通过，无需剔除")
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print(f"保留 {len(rows)} 行")
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if not rows:
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print("[错误] 清洗后没有数据", file=sys.stderr)
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return 3
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headers = [COLUMNS[c][0] for c in columns]
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out = Path(args.output)
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write_xlsx(rows, headers, out, args.sheet, dur_idx)
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print(f"\n已写入 {out}")
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print(f" {len(rows)} 行 × {len(headers)} 列：{' | '.join(headers)}")
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if dur_idx is not None:
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ds = [r[dur_idx] for r in rows]
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print(f" 总时长 {sum(ds) / 3600:.2f} 小时，平均 {sum(ds) / len(ds):.1f} 秒，"
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f"最短 {min(ds):.3f}，最长 {max(ds):.3f}")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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