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refactor(music): 音乐识别核心下沉 MetaMusic 并优化 MusicBrainz 检索
- 标题解析核心从 app/helper/music.py 迁移到 MetaMusic（apply_title）， 删除 music helper，metainfo/chain 调用点切换 - 解析增强：全角归一、场景点分命名、年份区间双模式、日期前缀、 视频标记剔除、VA 合辑署名归一、尾部年份提取、CJK 连字符拆分 - MusicBrainz 性能：全局 Session keep-alive 复用（6.3s→0.35s/请求）， 无艺术家线索时跳过专辑回退检索 - 候选挑选支持冒号副标题弱匹配，检索式剥离尾部年份减少无效检索 - 测试：test_metamusic 32 案例、musicbrainz 弱匹配/检索式新用例
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jxxghp
283
scripts/music_recognize_batch_test.py
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283
scripts/music_recognize_batch_test.py
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#!/usr/bin/env python3
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"""多站点音乐种子批量识别测试工具。
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用途：
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1. fetch - 用生产数据库中的站点 Cookie 抓取多个站点音乐分区种子标题
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2. test - 对标题批量执行音乐识别链路（与识别测试页相同），输出 CSV 报告与命中率汇总
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3. 抓取结果落盘后可离线重跑 test，用于优化识别程序前后对比
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约束：
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- 生产库仅以只读 URI 模式打开，不做任何写入
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- 识别仅调用 MusicBrainz 公共 API，遵守模块内置限流与退避重试
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- 抓取仅请求各站点音乐分区浏览页若干页，对站点无压力
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用法：
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.venv/bin/python scripts/music_recognize_batch_test.py --fetch # 抓取并测试
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.venv/bin/python scripts/music_recognize_batch_test.py --fetch --sites ptsbao,springsunday
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.venv/bin/python scripts/music_recognize_batch_test.py # 用已保存标题离线重测
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"""
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import argparse
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import csv
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import sqlite3
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import sys
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from pathlib import Path
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import yaml
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# 保证从仓库根目录外执行时也能导入 app 包
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ROOT = Path(__file__).resolve().parents[1]
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sys.path.insert(0, str(ROOT))
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# 生产数据库（site 表中的站点 Cookie）与站点索引配置源文件目录
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DB_PATH = Path.home() / "Documents" / "MoviePilot" / "user.db"
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INDEXER_DIR = Path.home() / "MPProjects" / "MoviePilot-Build" / "sites" / "private"
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TITLES_FILE = ROOT / "config" / "temp" / "music_batch_titles.txt"
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REPORT_FILE = ROOT / "config" / "temp" / "music_batch_report.csv"
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# 各站点音乐分区浏览配置：yml 配置、浏览路径（{page} 由 SiteSpider 渲染）、每站抓取上限
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# NexusPHP 站点统一用 torrents.php?cat=<音乐分类>，憨憨音乐专区走 special.php
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SITES = [
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{"key": "hhanclub", "name": "憨憨", "yml": "hhanclub.yml",
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"browse": "special.php?page={page}", "limit": 30},
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{"key": "ptsbao", "name": "烧包乐园", "yml": "ptsbao.yml",
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"browse": "torrents.php?cat=414&page={page}", "limit": 30},
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{"key": "springsunday", "name": "春天", "yml": "springsunday.yml",
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"browse": "torrents.php?cat=508&page={page}", "limit": 30},
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{"key": "hdhome", "name": "家园", "yml": "hdhome.yml",
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"browse": "torrents.php?cat[]=439&cat[]=440&page={page}", "limit": 30},
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{"key": "btschool", "name": "学校", "yml": "btschool.yml",
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"browse": "torrents.php?cat=409&page={page}", "limit": 30},
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{"key": "0ff", "name": "自由农场", "yml": "0ff.yml",
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"browse": "torrents.php?cat=407&page={page}", "limit": 30},
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{"key": "hdfans", "name": "红豆饭", "yml": "hdfans.yml",
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"browse": "torrents.php?cat=406&page={page}", "limit": 30},
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{"key": "wintersakura", "name": "冬樱", "yml": "wintersakura.yml",
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"browse": "torrents.php?cat=408&page={page}", "limit": 30},
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{"key": "audiences", "name": "观众", "yml": "audiences.yml",
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"browse": "torrents.php?cat=408&page={page}", "limit": 30},
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]
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def load_site_credentials(domains: list[str]) -> dict[str, dict]:
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"""只读打开生产库，按域名批量取出站点 Cookie 与 UA。"""
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if not DB_PATH.exists():
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sys.exit(f"生产数据库不存在：{DB_PATH}")
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credentials: dict[str, dict] = {}
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con = sqlite3.connect(f"file:{DB_PATH}?mode=ro", uri=True)
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try:
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for domain in domains:
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row = con.execute(
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"SELECT cookie, ua FROM site WHERE domain = ?", (domain,)
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).fetchone()
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if row and row[0]:
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credentials[domain] = {"cookie": row[0], "ua": row[1] or None}
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finally:
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con.close()
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return credentials
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def build_indexer(site: dict, credential: dict) -> dict:
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"""加载站点索引配置并注入凭据，补充无关键词浏览所需的 browse 配置。
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索引 yml 没有 browse 节，这里按站点音乐分区构造浏览路径，
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列表与字段解析复用 yml 中 torrents 节的现有选择器，不改动配置文件。
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"""
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with open(INDEXER_DIR / site["yml"], "r", encoding="utf-8") as f:
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indexer = yaml.safe_load(f)
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indexer["cookie"] = credential["cookie"]
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if credential["ua"]:
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indexer["ua"] = credential["ua"]
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indexer["browse"] = {"path": site["browse"]}
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return indexer
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def fetch_site_titles(site: dict, indexer: dict, max_pages: int) -> list[str]:
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"""翻页抓取单个站点音乐分区种子标题，按标题去重并保留出现顺序。"""
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from app.modules.indexer.spider import SiteSpider
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from app.schemas.types import MediaType
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titles: list[str] = []
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seen: set[str] = set()
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for page in range(max_pages):
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spider = SiteSpider(indexer=indexer, mtype=MediaType.MUSIC, page=page)
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torrents = spider.get_torrents()
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if spider.is_error:
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print(f" [{site['name']}] 第 {page} 页请求失败（Cookie 可能失效或站点不可达），跳过该站点")
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return []
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if not torrents:
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break
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for torrent in torrents:
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title = (torrent.get("title") or "").strip()
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if not title or title in seen:
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continue
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seen.add(title)
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titles.append(title)
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if len(titles) >= site["limit"]:
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break
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print(f" [{site['name']}] 获取 {len(titles)} 条")
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return titles[:site["limit"]]
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def fetch_titles(site_keys: list[str], max_pages: int) -> list[tuple[str, str]]:
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"""按配置抓取多个站点音乐分区标题，返回 (站点名, 标题) 列表。"""
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sites = [site for site in SITES if not site_keys or site["key"] in site_keys]
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unknown = set(site_keys) - {site["key"] for site in sites}
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if unknown:
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sys.exit(f"未知站点：{', '.join(sorted(unknown))}；可选：{', '.join(site['key'] for site in SITES)}")
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domains = []
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for site in sites:
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with open(INDEXER_DIR / site["yml"], "r", encoding="utf-8") as f:
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domain = (yaml.safe_load(f).get("domain") or "").replace("https://", "").replace("http://", "").rstrip("/")
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site["domain"] = domain
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domains.append(domain)
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credentials = load_site_credentials(domains)
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results: list[tuple[str, str]] = []
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for site in sites:
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credential = credentials.get(site["domain"])
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if not credential:
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print(f" [{site['name']}] 未配置 Cookie，跳过")
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continue
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indexer = build_indexer(site, credential)
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for title in fetch_site_titles(site, indexer, max_pages):
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results.append((site["name"], title))
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return results
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def recognize_one(module, title: str) -> dict:
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"""对单条标题执行与识别测试页相同的解析+识别链路，并给出失败归因。"""
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from app.chain.music import MusicChain
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row = {"title": title}
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try:
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meta = MusicChain.parse_query(title)
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row.update({
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"parsed_title": meta.title,
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"parsed_artists": " / ".join(meta.artists or []),
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"parsed_format": meta.audio_format or "",
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})
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# 拆开检索与候选挑选两步，便于区分零命中与比对失配
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candidates = module._search_recordings(meta, limit=10)
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matched = module._select_candidate(meta, candidates, source="musicbrainz")
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hit_label = "命中"
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albums: list = []
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# 与正式链路一致：专辑挑选要求艺术家命中，无艺术家线索时跳过专辑回退检索
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if not matched and meta.artists:
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albums = module._search_albums(meta, limit=10)
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matched = module._select_album_candidate(meta, albums)
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hit_label = "命中(专辑)"
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if matched:
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row.update({
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"status": hit_label,
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"matched_title": matched.title,
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"matched_artists": " / ".join(matched.artists or []),
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"matched_album": matched.album or "",
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"matched_year": matched.year or "",
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"media_id": matched.media_id,
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})
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elif candidates:
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# 有候选但全部比对失配，列出最接近的候选方便归因
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top = candidates[0]
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row.update({
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"status": "候选比对失配",
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"matched_title": f"{top.title} | {' / '.join(top.artists or [])}",
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})
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elif albums:
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row.update({
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"status": "专辑候选失配",
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"matched_title": f"{albums[0].title} | {' / '.join(albums[0].artists or [])}",
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})
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elif not meta.title:
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row.update({"status": "解析失败"})
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else:
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row.update({"status": "检索零命中"})
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except Exception as err: # pylint: disable=broad-except
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row.update({"status": "异常", "matched_title": str(err)[:200]})
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return row
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def run_batch(entries: list[tuple[str, str]]) -> list[dict]:
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"""批量执行识别并写出 CSV 报告，打印命中率汇总。"""
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from app.modules.musicbrainz import MusicBrainzModule
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module = MusicBrainzModule()
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module.init_module()
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rows = []
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for index, (site_name, title) in enumerate(entries, 1):
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row = recognize_one(module, title)
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row["site"] = site_name
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rows.append(row)
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if index % 20 == 0 or index == len(entries):
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print(f"识别进度 {index}/{len(entries)}")
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REPORT_FILE.parent.mkdir(parents=True, exist_ok=True)
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fieldnames = [
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"site", "title", "status", "parsed_title", "parsed_artists", "parsed_format",
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"matched_title", "matched_artists", "matched_album", "matched_year", "media_id",
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]
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with open(REPORT_FILE, "w", newline="", encoding="utf-8-sig") as f:
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writer = csv.DictWriter(f, fieldnames=fieldnames, extrasaction="ignore")
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writer.writeheader()
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writer.writerows(rows)
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# 按状态汇总，输出命中率与失败分布
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summary: dict[str, int] = {}
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for row in rows:
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summary[row["status"]] = summary.get(row["status"], 0) + 1
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total = len(rows) or 1
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print(f"\n报告已写入：{REPORT_FILE}")
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for status, count in sorted(summary.items(), key=lambda kv: -kv[1]):
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print(f" {status}: {count} ({count / total:.0%})")
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# 分站点命中率，便于定位特定站点标题格式问题
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print("分站点命中率：")
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for site_name in sorted({row["site"] for row in rows}):
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site_rows = [row for row in rows if row["site"] == site_name]
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hits = sum(1 for row in site_rows if row["status"].startswith("命中"))
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print(f" {site_name}: {hits}/{len(site_rows)} ({hits / max(len(site_rows), 1):.0%})")
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return rows
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def read_titles_file() -> list[tuple[str, str]]:
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"""读取落盘标题，兼容旧版纯标题格式（无站点前缀记为「憨憨」）。"""
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entries: list[tuple[str, str]] = []
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for line in TITLES_FILE.read_text(encoding="utf-8").splitlines():
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line = line.strip()
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if not line:
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continue
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if "\t" in line:
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site_name, title = line.split("\t", 1)
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else:
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site_name, title = "憨憨", line
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entries.append((site_name, title))
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return entries
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def main() -> None:
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parser = argparse.ArgumentParser(description="多站点音乐种子批量识别测试")
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parser.add_argument("--fetch", action="store_true", help="重新抓取种子标题（默认复用已保存列表）")
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parser.add_argument("--sites", default="", help="指定站点 key 逗号分隔，缺省抓取全部配置站点")
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parser.add_argument("--pages", type=int, default=3, help="每站最大翻页数")
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args = parser.parse_args()
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if args.fetch or not TITLES_FILE.exists():
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site_keys = [key.strip() for key in args.sites.split(",") if key.strip()]
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entries = fetch_titles(site_keys, max_pages=args.pages)
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if not entries:
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sys.exit("未抓取到任何种子标题")
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TITLES_FILE.parent.mkdir(parents=True, exist_ok=True)
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TITLES_FILE.write_text(
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"\n".join(f"{site_name}\t{title}" for site_name, title in entries),
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encoding="utf-8",
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)
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print(f"已保存 {len(entries)} 条标题到 {TITLES_FILE}")
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else:
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entries = read_titles_file()
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print(f"复用已保存的 {len(entries)} 条标题")
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run_batch(entries)
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if __name__ == "__main__":
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main()
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