feat(server): scrapeMedia 刮削任务,入库后自动刮削(SCR-1)

- 文件道任务 scrapeMedia:NFO 原子写入、图片经图片缓存下载(并发 4,失败不阻塞 NFO)、只补缺失 / 全部覆盖 - 设置 organize.scrapeAfterImport / scrapeMode / scrapeImages / scrapeEpisodeThumbs - POST /library/{id}/scrape、详情 scrape 状态;files/scrape writeNfo 与 scrape-batch write 走同一任务 - 迁移 0057_media_scrape、原因码、审计 organize.scrape - 与 MP 输出的 NFO 差分测试(apps/server/test/scrape) Co-Authored-By: Claude Opus 5.5 <[email protected]>
2026-09-30 22:36:14 +08:00
1 parent 861f799615
commit f38eca419e
@@ -305,8 +305,18 @@ describe.skipIf(skip)("files 识别 / 整理 / 探测 / 刮削", () => {

    const s = await h.api("POST", "/files/scrape", { idempotencyKey: key(), mediaEntityId: film, writeNfo: true });
    expect(s.status).toBe(200);
-    expect(s.body.data).toMatchObject({ mediaEntityId: film, nfo: "not_implemented", images: "not_requested" });
+    // SCR-1:writeNfo 另排 scrapeMedia(写 NFO 与图片到媒体库目录)
+    expect(s.body.data).toMatchObject({ mediaEntityId: film, nfo: "queued", images: "not_requested" });
+    expect(s.body.data.scrapeTaskId).toBeTruthy();
    expect(h.engine.enqueued.some((e) => e.task === "refreshMetadata")).toBe(true);
+    expect(h.engine.enqueued.some((e) => e.task === "scrapeMedia")).toBe(true);
+    const b = await h.api("POST", "/files/scrape-batch", {
+      idempotencyKey: key(),
+      mediaEntityIds: [film],
+      write: true,
+    });
+    expect(b.status).toBe(200);
+    expect(b.body.data.submitted).toHaveLength(1);
    const none = await h.api("POST", "/files/scrape", { idempotencyKey: key(), mediaEntityId: show });
    expect(none.status).toBe(400);
  });
@@ -0,0 +1,51 @@
+"""SCR-1 刮削差分:用 MP 上游的 TmdbScraper(themoviedb/scraper.py)从同一份 TMDB 原始响应生成 NFO,写 scrape-mp.json。
+
+用法(MP 仓库根目录,用其 .venv):
+  cd /opt/moviepilot-plus/upstream/MoviePilot && PYTHONPATH=. \
+  .venv/bin/python /opt/uhd_media_tool/apps/server/test/scrape/gen-scrape-mp.py
+
+只记录行为输出,不复制 MP 源码。MediaInfo 用 MP 自己的 set_tmdb_info(TMDB 详情 → 统一字段),
+季 / 集直接喂 TMDB 季详情(与 MP get_metadata_nfo 取到的一致)。图片命名按 MP 代码行为登记在 nfo-mp-diff.test.ts。
+"""
+
+import json
+import pathlib
+
+from app.domain.context import MediaInfo
+from app.domain.projection.tmdb import configure_image_url_builder
+from app.modules.themoviedb.scraper import TmdbScraper
+
+HERE = pathlib.Path(__file__).parent
+raw = json.loads((HERE / "tmdb-raw.json").read_text(encoding="utf-8"))
+
+# 启动组合根里注入的 TMDB 图片地址(settings.TMDB_IMAGE_URL,原图)
+configure_image_url_builder(lambda p: f"https://image.tmdb.org/t/p/original/{p.removeprefix('/')}")
+
+s = TmdbScraper()
+
+
+def xml(doc) -> str:
+    return doc.toprettyxml(indent="  ", encoding="utf-8").decode("utf-8")
+
+
+def media(info: dict, media_type: str) -> MediaInfo:
+    mi = MediaInfo()
+    mi.set_tmdb_info({**info, "media_type": media_type})
+    return mi
+
+
+out = {}
+out["movie"] = xml(s._TmdbScraper__gen_movie_nfo_file(mediainfo=media(raw["/movie/157336"], "movie")))
+out["tvshow"] = xml(s._TmdbScraper__gen_tv_nfo_file(mediainfo=media(raw["/tv/95396"], "tv")))
+season = raw["/tv/95396/season/1"]
+out["season1"] = xml(s._TmdbScraper__gen_tv_season_nfo_file(seasoninfo=season, season=1))
+for ep in season["episodes"]:
+    n = ep["episode_number"]
+    out[f"s01e{n:02d}"] = xml(
+        s._TmdbScraper__gen_tv_episode_nfo_file(tmdbid=95396, episodeinfo=ep, season=1, episode=n)
+    )
+out["seasonPosterName"] = TmdbScraper.get_season_poster(season, 1)[0]
+out["seasonSpecialsPosterName"] = TmdbScraper.get_season_poster({"poster_path": "/x.jpg"}, 0)[0]
+
+(HERE / "scrape-mp.json").write_text(json.dumps(out, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
+print(f"写入 {len(out)} 项 → scrape-mp.json")
@@ -0,0 +1,69 @@
+{
+  "_note": "SCR-1 NFO 与 MP 的已登记差异(按样例、按元素)。测试先去掉双方的空元素(MP 缺值写 <x/>、空 CDATA、评分 0,我们不写),再去掉这里登记的元素后逐行比较;登记的元素必须确实不同,差异消除后删掉登记。",
+  "deviations": [
+    {
+      "case": "movie",
+      "tag": "studio",
+      "reason": "本地不存 TMDB production_companies,电影不写出品公司(Emby / Jellyfin 刷新时会自己补)"
+    },
+    {
+      "case": "movie",
+      "tag": "country",
+      "reason": "制片国取 TMDB origin_country(代码转中文名);MP 取 production_countries(本例多一个英国)"
+    },
+    {
+      "case": "movie",
+      "tag": "tagline",
+      "reason": "我们额外写标语,MP 不写"
+    },
+    {
+      "case": "tvshow",
+      "tag": "studio",
+      "reason": "剧集写播出平台(TMDB networks,本例 Apple TV+);MP 写出品公司 production_companies"
+    },
+    {
+      "case": "s01e01",
+      "tag": "uniqueid",
+      "reason": "本地不存 TMDB 集 id,集 NFO 不写 uniqueid,媒体服务器按季号集号匹配"
+    },
+    {
+      "case": "s01e01",
+      "tag": "tmdbid",
+      "reason": "同上"
+    },
+    {
+      "case": "s01e01",
+      "tag": "runtime",
+      "reason": "我们额外写集时长,MP 不写"
+    },
+    {
+      "case": "s01e02",
+      "tag": "uniqueid",
+      "reason": "同 s01e01"
+    },
+    {
+      "case": "s01e02",
+      "tag": "tmdbid",
+      "reason": "同 s01e01"
+    },
+    {
+      "case": "s01e02",
+      "tag": "runtime",
+      "reason": "同 s01e01"
+    }
+  ],
+  "images": [
+    {
+      "role": "movie poster / fanart",
+      "mp": "poster.jpg、backdrop.jpg、fanart.jpg(作品目录)",
+      "ours": "poster.jpg、fanart.jpg",
+      "reason": "backdrop.jpg 是 fanart.jpg 的副本,Emby / Jellyfin / Kodi 都认 fanart.jpg,不写重复文件"
+    },
+    {
+      "role": "episode thumb",
+      "mp": "<视频名>.jpg",
+      "ours": "<视频名>-thumb.jpg",
+      "reason": "Kodi 约定 -thumb 后缀;Jellyfin / Emby 同样识别,且不会和同名海报规则冲突"
+    }
+  ]
+}
@@ -0,0 +1,149 @@
+import { readFileSync } from "node:fs";
+import { fetchRichDetail, fetchRichSeason } from "@umt/adapters";
+import { episodeNfo, planScrapeTargets, seasonNfo, seasonPosterName, workNfo } from "@umt/domain";
+import { describe, expect, it } from "vitest";
+import { nfoEpisode, nfoSeason, nfoWork } from "../../src/modules/acquisition-organize/services/scrape-input.ts";
+import { richEntityFields } from "../../src/modules/sources-identity/service/metadata-rich.ts";
+
+// SCR-1 NFO 差分:同一份 TMDB 原始响应(tmdb-raw.json),MP 走 set_tmdb_info + TmdbScraper(gen-scrape-mp.py → scrape-mp.json),
+// 我们走 fetchRichDetail / fetchRichSeason → 字段投影(metadata)→ scrape-input → domain NFO 生成器。
+// 双方去掉空元素后逐行比较,已登记的差异(nfo-deviations.json)按元素排除并要求确实不同。
+
+const read = (f: string) => JSON.parse(readFileSync(new URL(f, import.meta.url), "utf8"));
+const raw = read("./tmdb-raw.json") as Record<string, unknown>;
+const mp = read("./scrape-mp.json") as Record<string, string>;
+const devs = read("./nfo-deviations.json").deviations as { case: string; tag: string }[];
+
+const LANGS = ["zh-CN", "zh-SG", "zh-TW", "zh-HK", "en-US"];
+const client = {
+  async getJson<T>(path: string): Promise<T> {
+    const r = raw[path];
+    if (!r) throw new Error(`fixture 缺 ${path}`);
+    return structuredClone(r) as T;
+  },
+};
+const final = (fields: Record<string, { value: unknown }>) =>
+  Object.fromEntries(Object.entries(fields).map(([k, v]) => [k, { value: v.value }]));
+
+async function ours(): Promise<Record<string, string>> {
+  const out: Record<string, string> = {};
+  const movie = await fetchRichDetail(client, "movie", 157336, LANGS);
+  out.movie = workNfo(
+    nfoWork(
+      {
+        kind: "movie",
+        title: movie.title,
+        original_title: movie.originalTitle,
+        year: movie.year,
+        metadata: final(richEntityFields(movie) as never),
+      },
+      { tmdb: "157336" },
+    ),
+  );
+  const tv = await fetchRichDetail(client, "tv", 95396, LANGS);
+  out.tvshow = workNfo(
+    nfoWork(
+      {
+        kind: "series",
+        title: tv.title,
+        original_title: tv.originalTitle,
+        year: tv.year,
+        metadata: final(richEntityFields(tv) as never),
+      },
+      { tmdb: "95396" },
+    ),
+  );
+  const sd = await fetchRichSeason(client, 95396, 1, LANGS, { now: new Date("2026-01-01") });
+  out.season1 = seasonNfo(
+    nfoSeason(1, {
+      season_number: 1,
+      episode_number: null,
+      title: sd.name,
+      air_date: sd.airDate,
+      metadata: { name: { value: sd.name }, overview: { value: sd.overview }, airDate: { value: sd.airDate } },
+    }),
+  );
+  for (const e of sd.episodes) {
+    out[`s01e${String(e.episodeNumber).padStart(2, "0")}`] = episodeNfo(
+      nfoEpisode(1, e.episodeNumber, {
+        season_number: 1,
+        episode_number: e.episodeNumber,
+        title: e.name,
+        air_date: e.airDate,
+        metadata: {
+          name: { value: e.name },
+          overview: { value: e.overview },
+          airDate: { value: e.airDate },
+          runtime: { value: e.runtime },
+          voteAverage: { value: e.voteAverage },
+        },
+      }),
+    );
+  }
+  return out;
+}
+
+/** 去空元素(MP 缺值写 <x/>、空 CDATA、评分 0) */
+const normalize = (xml: string) =>
+  xml
+    .split("\n")
+    .filter((l) => l.trim() !== "")
+    .filter((l) => !/^\s*<[\w]+(\s[^>]*)?\/>$/.test(l))
+    .filter((l) => !/<!\[CDATA\[\]\]>/.test(l))
+    .filter((l) => !/^\s*<rating>0<\/rating>$/.test(l));
+const tagOf = (l: string) => /^ {2}<(\w+)/.exec(l)?.[1] ?? null;
+
+describe("NFO 与 MP 差分", async () => {
+  const mine = await ours();
+  const cases = ["movie", "tvshow", "season1", "s01e01", "s01e02"];
+
+  it.each(cases)("%s:结构与取值一致(已登记差异除外)", (c) => {
+    const skip = new Set(devs.filter((d) => d.case === c).map((d) => d.tag));
+    const a = normalize(mp[c]!).filter((l) => !skip.has(tagOf(l) ?? ""));
+    const b = normalize(mine[c]!).filter((l) => !skip.has(tagOf(l) ?? ""));
+    expect(b).toEqual(a);
+    for (const tag of skip) {
+      const ma = normalize(mp[c]!).filter((l) => tagOf(l) === tag);
+      const mb = normalize(mine[c]!).filter((l) => tagOf(l) === tag);
+      expect(mb, `登记的差异 ${c}.${tag} 已消失,删掉登记`).not.toEqual(ma);
+    }
+  });
+
+  it("编码与声明:UTF-8、两空格缩进、末尾换行,和 MP 一致", () => {
+    for (const c of cases) {
+      expect(mine[c]!.split("\n")[0]).toBe(mp[c]!.split("\n")[0]);
+      expect(mine[c]!.endsWith("\n")).toBe(true);
+    }
+  });
+
+  it("季海报命名与 MP get_season_poster 一致", () => {
+    expect(seasonPosterName(1)).toBe(mp.seasonPosterName);
+    expect(seasonPosterName(0)).toBe(mp.seasonSpecialsPosterName);
+  });
+
+  it("文件命名:对照 MP scraping.py 的目标路径(差异见 nfo-deviations.json images)", () => {
+    const t = planScrapeTargets({
+      kind: "tv",
+      workDir: "人生切割术 (2022)",
+      videos: [{ path: "人生切割术 (2022)/Season 1/人生切割术 - S01E01 - 第 1 集.mkv", season: 1, episode: 1 }],
+      images: {
+        posterPath: "/p.jpg",
+        backdropPath: "/b.jpg",
+        seasonPosters: new Map([[1, "/s.jpg"]]),
+        stills: new Map([["1:1", "/e.jpg"]]),
+      },
+      options: { images: true, episodeThumbs: true },
+    });
+    // MP:tvshow.nfo(TV)、season.nfo(SEASON)、<stem>.nfo(EPISODE);季海报根目录 seasonXX-poster + 季目录 poster
+    expect(t.map((x) => x.path)).toEqual([
+      "人生切割术 (2022)/tvshow.nfo",
+      "人生切割术 (2022)/poster.jpg",
+      "人生切割术 (2022)/fanart.jpg",
+      "人生切割术 (2022)/Season 1/season.nfo",
+      "人生切割术 (2022)/season01-poster.jpg",
+      "人生切割术 (2022)/Season 1/poster.jpg",
+      "人生切割术 (2022)/Season 1/人生切割术 - S01E01 - 第 1 集.nfo",
+      "人生切割术 (2022)/Season 1/人生切割术 - S01E01 - 第 1 集-thumb.jpg",
+    ]);
+  });
+});
@@ -0,0 +1,9 @@
+{
+  "movie": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<movie>\n  <tmdbid>157336</tmdbid>\n  <uniqueid type=\"tmdb\" default=\"false\">157336</uniqueid>\n  <imdbid>tt0816692</imdbid>\n  <uniqueid type=\"imdb\" default=\"true\">tt0816692</uniqueid>\n  <plot><![CDATA[在不远的未来，随着地球自然环境的恶化，人类面临着无法生存的威胁。一群宇航员穿越虫洞，为人类寻找新家园。]]></plot>\n  <outline><![CDATA[在不远的未来，随着地球自然环境的恶化，人类面临着无法生存的威胁。一群宇航员穿越虫洞，为人类寻找新家园。]]></outline>\n  <director tmdbid=\"525\">克里斯托弗·诺兰</director>\n  <actor>\n    <name>马修·麦康纳</name>\n    <type>Actor</type>\n    <role>Cooper</role>\n    <tmdbid>10297</tmdbid>\n    <thumb>https://image.tmdb.org/t/p/original/lCySuYjhXix3FzQdS4oceDDrXKI.jpg</thumb>\n    <profile>https://www.themoviedb.org/person/10297</profile>\n  </actor>\n  <actor>\n    <name>安妮·海瑟薇</name>\n    <type>Actor</type>\n    <role>Brand</role>\n    <tmdbid>1813</tmdbid>\n    <thumb>https://image.tmdb.org/t/p/original/s6tflSD20MGz04ZR2R1lZvhmC4Y.jpg</thumb>\n    <profile>https://www.themoviedb.org/person/1813</profile>\n  </actor>\n  <actor>\n    <name>杰西卡·查斯坦</name>\n    <type>Actor</type>\n    <role>Murph</role>\n    <tmdbid>83002</tmdbid>\n    <profile>https://www.themoviedb.org/person/83002</profile>\n  </actor>\n  <genre>冒险</genre>\n  <genre>剧情</genre>\n  <genre>科幻</genre>\n  <rating>8.5</rating>\n  <studio>Legendary Pictures</studio>\n  <country>英国</country>\n  <country>美国</country>\n  <runtime>169</runtime>\n  <title>星际穿越</title>\n  <originaltitle>Interstellar</originaltitle>\n  <premiered>2014-11-05</premiered>\n  <year>2014</year>\n</movie>\n",
+  "tvshow": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<tvshow>\n  <tmdbid>95396</tmdbid>\n  <uniqueid type=\"tmdb\" default=\"false\">95396</uniqueid>\n  <tvdbid>371980</tvdbid>\n  <uniqueid type=\"tvdb\">371980</uniqueid>\n  <imdbid>tt11280740</imdbid>\n  <uniqueid type=\"imdb\" default=\"true\">tt11280740</uniqueid>\n  <plot><![CDATA[马克领导着一个办公室团队，他们的记忆被手术分割，工作与生活从此一分为二。]]></plot>\n  <outline><![CDATA[马克领导着一个办公室团队，他们的记忆被手术分割，工作与生活从此一分为二。]]></outline>\n  <actor>\n    <name>亚当·斯科特</name>\n    <type>Actor</type>\n    <role>Mark Scout</role>\n    <tmdbid>4495</tmdbid>\n    <thumb>https://image.tmdb.org/t/p/original/9ynbGSZ7O7stcCYx1ElmFhUgCKj.jpg</thumb>\n    <profile>https://www.themoviedb.org/person/4495</profile>\n  </actor>\n  <actor>\n    <name>布丽特·洛薇尔</name>\n    <type>Actor</type>\n    <role>Helly R.</role>\n    <tmdbid>1319469</tmdbid>\n    <profile>https://www.themoviedb.org/person/1319469</profile>\n  </actor>\n  <genre>剧情</genre>\n  <genre>悬疑</genre>\n  <genre>Sci-Fi &amp; Fantasy</genre>\n  <rating>8.4</rating>\n  <studio>Red Hour Productions</studio>\n  <country>美国</country>\n  <title>人生切割术</title>\n  <originaltitle>Severance</originaltitle>\n  <premiered>2022-02-17</premiered>\n  <year>2022</year>\n  <season>-1</season>\n  <episode>-1</episode>\n</tvshow>\n",
+  "season1": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<season>\n  <plot><![CDATA[在卢蒙工业公司，员工们接受了一种名为“分割”的手术 & 工作记忆与生活记忆被彻底隔开。]]></plot>\n  <outline><![CDATA[在卢蒙工业公司，员工们接受了一种名为“分割”的手术 & 工作记忆与生活记忆被彻底隔开。]]></outline>\n  <title>第 1 季</title>\n  <premiered>2022-02-17</premiered>\n  <releasedate>2022-02-17</releasedate>\n  <year>2022</year>\n  <seasonnumber>1</seasonnumber>\n</season>\n",
+  "s01e01": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<episodedetails>\n  <uniqueid type=\"tmdb\" default=\"true\">1830836</uniqueid>\n  <tmdbid>1830836</tmdbid>\n  <title>有关地狱的好消息</title>\n  <plot><![CDATA[马克升职成为宏观数据精炼部的主管，并迎来一位新员工。]]></plot>\n  <outline><![CDATA[马克升职成为宏观数据精炼部的主管，并迎来一位新员工。]]></outline>\n  <aired>2022-02-17</aired>\n  <year>2022</year>\n  <season>1</season>\n  <episode>1</episode>\n  <rating>8.2</rating>\n</episodedetails>\n",
+  "s01e02": "<?xml version=\"1.0\" encoding=\"utf-8\"?>\n<episodedetails>\n  <uniqueid type=\"tmdb\" default=\"true\">3435543</uniqueid>\n  <tmdbid>3435543</tmdbid>\n  <title>半循环</title>\n  <plot><![CDATA[马克带海莉参观办公室。]]></plot>\n  <outline><![CDATA[马克带海莉参观办公室。]]></outline>\n  <aired>2022-02-18</aired>\n  <year>2022</year>\n  <season>1</season>\n  <episode>2</episode>\n  <rating>8.0</rating>\n</episodedetails>\n",
+  "seasonPosterName": "season01-poster.jpg",
+  "seasonSpecialsPosterName": "season-specials-poster.jpg"
+}
@@ -0,0 +1,215 @@
+{
+  "_note": "SCR-1 差分用 TMDB 原始响应(zh-CN,形态照 TMDB v3;数值只保证合理,不作权威数据)。MP 与我们都从这里出发生成 NFO。",
+  "/movie/157336": {
+    "id": 157336,
+    "title": "星际穿越",
+    "original_title": "Interstellar",
+    "original_language": "en",
+    "origin_country": ["US"],
+    "release_date": "2014-11-05",
+    "overview": "在不远的未来，随着地球自然环境的恶化，人类面临着无法生存的威胁。一群宇航员穿越虫洞，为人类寻找新家园。",
+    "tagline": "我们注定要离开地球",
+    "runtime": 169,
+    "vote_average": 8.464,
+    "vote_count": 37000,
+    "status": "Released",
+    "poster_path": "/nCbkOyOMTEwlEV0LtCOvCnwEONA.jpg",
+    "backdrop_path": "/xJHokMbljvjADYdit5fK5VQsXEG.jpg",
+    "genres": [{ "id": 12, "name": "冒险" }, { "id": 18, "name": "剧情" }, { "id": 878, "name": "科幻" }],
+    "production_countries": [{ "iso_3166_1": "GB", "name": "英国" }, { "iso_3166_1": "US", "name": "美国" }],
+    "production_companies": [{ "id": 923, "name": "Legendary Pictures" }],
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