WorkBuddy
df56c2c137
内容分四块： 1、产品规划产出 —— MCN 短视频整合营销工作台的①段五份（1a 需求／1b 竞品／1c 画像／1d 策略／1e 场景）、②段两份（2a 功能／2b 布局）、③段界面（DESIGN.md 契约与令牌表 ＋ mcn-workbench.html 原型 ＋ 实测/会诊/审查三份 ＋ 23 张闸门截图）。 2、开源竞品调研 —— 5 个内容工作台项目的取证原始件与 1b 系列分析文档。 3、参考资料 —— 竞品视频抽帧 1145 张 ＋ 2 个源视频 ＋ 功能点截图。 4、机制侧 —— 协作脚本与状态台账、工作区记忆日志、抽帧/OCR 脚本。 .gitignore 只排运行时日志、脚本备份副本与一次性探针输出，其余按原样入库。
110 lines
3.3 KiB
Python
110 lines
3.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""复述检测 v2：按「最大重复簇」聚合输出。
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输出形如：
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【簇 3 文件 · 5 处】关键词行
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- 文件A#12
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- 文件B#40
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...
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只读，不写被扫描文件。
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"""
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import os, re, sys, collections
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ROOT = sys.argv[1] if len(sys.argv) > 1 else "."
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MINLEN = int(sys.argv[2]) if len(sys.argv) > 2 else 14
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SKIP_DIRS = {"assets", "归档", "_留痕", ".git", "node_modules", "vendor"}
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SKIP_NAME = {"_superseded-competitor-analysis-英文商业版.md"}
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def norm(s: str) -> str:
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s = re.sub(r"`[^`]*`", "", s)
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s = re.sub(r"[*#>|\-\s`]+", "", s)
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s = re.sub(r"[，。！？；：、（）()《》「」『』\[\]【】…—～~·\"'’“”]", "", s)
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return s
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def sentences(text):
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out = []
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for ln in text.splitlines():
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ln = ln.strip()
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if not ln:
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continue
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for piece in re.split(r"(?<=[。！？；])", ln):
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p = piece.strip()
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if p:
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out.append(p)
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return out
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files = []
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for dp, dns, fns in os.walk(ROOT):
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dns[:] = [d for d in dns if d not in SKIP_DIRS]
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for fn in fns:
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if fn.endswith(".md") and fn not in SKIP_NAME:
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files.append(os.path.join(dp, fn))
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files.sort()
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sent = [] # (loc, raw, norm)
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for path in files:
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with open(path, encoding="utf-8") as f:
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for i, raw in enumerate(sentences(f.read())):
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n = norm(raw)
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if len(n) >= MINLEN:
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sent.append(((path, i), raw, n))
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sh_map = collections.defaultdict(set)
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for loc, raw, n in sent:
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for j in range(len(n) - MINLEN + 1):
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sh_map[n[j:j + MINLEN]].add(loc)
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# 句级：收集它命中的、跨≥2文件的 shingle 所覆盖的全部位置
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pairs = []
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for loc, raw, n in sent:
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hit = set()
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for j in range(max(1, len(n) - MINLEN + 1)):
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locs = sh_map.get(n[j:j + MINLEN])
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if locs and len({p for p, _ in locs}) >= 2:
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hit |= locs
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if len({p for p, _ in hit}) >= 2:
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pairs.append((loc, raw, hit))
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# 聚簇：位置集合有交集的句子并入同一簇
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clusters = []
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for loc, raw, hit in pairs:
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placed = False
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for c in clusters:
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if c["locs"] & hit:
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c["locs"] |= hit
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c["members"].append((loc, raw))
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placed = True
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break
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if not placed:
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clusters.append({"locs": set(hit), "members": [(loc, raw)]})
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# 合并可传递的簇
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changed = True
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while changed:
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changed = False
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for i in range(len(clusters)):
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for j in range(i + 1, len(clusters)):
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if clusters[i]["locs"] & clusters[j]["locs"]:
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clusters[i]["locs"] |= clusters[j]["locs"]
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clusters[i]["members"] += clusters[j]["members"]
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del clusters[j]
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changed = True
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break
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if changed:
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break
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clusters = [c for c in clusters if len({p for p, _ in c["locs"]}) >= 2]
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clusters.sort(key=lambda c: (-len({p for p, _ in c["locs"]}), -len(c["locs"])))
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print(f"# 跨文件复述簇：{len(clusters)} 个（MINLEN={MINLEN}）\n")
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for k, c in enumerate(clusters, 1):
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fs = sorted({p for p, _ in c["locs"]})
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print(f"【簇{k}】{len(fs)} 文件 · {len(c['locs'])} 处")
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for loc, raw in sorted(c["members"]):
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print(f" {loc[0]}#{loc[1]} {raw[:110]}")
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print()
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