180 lines
8.7 KiB
Python
180 lines
8.7 KiB
Python
#!/usr/bin/env python3
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"""impact_analysis.py — 依赖图构建 + change-set 影响范围分析（Phase 2B，纯确定性）。
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build 模式：从 Capability Bundle（+ 可选 chunks.jsonl）构建带类型的依赖图
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（dependency-graph.schema.json）：source→chunk→capability→entrypoint→eval。
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analyze 模式：给定 change-set，沿图向下找：
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1. 直接依赖变更块的能力（chunk_id 精确匹配，或 source_evidence.location 与块 heading_path 的文本匹配）；
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2. 这些能力编译成的入口（single 入口 / 晋级 Skill / 来源路由入口）；
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3. also_read 邻居能力（对比/组合关系需一并回归）；
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4. 覆盖这些能力的评测用例。
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匹配不到任何能力的 additive 变更 → 标注为"新知识候选"，交给 Agent 做增量提取。
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用法:
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python3 scripts/impact_analysis.py build --bundle <dir> [--chunks <chunks.jsonl>] --out <graph.json>
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python3 scripts/impact_analysis.py analyze --graph <graph.json> --change-set <cs.json> --out <report.md>
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"""
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from __future__ import annotations
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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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sys.path.insert(0, str(Path(__file__).parent))
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from cangjie_common import TOOL_VERSION, dump_json, load_json, load_yaml # noqa: E402
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def build_graph(bundle_dir: Path, chunks_path: Path | None) -> dict:
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bundle = load_yaml(bundle_dir / "verified.yaml")
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router_name = bundle["router_entry"]["name"]
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nodes: list[dict] = []
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edges: list[dict] = []
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def add_node(node_id: str, node_type: str, label: str = "") -> None:
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nodes.append({"node_id": node_id, "node_type": node_type, "label": label})
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chunks = []
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if chunks_path and chunks_path.exists():
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chunks = [json.loads(l) for l in chunks_path.read_text(encoding="utf-8").splitlines() if l.strip()]
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if chunks:
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sv = f"{chunks[0]['source_id']}@{chunks[0]['version_id']}"
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add_node(sv, "source_version")
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for c in chunks:
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add_node(c["chunk_id"], "chunk", " / ".join(c["heading_path"]))
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edges.append({"from": sv, "to": c["chunk_id"], "edge_type": "contains"})
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add_node(router_name, "entrypoint", "来源路由入口")
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for cap in bundle["capabilities"]:
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cid = cap["capability_id"]
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add_node(cid, "capability", cap["title"])
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# 证据边：chunk_id 精确匹配 + location 与 heading_path 的文本匹配
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for ev in cap.get("source_evidence", []):
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for chunk_id in ev.get("chunk_ids", []):
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edges.append({"from": chunk_id, "to": cid, "edge_type": "supports", "evidence": "chunk_ids"})
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loc = str(ev.get("location", "")).strip()
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if loc and chunks:
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# 章节粒度匹配：location 的任一段与块 heading 的任一段互为子串即建边。
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# 宁可过近似（多回归）不可漏（少回归）。
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loc_segs = [s.strip() for s in loc.split("/") if len(s.strip()) >= 3]
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for c in chunks:
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hp_segs = [s for s in c["heading_path"] if len(s) >= 3]
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if any(ls in hs or hs in ls for ls in loc_segs for hs in hp_segs):
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edges.append({"from": c["chunk_id"], "to": cid, "edge_type": "supports",
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"evidence": f"location~heading(章节粒度): {loc}"})
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# 编译去向
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if cap.get("promotion", {}).get("destination") == "promoted":
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add_node(cap["slug"], "entrypoint", f"晋级 Skill: {cap['title']}")
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edges.append({"from": cid, "to": cap["slug"], "edge_type": "compiled_as"})
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edges.append({"from": cid, "to": router_name, "edge_type": "served_by"})
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# 邻居
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slug_to_id = {c["slug"]: c["capability_id"] for c in bundle["capabilities"]}
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for sib in cap.get("also_read", []):
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if sib in slug_to_id:
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edges.append({"from": cid, "to": slug_to_id[sib], "edge_type": "composes_with"})
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return {
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"schema_version": 1,
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"content_pack": bundle["book"].get("source_pack", bundle["bundle_id"]),
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"generated_by": TOOL_VERSION,
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"nodes": nodes,
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"edges": edges,
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}
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def analyze(graph: dict, change_set: dict) -> str:
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edges = graph["edges"]
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labels = {n["node_id"]: n.get("label", "") for n in graph["nodes"]}
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node_types = {n["node_id"]: n["node_type"] for n in graph["nodes"]}
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chunk_headings = {n["node_id"]: n.get("label", "") for n in graph["nodes"] if n["node_type"] == "chunk"}
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affected_caps: dict[str, list[str]] = {}
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orphan_changes: list[dict] = []
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for ch in change_set["changes"]:
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hit = False
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# 1) chunk_id 精确匹配
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for e in edges:
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if e["edge_type"] in ("supports", "contradicts", "examples") and e["from"] == ch["chunk_id"]:
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affected_caps.setdefault(e["to"], []).append(f"{ch['change_type']}:{ch['chunk_id']}")
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hit = True
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# 2) heading_path 文本匹配（新版本块的 chunk_id 不在旧图中时）
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if not hit and ch.get("heading_path"):
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hp_new = " / ".join(ch["heading_path"])
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for cid_chunk, hp in chunk_headings.items():
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if hp and (hp in hp_new or hp_new in hp):
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for e in edges:
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if e["edge_type"] == "supports" and e["from"] == cid_chunk:
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affected_caps.setdefault(e["to"], []).append(f"{ch['change_type']}:{hp_new}")
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hit = True
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if not hit and ch["change_type"] == "additive":
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orphan_changes.append(ch)
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# 沿图向下：能力 → 入口 / 邻居 / 评测
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affected_entrypoints: set[str] = set()
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neighbor_caps: set[str] = set()
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affected_evals: set[str] = set()
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for cap in affected_caps:
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for e in edges:
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if e["from"] == cap and e["edge_type"] in ("compiled_as", "served_by"):
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affected_entrypoints.add(e["to"])
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if e["edge_type"] in ("composes_with", "compared_with", "depends_on") and cap in (e["from"], e["to"]):
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other = e["to"] if e["from"] == cap else e["from"]
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if node_types.get(other) == "capability" and other not in affected_caps:
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neighbor_caps.add(other)
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if e["edge_type"] == "covers" and e["to"] == cap:
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affected_evals.add(e["from"])
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lines = ["# 影响范围分析", "",
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f"- change-set: `{change_set['change_id']}`（+{change_set['summary']['added']} / "
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f"-{change_set['summary']['removed']} / ~{change_set['summary']['modified']}）", ""]
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lines.append(f"## 受影响能力（{len(affected_caps)}）\n")
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for cap, reasons in sorted(affected_caps.items()):
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lines.append(f"- `{cap}` {labels.get(cap, '')} ← {'; '.join(sorted(set(reasons))[:3])}")
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lines.append(f"\n## 需重编译/回归的入口（{len(affected_entrypoints)}）\n")
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for ep in sorted(affected_entrypoints):
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lines.append(f"- `{ep}` {labels.get(ep, '')}")
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lines.append(f"\n## 需一并回归的邻居能力（{len(neighbor_caps)}）\n")
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for cap in sorted(neighbor_caps):
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lines.append(f"- `{cap}` {labels.get(cap, '')}")
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if affected_evals:
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lines.append(f"\n## 覆盖这些能力的评测（{len(affected_evals)}）\n")
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lines += [f"- `{e}`" for e in sorted(affected_evals)]
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lines.append(f"\n## 未命中任何既有能力的新增块（{len(orphan_changes)}）——新知识候选\n")
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for ch in orphan_changes:
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lines.append(f"- {ch['chunk_id']} [{' / '.join(ch.get('heading_path', []))}]")
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lines.append("\n> 未受影响的能力/入口不重编译，文件哈希保持不变（增量验收要求 §6.5）。")
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return "\n".join(lines) + "\n"
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def main() -> int:
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ap = argparse.ArgumentParser(description=__doc__)
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sub = ap.add_subparsers(dest="mode", required=True)
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b = sub.add_parser("build")
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b.add_argument("--bundle", required=True)
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b.add_argument("--chunks", default=None)
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b.add_argument("--out", required=True)
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a = sub.add_parser("analyze")
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a.add_argument("--graph", required=True)
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a.add_argument("--change-set", required=True)
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a.add_argument("--out", required=True)
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args = ap.parse_args()
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if args.mode == "build":
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graph = build_graph(Path(args.bundle), Path(args.chunks) if args.chunks else None)
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dump_json(Path(args.out), graph)
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print(f"依赖图: {args.out}（{len(graph['nodes'])} nodes / {len(graph['edges'])} edges）")
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else:
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report = analyze(load_json(Path(args.graph)), load_json(Path(args.change_set)))
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Path(args.out).parent.mkdir(parents=True, exist_ok=True)
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Path(args.out).write_text(report, encoding="utf-8")
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print(report)
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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