374 lines
18 KiB
Python
374 lines
18 KiB
Python
"""P0 数据一致性测试：
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- 审核入库岗位跨图谱重建持久化（真实区间/来源/场景行业边/演化事件）；
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- 节点编辑跨重建保留且与 /api/jobs 的 JobDefinition 一致；
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- JD 手动导入（文件上传 / 文本粘贴 / 坏行清单 三路径）；
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- 访问令牌空串清除端到端；
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- 语义权重相对路径（相对工程根解析）检测。
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"""
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from __future__ import annotations
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import json
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import time
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from datetime import date
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import pytest
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from fastapi.testclient import TestClient
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from app.api.routes import app
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from app.config import load_config
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from app.graph.tkg import TemporalKG
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from app.models import JDRecord
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@pytest.fixture(scope="module")
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def client(graph_path):
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with TestClient(app) as c: # 触发 startup 加载图谱
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yield c
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@pytest.fixture(autouse=True)
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def _restore_kg():
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"""本模块的 API 调用会改内存图谱；每个用例结束后从真实快照重载，避免串扰。"""
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yield
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import app.api.routes as routes
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from app.config import resolve
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gp = resolve(routes._cfg, "graph_path")
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if gp.exists():
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routes._state["kg"] = TemporalKG.load(gp)
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def _jd(jid: str, title: str, pub: str, req: list[str], pref: list[str] | None = None) -> dict:
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text = (f"岗位名称：{title}\n岗位职责：\n1、负责相关研发工作\n"
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f"任职要求：\n1、熟悉 {'、'.join(req)}\n"
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f"加分项：\n1、了解 {'、'.join(pref or ['团队协作'])}\n")
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return {"jid": jid, "job_title": title, "company": f"测试公司{jid}", "city": "深圳",
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"industry": "互联网/软件", "publish_date": pub, "text": text}
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JAVA_RECORDS = [
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_jd("j1", "Java开发工程师", "2022-01-15", ["Java", "MySQL"]),
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_jd("j2", "Java开发工程师", "2022-04-15", ["Java", "Redis"]),
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_jd("j3", "Java开发工程师", "2023-07-15", ["Java", "MySQL"]),
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]
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def _tmp_cfg(tmp_path, records) -> dict:
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"""最小数据集 + 全部状态路径指向 tmp 的 pipeline 配置。"""
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jd_dir = tmp_path / "jd_raw"
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jd_dir.mkdir(exist_ok=True)
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(jd_dir / "batch_2022.jsonl").write_text(
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"\n".join(json.dumps(r, ensure_ascii=False) for r in records) + "\n", encoding="utf-8")
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cfg = load_config()
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cfg["jd_raw_dir"] = str(jd_dir)
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cfg["graph_path"] = str(tmp_path / "graph.json")
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cfg["state_db_path"] = str(tmp_path / "state.db")
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cfg["audit_path"] = str(tmp_path / "audit.jsonl")
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cfg["pending_path"] = str(tmp_path / "pending.json")
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return cfg
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def _wait_task(client, task_id: str) -> dict:
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for _ in range(150):
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t = client.get(f"/api/tasks/{task_id}").json()["data"]
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if t["status"] in ("done", "failed"):
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return t
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time.sleep(0.2)
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raise AssertionError("任务超时未完成")
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# ---------- 1. 审核入库真实化 + 跨重建持久化 ----------
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def test_accept_real_data_and_persists_across_rebuild(client, tmp_path, monkeypatch):
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"""accept 用候选簇真实统计入库；pipeline 重建后岗位仍在（含场景/行业边与演化事件）。"""
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import app.api.routes as routes
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from app.discover.cluster import save_pending
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from app.models import JobDefinition
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from app.services.pipeline import run_pipeline
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from app.storage import db as state_db
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cfg = _tmp_cfg(tmp_path, JAVA_RECORDS)
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db_path = tmp_path / "state.db"
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monkeypatch.setitem(routes._cfg, "state_db_path", str(db_path))
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monkeypatch.setitem(routes._cfg, "audit_path", str(tmp_path / "audit.jsonl"))
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monkeypatch.setitem(routes._cfg, "graph_path", str(tmp_path / "graph_api.json"))
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cand = JobDefinition(
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job_id="cand_大模型工程师", title="大模型工程师", category="新岗位候选",
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industries=["人工智能"], required_skills=["Python", "PyTorch"],
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preferred_skills=["Docker"], scenarios=["智能客服"], status="pending",
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expected_years=3, source_count=12, company_count=5,
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support_source_ids=["import_20260801.jsonl#1", "import_20260801.jsonl#2"],
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support_windows=["2025Q4", "2025Q3"])
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save_pending([cand], db_path)
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r = client.post("/api/review", json={
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"candidate_id": "cand_大模型工程师", "action": "accept", "operator": "张老师"})
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assert r.status_code == 200
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# 当前图谱：真实区间（首个支持窗口 2025Q3 起）与真实来源、场景/行业边、新增事件
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g = client.get("/api/graph").json()["data"]
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req_edges = [e for e in g["edges"]
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if e["source"] == "job_大模型工程师" and e.get("rel") == "REQUIRES"]
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assert len(req_edges) == 3
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assert all(e["intervals"][0] == ["2025Q3", None] for e in req_edges)
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assert all(set(e["sources"]) == {"import_20260801.jsonl#1", "import_20260801.jsonl#2"}
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for e in req_edges)
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others = [e for e in g["edges"] if e["source"] == "job_大模型工程师"]
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assert any(e["rel"] == "APPLIES_TO" and e["target"] == "场景::智能客服" for e in others)
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assert any(e["rel"] == "BELONGS_TO" and e["target"] == "行业::人工智能" for e in others)
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evs = [e for e in g["events"] if e["job_id"] == "job_大模型工程师"]
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assert len(evs) == 3
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assert all(e["change_type"] == "新增" and e["window"] == "2025Q3" for e in evs)
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# 覆写层已记录（跨重建持久化的依据）
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assert state_db.get_override(db_path, "job_大模型工程师")["kind"] == "job_accept"
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# 全量重建：数据集中根本没有该岗位（2023 后新岗位），仅靠覆写层重放强制纳入
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stats = run_pipeline(cfg)
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assert stats["stages"]["overrides"]["jobs"] == 1
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# 已入库岗位不会重新出现在待审核分区
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assert state_db.get_candidate(db_path, "cand_大模型工程师") is None
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kg = TemporalKG.load(tmp_path / "graph.json")
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assert "job_大模型工程师" in kg.jobs
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job = kg.jobs["job_大模型工程师"]
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assert job.status == "active" and job.title == "大模型工程师"
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edge = kg.g["job_大模型工程师"]["Python"]
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assert edge["intervals"][0] == ["2025Q3", None]
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assert set(edge["sources"]) == {"import_20260801.jsonl#1", "import_20260801.jsonl#2"}
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assert kg.g.has_edge("job_大模型工程师", "场景::智能客服")
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assert kg.g.has_edge("job_大模型工程师", "行业::人工智能")
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assert any(ev.change_type == "新增" and ev.window == "2025Q3"
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for ev in kg.events_of("job_大模型工程师"))
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def test_reject_clears_override(client, tmp_path, monkeypatch):
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"""驳回：清理覆写层记录，重建后岗位不复活。"""
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import app.api.routes as routes
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from app.discover.cluster import save_pending
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from app.models import JobDefinition
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from app.storage import db as state_db
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db_path = tmp_path / "state.db"
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monkeypatch.setitem(routes._cfg, "state_db_path", str(db_path))
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monkeypatch.setitem(routes._cfg, "audit_path", str(tmp_path / "audit.jsonl"))
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monkeypatch.setitem(routes._cfg, "graph_path", str(tmp_path / "graph_api.json"))
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cand = JobDefinition(job_id="cand_短命岗位", title="短命岗位",
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required_skills=["Python"], status="pending",
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support_source_ids=["x.jsonl#1"], support_windows=["2025Q2"])
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save_pending([cand], db_path)
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state_db.save_override(db_path, "cand_短命岗位",
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{"kind": "job_accept", "job": cand.model_dump()})
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r = client.post("/api/review", json={
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"candidate_id": "cand_短命岗位", "action": "reject",
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"operator": "张老师", "reason": "证据不足"})
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assert r.status_code == 200
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assert state_db.get_override(db_path, "cand_短命岗位") is None
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assert state_db.get_candidate(db_path, "cand_短命岗位") is None
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def test_discover_candidate_carries_support_evidence():
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"""新岗位发现：候选带支撑 source_id / 季度窗口 / 行业，供审核入库真实化。"""
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from app.discover import cluster
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from app.models import ExtractionResult
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records, extractions = [], {}
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for i in range(15): # ≥ MIN_CLUSTER_SIZE(15)，5 家企业 ≥ MIN_COMPANIES(5)
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r = JDRecord(jid=f"c{i}", job_title="提示词工程师", company=f"公司{i % 5}",
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industry="人工智能", publish_date=date(2025, i % 6 + 1, 1),
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text="负责大模型提示词设计与优化", source_id=f"t.jsonl#{i + 1}")
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records.append(r)
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extractions[r.jid] = ExtractionResult(
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jid=r.jid, job_title="提示词工程师",
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required_skills=["Python", "提示工程"], scenarios=["智能客服"])
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cands = cluster.discover_new_jobs(records, extractions, known_titles=set())
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assert len(cands) == 1
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c = cands[0]
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assert len(c.support_source_ids) == 15
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assert min(c.support_windows) == "2025Q1"
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assert c.industries == ["人工智能"]
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# ---------- 2. 节点编辑同步 JobDefinition + 跨重建保留 ----------
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def test_node_update_syncs_jobdef_and_persists(client, tmp_path, monkeypatch):
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"""节点编辑同步 kg.jobs；重建后编辑保留且 /api/jobs 定义一致。"""
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import app.api.routes as routes
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from app.services.pipeline import run_pipeline
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cfg = _tmp_cfg(tmp_path, JAVA_RECORDS)
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db_path = tmp_path / "state.db"
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monkeypatch.setitem(routes._cfg, "state_db_path", str(db_path))
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monkeypatch.setitem(routes._cfg, "audit_path", str(tmp_path / "audit.jsonl"))
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monkeypatch.setitem(routes._cfg, "graph_path", str(tmp_path / "graph_api.json"))
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r = client.post("/api/graph/node/update", json={
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"node_id": "job_Java开发工程师",
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"updates": {"title": "Java后端架构师", "level": "高级"},
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"operator": "张老师", "reason": "校准"})
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assert r.status_code == 200
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node = r.json()["data"]["node"]
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assert node["title"] == "Java后端架构师" and node["level"] == "高级"
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assert node["expected_years"] == 6 # 级别同步回年限（高级→6）
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# /api/jobs 的 JobDefinition 同步一致
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d = client.get("/api/jobs/job_Java开发工程师").json()["data"]["definition"]
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assert d["title"] == "Java后端架构师" and d["expected_years"] == 6
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# 重建：节点编辑经覆写层重放保留，JobDefinition 同样一致
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run_pipeline(cfg)
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kg = TemporalKG.load(tmp_path / "graph.json")
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assert "job_Java开发工程师" in kg.jobs # 2022 年出现 → 既有岗位正常重建
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attrs = kg.g.nodes["job_Java开发工程师"]
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assert attrs["title"] == "Java后端架构师" and attrs["level"] == "高级"
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assert attrs["expected_years"] == 6
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jd = kg.jobs["job_Java开发工程师"]
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assert jd.title == "Java后端架构师" and jd.expected_years == 6
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# ---------- 3. JD 手动导入（文件 / 文本 / 坏行） ----------
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def _import_setup(tmp_path, monkeypatch):
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import app.api.routes as routes
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cfg = _tmp_cfg(tmp_path, JAVA_RECORDS)
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monkeypatch.setitem(routes._cfg, "jd_raw_dir", cfg["jd_raw_dir"])
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monkeypatch.setitem(routes._cfg, "graph_path", cfg["graph_path"])
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monkeypatch.setitem(routes._cfg, "state_db_path", cfg["state_db_path"])
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monkeypatch.setitem(routes._cfg, "audit_path", cfg["audit_path"])
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monkeypatch.setitem(routes._cfg, "pending_path", cfg["pending_path"])
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return cfg
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def test_jd_import_text_paste(client, tmp_path, monkeypatch):
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"""JSON 文本粘贴：合格记录落 import_*.jsonl（保留来源标记），坏行返回并写 logs，触发重建。"""
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_import_setup(tmp_path, monkeypatch)
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lines = [
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json.dumps(_jd("n1", "Java开发工程师", "2025-03-01", ["Java"]), ensure_ascii=False),
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"", # 空行 → 跳过
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json.dumps(_jd("n2", "Python开发工程师", "2025-05-01", ["Python"]), ensure_ascii=False),
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"{不是合法 json", # 坏行
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]
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r = client.post("/api/jd/import", json={"text": "\n".join(lines)})
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assert r.status_code == 200
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data = r.json()["data"]
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assert data["imported"] == 2 and data["skipped"] == 1
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assert len(data["bad_lines"]) == 1 and data["bad_lines"][0]["line"] == 4
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jd_dir = tmp_path / "jd_raw"
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imported = jd_dir / data["file"]
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assert imported.exists() and data["file"].startswith("import_")
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saved = [json.loads(x) for x in imported.read_text(encoding="utf-8").splitlines()]
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assert {s["jid"] for s in saved} == {"n1", "n2"}
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# 坏行写 logs
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from app.config import ROOT
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assert (ROOT / "logs" / data["bad_log"]).exists()
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# 异步重建完成，导入统计随任务可查
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t = _wait_task(client, data["task_id"])
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assert t["status"] == "done" and t["import"]["imported"] == 2
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def test_jd_import_file_upload(client, tmp_path, monkeypatch):
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"""multipart 文件上传（.jsonl）：与文本粘贴同一入库链路。"""
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_import_setup(tmp_path, monkeypatch)
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content = "\n".join([
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json.dumps(_jd("f1", "Java开发工程师", "2025-01-10", ["Java"]), ensure_ascii=False),
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json.dumps({"jid": "f2"}), # 缺必需字段 → 坏行
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]).encode("utf-8")
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r = client.post("/api/jd/import",
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files={"file": ("extra.jsonl", content, "application/octet-stream")})
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assert r.status_code == 200
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data = r.json()["data"]
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assert data["imported"] == 1 and len(data["bad_lines"]) == 1
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assert data["bad_lines"][0]["line"] == 2
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t = _wait_task(client, data["task_id"])
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assert t["status"] == "done"
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def test_jd_import_csv_and_bad_ext(client, tmp_path, monkeypatch):
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"""CSV 表头映射导入；不支持的扩展名 400。"""
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_import_setup(tmp_path, monkeypatch)
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csv_text = ("jid,job_title,company,publish_date,text\n"
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"c1,Java开发工程师,示例科技,2025-02-01,熟悉Java后端开发\n"
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"c2,缺日期岗位,示例科技,,熟悉Python\n") # publish_date 缺失 → 坏行
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r = client.post("/api/jd/import",
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files={"file": ("jd.csv", csv_text.encode("utf-8"), "text/csv")})
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assert r.status_code == 200
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data = r.json()["data"]
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assert data["imported"] == 1 and len(data["bad_lines"]) == 1
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_wait_task(client, data["task_id"])
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bad = client.post("/api/jd/import",
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files={"file": ("jd.exe", b"MZ", "application/octet-stream")})
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assert bad.status_code == 400
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def test_jd_import_rebuild_only(client, tmp_path, monkeypatch):
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"""不带内容调用保持旧行为：仅触发全量重建。"""
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_import_setup(tmp_path, monkeypatch)
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r = client.post("/api/jd/import", json={})
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assert r.status_code == 200
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data = r.json()["data"]
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assert "imported" not in data and data["task_id"]
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t = _wait_task(client, data["task_id"])
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assert t["status"] == "done"
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# ---------- 4. 访问令牌空串清除端到端 ----------
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def test_token_clear_end_to_end(client, tmp_path, monkeypatch):
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"""设置令牌 → 鉴权生效 → 空串清除 → 鉴权解除（config.json 同步）。"""
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import app.config as cfgmod
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import app.api.routes as routes
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monkeypatch.setattr(cfgmod, "CONFIG_JSON", tmp_path / "config.json")
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monkeypatch.setattr(routes, "load_runtime_settings", cfgmod.load_runtime_settings)
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r = client.post("/api/config", json={"access_token": "tok-xyz"})
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assert r.status_code == 200 and r.json()["data"]["has_access_token"] is True
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assert client.get("/api/jobs").status_code == 401
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assert client.get("/api/jobs", headers={"X-Access-Token": "tok-xyz"}).status_code == 200
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# 空串清除（前端令牌框 dirty 后留空提交的场景）
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r2 = client.post("/api/config", json={"access_token": ""},
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headers={"X-Access-Token": "tok-xyz"})
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assert r2.status_code == 200
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assert r2.json()["data"]["has_access_token"] is False
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assert "access_token" not in routes._cfg
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assert "access_token" not in cfgmod.load_runtime_settings()
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assert client.get("/api/jobs").status_code == 200 # 无需令牌即可访问
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# ---------- 5. 语义权重相对路径 ----------
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def test_relative_weights_path(tmp_path, monkeypatch):
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"""embed_model_path 支持相对路径（相对工程根解析），绝对路径配置自动兼容。"""
|
||
import app.config as cfgmod
|
||
from app.match import semantic
|
||
monkeypatch.setattr(cfgmod, "ROOT", tmp_path)
|
||
w = tmp_path / "models" / "bge-m3"
|
||
w.mkdir(parents=True)
|
||
for f in ["config.json", "model.safetensors", "tokenizer.json"]:
|
||
(w / f).write_text("{}")
|
||
st = semantic.status({"embed_model_path": "models/bge-m3"})
|
||
assert st["configured"] is True and st["weights_present"] is True
|
||
# 既有绝对路径配置不受影响
|
||
st2 = semantic.status({"embed_model_path": str(w)})
|
||
assert st2["weights_present"] is True
|
||
assert semantic.resolve_weights_path("models/bge-m3") == w
|
||
assert semantic.resolve_weights_path(str(w)) == w
|
||
|
||
|
||
def test_accept_normalizes_candidate_id_single_node(client, tmp_path, monkeypatch):
|
||
"""候选转正归一化：accept 后全图只有 job_<岗位名> 一个节点，边/事件挂在其下。"""
|
||
import app.api.routes as routes
|
||
from app.services.overrides import normalize_job_id
|
||
from app.models import JobDefinition
|
||
kg = routes._get_kg()
|
||
job = JobDefinition(job_id="cand_测试岗位X", title="测试岗位X", category="测试",
|
||
required_skills=["Python"], preferred_skills=["Docker"],
|
||
scenarios=["教育"], industries=[], expected_years=3,
|
||
status="active", support_source_ids=["batch_2024.jsonl#1"],
|
||
support_windows=["2024Q1"])
|
||
assert normalize_job_id(job) == "job_测试岗位X"
|
||
job.job_id = normalize_job_id(job) # 调用方负责归一化（与 routes 一致）
|
||
from app.services.overrides import apply_accepted_job
|
||
apply_accepted_job(kg, job)
|
||
# 全图唯一节点：无 cand_ 残留，REQUIRES 边挂在归一化 id 下
|
||
assert "job_测试岗位X" in kg.g and "cand_测试岗位X" not in kg.g
|
||
assert kg.g.has_edge("job_测试岗位X", "Python")
|
||
assert not list(kg.g.edges("cand_测试岗位X"))
|
||
# 清理测试数据
|
||
kg.g.remove_node("job_测试岗位X")
|
||
kg.jobs.pop("job_测试岗位X", None)
|