fix: 批量匹配跳过画像待补录教师 + render-html 按行重建 + 金标准 fixtures 业务化（P0+P1）
- run_match 新增 skip_incomplete：批量缺省跳过画像不完整教师并记录 skipped，指定单教师仍 PROFILE_INCOMPLETE；汇总页出"画像待补录"行 - render-html 补 --report-id 行上下文（inputMapping $row.$pk），CLI 容错解析回退最近 10 份 - report_service 日志改容错 _log()，修复未 setup 时单跑测试崩溃的顺序依赖 - fixtures 替换为教师画像/赛道/期望结论金标准样例，新增 sample_tracks.json - 新增 4 个批量跳过用例（314 项，除 3 个已知 jsonschema 环境失败外全绿） - tests/README 增补本机无共享 runtime 的测试方式；TUTORIAL/ACTIONS.md 同步表述
This commit is contained in:
chenfuqiang
@@ -23,7 +23,7 @@
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1. 在"教师画像"表点顶栏「赛道匹配」；可只填某位教师，缺省匹配全部
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2. 提交后稍等，切到"推荐报告"表查看每人的 Top 3 与可匹配赛道数
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3. 点顶栏「生成建议书」重建 HTML；左侧报告区打开 `report-编号` 查看 Top 3 卡片、分层清单与剔除原因
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3. 点顶栏「生成建议书」重建 HTML（在"推荐报告"表选中某一行则只重建该报告，未选中则重建最近 10 份）；左侧报告区打开 `report-编号` 查看 Top 3 卡片、分层清单与剔除原因
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## 入口二：对话任务
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@@ -67,3 +67,4 @@
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- **所有赛道都是"不建议"**：研究标签与赛道需求标签重合度低；请教师补充/细化标签后重新匹配
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- **看不到建议书**：先在"推荐报告"表点一次「生成建议书」，再到左侧 HTML 报告区打开
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- **批量匹配没有结果**：确认 input 目录里的 JSON 是教师对象数组，且赛道库不为空
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- **批量匹配少了某位老师**：该教师画像不完整（研究标签与论文都没有）会被跳过并记录原因，补录标签后重新匹配即可
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@@ -329,17 +329,31 @@
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{
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"id": "render-html",
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"label": "生成建议书",
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"description": "重建《申报策略建议书》HTML（缺省最近 10 份）。",
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"description": "重建《申报策略建议书》HTML（未选择报告行时重建最近 10 份）。",
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"placements": ["toolbar", "skill-detail", "agent"],
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"executionProfile": "sync",
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"interaction": "direct",
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"bind": {
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"tables": ["match_reports"]
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"tables": ["match_reports"],
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"inputMapping": {
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"id": "$row.$pk"
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}
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},
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"inputSchema": {
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"type": "object",
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"properties": {
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"id": {
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"type": "number",
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"title": "报告编号",
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"description": "重建该报告的建议书。未选择行时留空，重建最近 10 份。",
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"readOnly": true
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}
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}
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},
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"entrypoint": {
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"type": "cli",
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"command": "render-html",
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"args": []
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"args": ["--report-id", "{{id}}"]
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},
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"steps": [
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{
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@@ -777,6 +777,12 @@ HINT: <next step>
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完整 JSON 形状见 [`../assets/examples/render-html.action.example.json`](../assets/examples/render-html.action.example.json)。最小页面壳见 [`../assets/html/example-report.html`](../assets/html/example-report.html)（已含数据管理 iframe 预览的布局基线；复制后可按需扩展 `{{BODY}}` 内结构）。
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**本技能的行上下文写法**：`render-html` 的 `entrypoint.args` 为 `["--report-id", "{{id}}"]`，行 id 经 `bind.inputMapping: { "id": "$row.$pk" }` 注入、并在 `inputSchema.properties.id` 声明（模板参数必须声明，见上文规则）。行为约定：
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- 数据管理在"推荐报告"表**选中某行**点「生成建议书」→ 只重建该报告（`report-{id}.html`）。
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- 从 **HTML 右键重新生成 / skill-detail / 对话** 触发时**无行上下文**：宿主省略空的可选数字字段或占位未解析；CLI（`scripts/cli/app.py` `_handle_render_html`）对 `--report-id` 为 `""` / 非数字 / 缺值一律回退为"重建最近 10 份"，不会报错。
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- 因此 `--report-id` 在 argparse 上是可选值（`nargs="?"`），这是对宿主省略行为的容错，勿删。
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### 宿主预览布局
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数据管理在 **iframe** 内预览 `html/*.html`；宿主 iframe 已占满右侧预览区，**技能页不应再人为收窄正文**（尤其数据管理窗口通常较窄）。
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@@ -109,8 +109,10 @@ def _handle_list_reports(args: argparse.Namespace) -> int:
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def _handle_render_html(args: argparse.Namespace) -> int:
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report_id = getattr(args, "report_id", None)
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return cmd_render_html(report_id=int(report_id) if report_id else None)
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# 宿主行上下文可能给空串或未解析占位符（如 {{id}}）：解析失败一律回退
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# 缺省行为（重建最近 10 份），不让 args 变体把渲染打崩。
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report_id = _cli_int_or_none(getattr(args, "report_id", None))
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return cmd_render_html(report_id=report_id)
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def _print_full_usage() -> None:
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@@ -195,7 +197,7 @@ def build_parser() -> ZhArgumentParser:
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sp.set_defaults(handler=lambda a: cmd_show_report(report_id=int(a.report_id)))
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sp = sub.add_parser("render-html", help="重建《申报策略建议书》（缺省最近 10 份）")
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sp.add_argument("--report-id", default=None, metavar="报告编号", dest="report_id")
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sp.add_argument("--report-id", default=None, nargs="?", metavar="报告编号", dest="report_id")
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sp.set_defaults(handler=_handle_render_html)
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sp = sub.add_parser("stats", help="匹配统计")
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@@ -247,8 +247,20 @@ def _write_report(result: dict[str, Any], batch_no: str) -> str:
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return write_report_for_kernel(result=result, batch_no=batch_no)
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def run_match(teachers_raw: list[dict[str, Any]], tracks: list[dict[str, Any]], season: str, *, batch_no: str = "") -> dict[str, Any]:
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"""匹配内核：逐教师匹配 → 写库 → 生成建议书（多人时另出汇总页）。"""
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def run_match(
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teachers_raw: list[dict[str, Any]],
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tracks: list[dict[str, Any]],
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season: str,
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*,
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batch_no: str = "",
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skip_incomplete: bool = True,
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) -> dict[str, Any]:
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"""匹配内核：逐教师匹配 → 写库 → 生成建议书（多人时另出汇总页）。
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skip_incomplete=True（批量缺省）：画像不完整（E1）的教师被跳过并记入
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``skipped``，不中断批次；skip_incomplete=False（指定单教师）：直接抛
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ValueError，由 CLI 映射 PROFILE_INCOMPLETE。
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"""
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from service.report_service import build_batch_brief
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log = _log()
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@@ -263,11 +275,21 @@ def run_match(teachers_raw: list[dict[str, Any]], tracks: list[dict[str, Any]],
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log.info("match_kernel_start batch_no=%s teachers=%s tracks=%s season=%s stage=kernel", batch_no, len(teachers_raw), len(tracks), season)
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results = []
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skipped: list[dict[str, str]] = []
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conn = get_conn()
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try:
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cur = conn.cursor()
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for teacher_raw in teachers_raw:
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try:
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result = match_teacher(teacher_raw, tracks, season)
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except ValueError as exc:
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if not skip_incomplete:
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raise
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raw_name = str((teacher_raw or {}).get("teacherName") or (teacher_raw or {}).get("teacher_name") or "").strip() or "未命名教师"
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skipped.append({"teacher_name": raw_name, "reason": str(exc)})
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if log:
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log.warning("match_teacher_skipped teacher=%s reason=%s stage=kernel", raw_name, exc)
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continue
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cur.execute(
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"""
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INSERT INTO match_reports
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@@ -296,7 +318,7 @@ def run_match(teachers_raw: list[dict[str, Any]], tracks: list[dict[str, Any]],
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finally:
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conn.close()
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brief_file = build_batch_brief(batch_no=batch_no, results=results, season=season)
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brief_file = build_batch_brief(batch_no=batch_no, results=results, season=season, skipped=skipped)
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tier_counts: dict[str, int] = {}
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for result in results:
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for tier, entries in result["tiers"].items():
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@@ -307,13 +329,19 @@ def run_match(teachers_raw: list[dict[str, Any]], tracks: list[dict[str, Any]],
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"batch_no": batch_no,
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"season": season,
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"count": len(results),
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"skipped": skipped,
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"tier_counts": tier_counts,
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"brief_file": brief_file,
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"disclaimer": "推荐仅供参考，申报决策请结合个人规划与学院统筹。",
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"reports": results,
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}
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if log:
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log.info("match_kernel_done batch_no=%s count=%s stage=kernel", batch_no, len(results))
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log.info(
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"match_kernel_done batch_no=%s count=%s skipped=%s stage=kernel",
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batch_no,
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len(results),
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len(skipped),
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)
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return payload
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@@ -18,6 +18,14 @@ _TEMPLATE_REL = "assets/html/match-report.html"
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_TIER_BADGE = {"强烈推荐": "tier-strong", "可尝试": "tier-try", "不建议": "tier-not"}
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def _log():
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"""容错取 logger：未 setup_skill_logging（如单测直调 service）时返回 None。"""
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try:
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return get_skill_logger()
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except RuntimeError:
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return None
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def _esc(value: Any) -> str:
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return html_escape(str(value if value is not None else "—"))
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@@ -106,8 +114,9 @@ def build_match_html(result: dict[str, Any], batch_no: str = "") -> str:
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def write_report_for_kernel(*, result: dict[str, Any], batch_no: str) -> str:
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html_text = build_match_html(result, batch_no)
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log = get_skill_logger()
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log = _log()
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path = write_html_page(f"report-{result['report_id']}.html", html_text)
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if log:
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log.info("match_report_written report_id=%s path=%s stage=report", result["report_id"], path)
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return path
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@@ -116,7 +125,8 @@ def build_report_for_report_id(report_id: int) -> str:
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"""按报告 id 从库中取数并重写 HTML（重建入口用）。"""
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from db.connection import get_conn
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log = get_skill_logger()
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log = _log()
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if log:
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log.info("report_render_start report_id=%s stage=render", report_id)
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conn = get_conn()
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try:
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@@ -139,13 +149,20 @@ def build_report_for_report_id(report_id: int) -> str:
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result["top3"] = result.get("top") or []
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html_text = build_match_html(result)
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path = write_html_page(f"report-{report_id}.html", html_text)
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if log:
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log.info("report_render_done report_id=%s path=%s stage=render", report_id, path)
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return path
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def build_batch_brief(*, batch_no: str, results: list[dict[str, Any]], season: str) -> str:
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"""批量匹配汇总页：各教师 Top 1 一览。"""
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log = get_skill_logger()
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def build_batch_brief(
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*,
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batch_no: str,
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results: list[dict[str, Any]],
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season: str,
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skipped: list[dict[str, Any]] | None = None,
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) -> str:
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"""批量匹配汇总页：各教师 Top 1 一览；被跳过（画像待补录）教师单列。"""
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log = _log()
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rows = []
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for result in results:
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top3 = result.get("top3") or []
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@@ -163,6 +180,13 @@ def build_batch_brief(*, batch_no: str, results: list[dict[str, Any]], season: s
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)
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else:
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rows.append(f"<tr><td>{_esc(result.get('teacher_name'))}</td><td colspan='4' class='muted'>无可推荐赛道（画像待补全）</td></tr>")
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for entry in skipped or []:
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rows.append(
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"<tr>"
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f"<td>{_esc(entry.get('teacher_name'))}</td>"
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f"<td colspan='4' class='muted'>画像待补录，本期未匹配（{_esc(entry.get('reason'))}）</td>"
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"</tr>"
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)
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if not rows:
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rows.append('<tr><td colspan="5" class="muted">本期无匹配结果。</td></tr>')
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@@ -181,5 +205,6 @@ def build_batch_brief(*, batch_no: str, results: list[dict[str, Any]], season: s
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{"TITLE": "申报赛道匹配汇总", "GENERATED_AT": str(season), "BODY": body},
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)
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path = write_html_page(f"brief-{batch_no}.html", page)
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if log:
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log.info("match_brief_written batch_no=%s path=%s stage=report", batch_no, path)
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return path
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@@ -485,7 +485,9 @@ def cmd_match(*, teacher: str = "", year: Optional[int] = None) -> int:
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return 1
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season = str(year or tracks[0].get("year") or "")
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result = run_match(teachers, tracks, season)
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# 指定教师 → 严格模式，画像不完整直接 PROFILE_INCOMPLETE；
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# 缺省全量 → 跳过画像待补录教师并记录，不中断批次（E1）。
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result = run_match(teachers, tracks, season, skip_incomplete=not teacher)
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payload = {k: v for k, v in result.items() if k != "reports"}
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payload["reports_brief"] = [
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{
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@@ -499,9 +501,14 @@ def cmd_match(*, teacher: str = "", year: Optional[int] = None) -> int:
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for r in result["reports"]
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]
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_print_json(payload)
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skipped_count = len(result.get("skipped") or [])
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message = f"匹配完成 {result['count']} 名教师，建议书已生成"
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if skipped_count:
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message += f"；{skipped_count} 名教师画像待补录已跳过"
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log.info("match_skipped count=%s stage=match", skipped_count)
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finish(
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status="success",
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message=f"匹配完成 {result['count']} 名教师，建议书已生成",
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message=message,
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skill=SKILL_SLUG,
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stage="match",
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batch_no=result["batch_no"],
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@@ -568,7 +575,7 @@ def cmd_match_batch_input() -> int:
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return 1
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season = str(tracks[0].get("year") or "")
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result = run_match(teachers, tracks, season)
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result = run_match(teachers, tracks, season, skip_incomplete=True)
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for index, report in enumerate(result["reports"], start=1):
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top = (report.get("top3") or [{}])[0]
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emit(
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@@ -577,16 +584,27 @@ def cmd_match_batch_input() -> int:
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skill=SKILL_SLUG,
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stage="batch",
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)
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for entry in result.get("skipped") or []:
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emit(
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f"{entry.get('teacher_name')}：画像待补录，本期已跳过（{entry.get('reason')}）",
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type="warn",
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skill=SKILL_SLUG,
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stage="batch",
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)
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_print_json(
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{
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"ok": True,
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"batch_no": result["batch_no"],
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"count": result["count"],
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"skipped": result.get("skipped") or [],
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"tier_counts": result["tier_counts"],
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"brief_file": result["brief_file"],
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}
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)
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finish(status="success", message=f"批量匹配完成 {result['count']} 名教师", skill=SKILL_SLUG, stage="batch", batch_no=result["batch_no"])
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message = f"批量匹配完成 {result['count']} 名教师"
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if result.get("skipped"):
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message += f"，{len(result['skipped'])} 名画像待补录已跳过"
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finish(status="success", message=message, skill=SKILL_SLUG, stage="batch", batch_no=result["batch_no"])
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return 0
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except JobStopped:
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raise
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@@ -103,6 +103,20 @@ python tests/run_tests.py test_cli_smoke
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- ``tests/.gitignore`` 忽略 ``__pycache__``、``.pytest_cache``、``*.pyc``、``desktop/artifacts/``、``integration/artifacts/``、``.env`` 等。
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- 推荐运行前设置 ``PYTHONDONTWRITEBYTECODE=1`` 减少 ``.pyc``。
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### 1.5 本机无共享 runtime 时怎么跑（本技能开发机约定）
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宿主共享 runtime（``{JIANGCHANG_DATA_ROOT}/python-runtime/.venv``）只在宿主环境存在；纯开发机上 ``import jiangchang_skill_core`` 会直接 ``ModuleNotFoundError``（整套测试 60+ errors）。**不安装任何包**的跑法：
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```powershell
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$env:PYTHONPATH = "D:\jiangchang\huashang\jiangchang-platform-kit\jiangchang-platform-kit\src"
|
||||
python tests\run_tests.py -v
|
||||
```
|
||||
|
||||
已知环境性失败（不修、不装包）：``test_actions_manifest.py`` 中 3 项依赖 ``jsonschema`` 的 schema 校验
|
||||
（``test_schema_allows_all_placement_execution_profile_combinations`` / ``test_schema_allows_bind_label_column`` /
|
||||
``test_schema_rejects_toolbar_without_bind``）会以 ``jsonschema is required`` 失败。**除这 3 项外须全部通过**；
|
||||
接入宿主共享 runtime 后自动恢复。``requirements.txt`` 保持为空——平台库由宿主 runtime 提供，技能不声明平台依赖。
|
||||
|
||||
---
|
||||
|
||||
## 2. 可选：Service / Golden（``tests/samples/*.sample``）
|
||||
|
||||
5
tests/fixtures/README.md
vendored
5
tests/fixtures/README.md
vendored
@@ -12,8 +12,9 @@
|
||||
|
||||
| 文件 | 用途 |
|
||||
|------|------|
|
||||
| `sample_request.json` | 通用请求体样例，供 ``tests/samples/test_golden_cases.py.sample`` 演示读取。 |
|
||||
| `expected_response.json` | 与上配套的期望摘要字段（业务复制后按域替换）。 |
|
||||
| `sample_request.json` | 教师画像金标准样例（脱敏，JSON 数组），可直接 `import-teachers --teachers-json` 消费；供 `tests/samples/test_golden_cases.py.sample` 演示读取。 |
|
||||
| `sample_tracks.json` | 指南赛道金标准样例（脱敏，JSON 数组），可直接 `import-tracks --tracks-json` 消费；与上配套覆盖 H1/H2/S1~S3/T1 场景。 |
|
||||
| `expected_response.json` | 与上两份配套的期望匹配结论（Top 赛道/分层/得分/剔除项，业务复制后按域替换）。 |
|
||||
| `adapter_profiles.sample.yaml` | 五类运行方式（mock / simulator_api / simulator_rpa / real_api / real_rpa）的配置表达样例。 |
|
||||
|
||||
---
|
||||
|
||||
22
tests/fixtures/expected_response.json
vendored
22
tests/fixtures/expected_response.json
vendored
@@ -1,6 +1,22 @@
|
||||
{
|
||||
"success": true,
|
||||
"data": {
|
||||
"status": "ok"
|
||||
"season": "2027",
|
||||
"teacher_count": 2,
|
||||
"track_count": 3,
|
||||
"expectations": [
|
||||
{
|
||||
"teacherName": "张教授",
|
||||
"topTrack": "面上项目·光伏材料",
|
||||
"tier": "强烈推荐",
|
||||
"matchPct": 100,
|
||||
"reasonsContains": ["命中需求标签", "优先资助方向命中"]
|
||||
},
|
||||
{
|
||||
"teacherName": "王讲师",
|
||||
"topTrack": "青年项目·农村经济",
|
||||
"tier": "可尝试",
|
||||
"matchPct": 70,
|
||||
"excludedContains": ["面上项目·光伏材料", "重点项目·量子计算"]
|
||||
}
|
||||
],
|
||||
"disclaimerContains": "仅供参考"
|
||||
}
|
||||
|
||||
29
tests/fixtures/sample_request.json
vendored
29
tests/fixtures/sample_request.json
vendored
@@ -1,11 +1,22 @@
|
||||
[
|
||||
{
|
||||
"request_id": "req_test_001",
|
||||
"tenant_id": "tenant_demo",
|
||||
"actor": "tester",
|
||||
"parameters": {
|
||||
"input_text": "demo input",
|
||||
"options": {
|
||||
"dry_run": true
|
||||
}
|
||||
}
|
||||
"teacherName": "张教授",
|
||||
"department": "化材学院",
|
||||
"title": "教授",
|
||||
"researchTags": "钙钛矿,光伏,半导体,界面调控,稳定性",
|
||||
"recentPapers": "钙钛矿电池界面钝化研究",
|
||||
"projectHistory": "主持省自然科学基金",
|
||||
"sciQ1Count": 3,
|
||||
"corePaperCount": 8
|
||||
},
|
||||
{
|
||||
"teacherName": "王讲师",
|
||||
"department": "经管学院",
|
||||
"title": "讲师",
|
||||
"researchTags": "乡村振兴,农村经济",
|
||||
"recentPapers": "县域乡村产业发展研究",
|
||||
"projectHistory": "参与市社科基金",
|
||||
"sciQ1Count": 0,
|
||||
"corePaperCount": 1
|
||||
}
|
||||
]
|
||||
|
||||
38
tests/fixtures/sample_tracks.json
vendored
Normal file
38
tests/fixtures/sample_tracks.json
vendored
Normal file
@@ -0,0 +1,38 @@
|
||||
[
|
||||
{
|
||||
"year": 2027,
|
||||
"agency": "数理学部",
|
||||
"programName": "面上项目",
|
||||
"trackName": "光伏材料",
|
||||
"trackTags": "钙钛矿,光伏,半导体",
|
||||
"priorityKeywords": "界面调控,稳定性",
|
||||
"minTitle": "副高及以上",
|
||||
"minSciQ1": 0,
|
||||
"quota": 10,
|
||||
"sourceDoc": "2027年度申报指南（样例）"
|
||||
},
|
||||
{
|
||||
"year": 2027,
|
||||
"agency": "管理学部",
|
||||
"programName": "青年项目",
|
||||
"trackName": "农村经济",
|
||||
"trackTags": "乡村振兴,农村经济",
|
||||
"priorityKeywords": "数字经济",
|
||||
"minTitle": "",
|
||||
"minSciQ1": 0,
|
||||
"quota": 8,
|
||||
"sourceDoc": "2027年度申报指南（样例）"
|
||||
},
|
||||
{
|
||||
"year": 2027,
|
||||
"agency": "信息学部",
|
||||
"programName": "重点项目",
|
||||
"trackName": "量子计算",
|
||||
"trackTags": "量子计算,量子信息",
|
||||
"priorityKeywords": "",
|
||||
"minTitle": "正高及以上",
|
||||
"minSciQ1": 5,
|
||||
"quota": 3,
|
||||
"sourceDoc": "2027年度申报指南（样例）"
|
||||
}
|
||||
]
|
||||
@@ -40,7 +40,7 @@
|
||||
- **计算类**：费用、税费、分摊、账单字段。
|
||||
- **校验类**：合规、字段一致性、状态机规则。
|
||||
|
||||
推荐配合根目录下的 **`tests/fixtures/sample_request.json`** 与 **`tests/fixtures/expected_response.json`**（复制技能后按域替换字段，保持脱敏）。
|
||||
推荐配合根目录下的 **`tests/fixtures/sample_request.json`**、**`tests/fixtures/sample_tracks.json`** 与 **`tests/fixtures/expected_response.json`**（复制技能后按域替换字段，保持脱敏）。
|
||||
|
||||
### 5. `test_logging_contract.py.sample`
|
||||
|
||||
|
||||
@@ -26,11 +26,14 @@ class TestGoldenCasesSample(unittest.TestCase):
|
||||
req = json.load(f)
|
||||
with open(exp_path, encoding="utf-8") as f:
|
||||
exp = json.load(f)
|
||||
self.assertEqual(req["request_id"], "req_test_001")
|
||||
self.assertTrue(req["parameters"]["options"]["dry_run"])
|
||||
# 示意：out = run(req); 然后 assert out["success"] == exp["success"] 等关键字段
|
||||
self.assertTrue(exp["success"])
|
||||
self.assertEqual(exp["data"]["status"], "ok")
|
||||
# 本技能：sample_request = 教师画像数组（import-teachers 可直接消费）
|
||||
self.assertIsInstance(req, list)
|
||||
self.assertEqual(req[0]["teacherName"], "张教授")
|
||||
# 示意：run_match(req, tracks, exp["season"]) 后断言关键字段
|
||||
self.assertEqual(exp["season"], "2027")
|
||||
top = exp["expectations"][0]
|
||||
self.assertEqual(top["tier"], "强烈推荐")
|
||||
self.assertEqual(top["matchPct"], 100)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
@@ -167,5 +167,48 @@ class TestKernelAndPersistence(MatchRuleTestBase):
|
||||
self.assertEqual(payload["tracks_by_year"].get("2027"), 4)
|
||||
|
||||
|
||||
class TestBatchSkipIncomplete(MatchRuleTestBase):
|
||||
"""批量缺省跳过画像不完整教师（E1），指定单教师保持严格失败。"""
|
||||
|
||||
def test_batch_skips_incomplete_teacher(self) -> None:
|
||||
from service.match_service import run_match
|
||||
|
||||
incomplete = _teacher(teacherName="王讲师", researchTags="", recentPapers="")
|
||||
payload = run_match([_teacher(), incomplete], _tracks(), "2027")
|
||||
self.assertEqual(payload["ok"], True)
|
||||
self.assertEqual(payload["count"], 1)
|
||||
self.assertEqual(len(payload["skipped"]), 1)
|
||||
skipped = payload["skipped"][0]
|
||||
self.assertEqual(skipped["teacher_name"], "王讲师")
|
||||
self.assertIn("E1", skipped["reason"])
|
||||
# 正常教师仍有报告
|
||||
self.assertEqual(len(payload["reports"]), 1)
|
||||
self.assertEqual(payload["reports"][0]["teacher_name"], "张教授")
|
||||
|
||||
def test_batch_brief_marks_skipped_teacher(self) -> None:
|
||||
from service.match_service import run_match
|
||||
|
||||
incomplete = _teacher(teacherName="王讲师", researchTags="", recentPapers="")
|
||||
payload = run_match([_teacher(), incomplete], _tracks(), "2027")
|
||||
with open(payload["brief_file"], encoding="utf-8") as f:
|
||||
html_text = f.read()
|
||||
self.assertIn("画像待补录", html_text)
|
||||
self.assertIn("王讲师", html_text)
|
||||
|
||||
def test_all_skipped_still_returns_success_payload(self) -> None:
|
||||
from service.match_service import run_match
|
||||
|
||||
payload = run_match([_teacher(researchTags="", recentPapers="")], _tracks(), "2027")
|
||||
self.assertEqual(payload["ok"], True)
|
||||
self.assertEqual(payload["count"], 0)
|
||||
self.assertEqual(len(payload["skipped"]), 1)
|
||||
|
||||
def test_strict_mode_raises_for_incomplete(self) -> None:
|
||||
from service.match_service import run_match
|
||||
|
||||
with self.assertRaises(ValueError):
|
||||
run_match([_teacher(researchTags="", recentPapers="")], _tracks(), "2027", skip_incomplete=False)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
|
||||
Reference in New Issue
Block a user