6af6e0156b
- data/crowd_db/risk_report.py: build_crowd_risks 把 RiskFinding 转 模板所需 crowd_risks 字典；高/中/低三色 emoji（🔴/🟡/🟢）； group_by_risk / format_risk_summary / render_risk_table 辅助能力； LoaderLike Protocol 避免对 CrowdDBLoader 强依赖 - data/crowd_db/tests/test_risk_report.py: 22 用例覆盖三色 emoji、 模板字段、alternatives 重映射、防御 fallback、空方案、不存在 省份、自定义 loader 注入 - scripts/verify_t2_4_e2e.py: 用真实湖南 575 分数据 + audit_report.html 模板渲染一遍，6/6 集成断言通过 - CHANGELOG: T2.4 记录 验证：data/crowd_db/tests/ 105/105、仓库全量 392/392、ruff All checks passed、validate_template.py PASS
115 lines
4.0 KiB
Python
115 lines
4.0 KiB
Python
"""T2.4 端到端集成验证脚本
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模拟 audit_report.html 模板实际渲染时使用的 crowd_risks 字典，
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确认 build_crowd_risks 输出的字段与模板期望完全一致。
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跑法：python3 scripts/verify_t2_4_e2e.py
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"""
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import sys
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from pathlib import Path
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# 让 data/ 与 skills/ 模块可导入
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ROOT = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(ROOT))
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from jinja2 import Environment, FileSystemLoader, select_autoescape # noqa: E402
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from data.crowd_db.risk_report import ( # noqa: E402
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build_crowd_risks,
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format_risk_summary,
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group_by_risk,
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)
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def main() -> int:
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# 1) 真实场景：湖南 575 分，扎堆样本方案
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plan = [
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{"school": "长沙理工大学", "major": "计算机科学与技术"}, # frequency=4 → high
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{
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"school": "湖南科技大学",
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"major": "机械设计制造及其自动化",
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}, # frequency=2 → medium
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{"school": "某某野鸡大学", "major": "考古学"}, # 0 → 跳过
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]
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crowd_risks = build_crowd_risks(plan, user_score=575, province="湖南")
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print(f"✅ build_crowd_risks 输出 {len(crowd_risks)} 条风险")
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print(f" 汇总：{format_risk_summary(crowd_risks)}")
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grouped = group_by_risk(crowd_risks)
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print(
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f" 分组: high={len(grouped['high'])} medium={len(grouped['medium'])} low={len(grouped['low'])}"
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)
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# 2) 模板字段完整性逐项断言
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required_fields = {
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"school",
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"major",
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"frequency",
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"predicted_increase",
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"risk_level",
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"risk_level_label",
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"risk_emoji",
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"platforms",
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"alternatives",
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}
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for r in crowd_risks:
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missing = required_fields - r.keys()
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assert not missing, f"missing fields: {missing} in {r}"
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print(f"✅ 模板必需字段全部存在（{len(required_fields)} 个）")
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# 3) alternatives 字段名重映射检查
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for r in crowd_risks:
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for alt in r["alternatives"]:
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assert "school" in alt, f"alternative missing 'school' key: {alt}"
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assert "score" in alt, f"alternative missing 'score' key: {alt}"
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assert isinstance(alt["score"], int), f"score not int: {alt}"
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print("✅ alternatives 字段名重映射正确（name→school，score 为 int）")
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# 4) 三色 emoji 检查
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emojis = {r["risk_emoji"] for r in crowd_risks}
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assert emojis.issubset({"🔴", "🟡", "🟢"}), f"unexpected emojis: {emojis}"
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print(f"✅ 三色 emoji 标识正常：{emojis}")
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# 5) 真实模板渲染（不修改模板，使用当前 crowd_risks 数据）
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template_path = ROOT / "skills" / "gaokao-audit" / "templates" / "audit_report.html"
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env = Environment(
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loader=FileSystemLoader(str(template_path.parent)),
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autoescape=select_autoescape(["html"]),
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)
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template = env.get_template("audit_report.html")
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mock_payload = {
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"source": "端到端测试",
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"candidate_info": "湖南 575分 物化生",
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"audit_time": "2026-06-12 17:00",
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"report_id": "AUDIT-T24-E2E",
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"overall_score": 70,
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"fatal_count": 0,
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"warning_count": len(crowd_risks),
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"info_count": 0,
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"policy_errors": [],
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"crowd_risks": crowd_risks,
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"data_issues": [],
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"suggestions": [],
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}
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rendered = template.render(**mock_payload)
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# 渲染输出必须包含每个风险院校名 + emoji
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for r in crowd_risks:
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assert r["school"] in rendered, f"school not in rendered: {r['school']}"
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assert r["risk_emoji"] in rendered, f"emoji not in rendered: {r['risk_emoji']}"
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print(f"✅ 真实模板渲染成功，{len(rendered)} chars")
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# 6) 三色 emoji 在渲染输出中可见性
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assert "🔴" in rendered or "🟡" in rendered or "🟢" in rendered, (
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"no risk emoji found in rendered output"
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)
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print("✅ 风险 emoji 已渲染到 HTML 中")
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print("\n🎯 T2.4 端到端集成验证全部通过。")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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