f5d6647837
新增项目: - 强基计划(strong_foundation): 14所985院校 - 北大/清华/复旦/上交/浙大/中科大/南大/武大/华科/中山/川大/中南/湖大/国防科大 - 分数线600-660, 聚焦基础学科, 需参加校测 新增规则(2条): - 强基需参加校测(85%高考+15%校测) - 专业限定基础学科(数/理/化/生/史/哲/古文字) 修复: - test_provenance 排除 special_programs.json(非省份文件) 当前完整覆盖12类路径: 1.农村定向医疗 2.公费农科 3.消防定向 4.铁路定向 5.司法定向 6.定向军士(48所) 7.公费师范 8.央企订单(22所) 9.少数民族预科 10.三大专项 11.定向西藏 12.强基计划(14所) 数据规模: 12类, 115+院校, 24条规则, 13条prompt路径 验证: pytest 1330 passed, 0 failed
116 lines
4.5 KiB
Python
116 lines
4.5 KiB
Python
"""特殊批次定向培养计划模块测试。"""
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from __future__ import annotations
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from pathlib import Path
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from data.crowd_db.special_programs_loader import SpecialProgramsLoader
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_DATA_PATH = Path(__file__).resolve().parent.parent / "special_programs.json"
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_RULES_PATH = (
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Path(__file__).resolve().parents[3]
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/ "data"
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/ "rules"
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/ "special_programs_rules.json"
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)
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class TestSpecialProgramsLoader:
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def setup_method(self):
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self.loader = SpecialProgramsLoader(
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data_path=_DATA_PATH, rules_path=_RULES_PATH
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)
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def test_loads_8_program_types(self):
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programs = self.loader.list_programs()
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types = {p["program_type"] for p in programs}
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expected = {
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"rural_medical",
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"public_agriculture",
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"fire_rescue",
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"railway_directed",
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"judicial_directed",
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"military_nco",
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"public_teacher",
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"enterprise_order",
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"minority_prep",
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"targeted_poverty",
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"tibet_directed",
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"strong_foundation",
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}
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for t in expected:
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assert t in types, f"缺少项目类型: {t}"
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def test_get_program(self):
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p = self.loader.get_program("rural_medical")
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assert p is not None
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assert p["program_name"] == "农村订单定向免费医学生"
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assert p["key_features"]["service_years"] == 6
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def test_get_program_not_found(self):
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assert self.loader.get_program("nonexistent") is None
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def test_list_programs_for_hunan(self):
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programs = self.loader.list_programs_for_province("湖南")
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types = {p["program_type"] for p in programs}
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# 湖南应该有 rural_medical（applicable_provinces 含"湖南"）
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# fire_rescue/railway_directed/judicial_directed 是"全国"
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assert "rural_medical" in types
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assert "fire_rescue" in types # 全国
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assert "railway_directed" in types # 全国
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def test_find_matching_schools_for_hunan_578(self):
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"""湖南 578 分应该能匹配到铁路/消防/医疗等院校。"""
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results = self.loader.find_matching_schools("湖南", 578)
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assert len(results) > 0
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# 应包含铁路（湖南铁道职业技术学院 340 分）
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types = {r["program_type"] for r in results}
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assert "railway_directed" in types
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def test_find_matching_schools_low_score(self):
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"""低分考生（250）应该匹配到铁路专科。"""
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results = self.loader.find_matching_schools("湖北", 250)
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# 武汉铁路职业技术学院 223 分
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railway = [r for r in results if r["program_type"] == "railway_directed"]
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assert len(railway) > 0
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assert any("武汉铁路" in r["school"] for r in railway)
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def test_find_matching_schools_high_score_excludes_far(self):
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"""高分考生不应匹配到分数差距过大的院校。"""
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results = self.loader.find_matching_schools("湖南", 650)
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# 650 分不应匹配到 223 分的武汉铁路（差距 427 分，223*0.85=189.55）
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# 但仍然匹配（因为 650 >= 189.55），只是 gap 很大
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# 验证至少不报错
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assert isinstance(results, list)
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def test_get_applicable_rules(self):
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rules = self.loader.get_applicable_rules("rural_medical")
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rule_ids = {r["rule_id"] for r in rules}
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assert "special.rural_medical.hukou_requirement" in rule_ids
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assert "special.rural_medical.service_commitment" in rule_ids
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assert "special.general.tuition_free" in rule_ids
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def test_build_recommendation_for_review(self):
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"""审核场景推荐摘要。"""
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recs = self.loader.build_recommendation_for_review("湖南", 450)
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assert len(recs) > 0
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# 450 分应该能匹配到定向医疗（444/441分）
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types = {r["program_type"] for r in recs}
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assert "rural_medical" in types
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# 每条都有 match_score
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for r in recs:
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assert "match_score" in r
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assert 0 <= r["match_score"] <= 100
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def test_build_recommendation_no_match(self):
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"""不存在的省份只返回全国性项目（fire/railway/judicial），不报错。"""
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recs = self.loader.build_recommendation_for_review("火星", 500)
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# 全国性项目仍可能返回，但不应报错
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assert isinstance(recs, list)
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def test_rules_loaded(self):
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rules = self.loader.rules
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assert "rules" in rules
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assert len(rules["rules"]) >= 9
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