Initial commit

Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>

backend/app/api/state.py

@@ -0,0 +1,132 @@
+"""
+应用全局状态：管理数据引擎、赋分引擎、统计引擎的单例
+避免每次请求重新加载 Excel 数据
+"""
+import logging
+import time
+from datetime import datetime
+from typing import Dict, List, Optional
+
+import pandas as pd
+
+from ..engines.data_engine import DataEngine
+from ..engines.scoring_engine import ScoringEngine
+from ..engines.stats_engine import StatsEngine
+from ..config import SCHOOL_TYPE_MAP, DIMENSION_FRAMEWORK
+
+logger = logging.getLogger(__name__)
+
+
+class AppState:
+    """应用全局状态"""
+
+    def __init__(self):
+        self.data_engine: Optional[DataEngine] = None
+        self.scoring_engine: Optional[ScoringEngine] = None
+        self.stats_engine: Optional[StatsEngine] = None
+        self.raw_scores: Optional[Dict] = None
+        self.sub_scores: Optional[pd.DataFrame] = None
+        self.dim_scores: Optional[pd.DataFrame] = None
+        self.schools: List[str] = []
+        self._initialized = False
+
+    def initialize(self):
+        """初始化所有引擎（只在应用启动时调用一次）"""
+        if self._initialized:
+            return
+
+        start = time.time()
+
+        # 1. 加载数据
+        self.data_engine = DataEngine()
+        self.data_engine.load_all()
+        self.schools = self.data_engine.schools
+
+        # 2. 赋分
+        self.scoring_engine = ScoringEngine(self.data_engine)
+        self.raw_scores = self.scoring_engine.score_all_schools()
+
+        # 3. 统计
+        self.stats_engine = StatsEngine()
+        self.sub_scores = self.stats_engine.compute_dimension_scores(self.raw_scores)
+        self.dim_scores = self.stats_engine.compute_dimension_aggregates(self.sub_scores)
+
+        self._initialized = True
+        elapsed = time.time() - start
+        logger.info(f"全局状态初始化完成，耗时 {elapsed:.1f}s")
+
+    def get_report_data(self, school: str) -> Dict:
+        """获取某学校的报告数据包"""
+        if not self._initialized:
+            self.initialize()
+        return self.stats_engine.compute_school_report_data(
+            school, self.sub_scores, self.dim_scores
+        )
+
+    def get_school_info(self, school: str) -> Dict:
+        """获取学校基本信息"""
+        info = SCHOOL_TYPE_MAP.get(school, {})
+        if not self.dim_scores is None and school in self.dim_scores.index:
+            score = round(float(self.dim_scores.loc[school, "总体得分"]), 2)
+            rank = int((self.dim_scores["总体得分"] >= self.dim_scores.loc[school, "总体得分"]).sum())
+        else:
+            score = 0
+            rank = 0
+        return {
+            "name": school,
+            "type": info.get("type", ""),
+            "code": info.get("code", ""),
+            "nature": info.get("nature", ""),
+            "feature": info.get("feature", ""),
+            "score": score,
+            "rank": rank,
+            "total_schools": len(self.schools),
+        }
+
+    def get_all_schools_summary(self) -> List[Dict]:
+        """获取所有学校的摘要信息"""
+        if not self._initialized:
+            self.initialize()
+
+        summaries = []
+        # 排名
+        sorted_schools = self.dim_scores["总体得分"].sort_values(ascending=False)
+
+        for rank, (school, score) in enumerate(sorted_schools.items(), 1):
+            if school == "总体得分":
+                continue
+            info = SCHOOL_TYPE_MAP.get(school, {})
+
+            # 聚类
+            dim_cols = [c for c in self.dim_scores.columns if c in DIMENSION_FRAMEWORK]
+            cluster_result = self.stats_engine.cluster_analysis(self.dim_scores[dim_cols])
+            cluster = cluster_result["school_clusters"].get(school, "")
+
+            # 检查已生成的报告
+            from ..config import OUTPUT_DIR
+            report_path = OUTPUT_DIR / f"{school}_报告.html"
+            has_report = report_path.exists()
+            report_size = report_path.stat().st_size if has_report else 0
+            report_generated_at = ""
+            if has_report:
+                mtime = report_path.stat().st_mtime
+                report_generated_at = datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
+
+            summaries.append({
+                "name": school,
+                "type": info.get("type", ""),
+                "code": info.get("code", ""),
+                "nature": info.get("nature", ""),
+                "score": round(float(score), 2),
+                "rank": rank,
+                "cluster": cluster,
+                "has_report": has_report,
+                "report_size": report_size,
+                "report_generated_at": report_generated_at,
+            })
+
+        return summaries
+
+
+# 全局单例
+app_state = AppState()