feat: 形态选股 + 板块热力图

app/__init__.py

@@ -37,6 +37,9 @@ def create_app(config_name='default'):
     from app.api.data_jobs_api import data_jobs_bp
     from app.routes.ml_factor_routes import ml_factor_routes
     from app.routes.realtime_analysis_routes import realtime_analysis_routes
+    from app.routes.heatmap import heatmap_routes
+    from app.routes.pattern_screen import pattern_screen_bp
+    from app.api.pattern_screen_api import pattern_screen_api
     app.register_blueprint(api_bp, url_prefix='/api')
     app.register_blueprint(ml_factor_bp)
     app.register_blueprint(text2sql_bp)
@@ -50,7 +53,10 @@ def create_app(config_name='default'):
     app.register_blueprint(data_jobs_bp)
     app.register_blueprint(ml_factor_routes)
     app.register_blueprint(realtime_analysis_routes)
-
+    app.register_blueprint(heatmap_routes)
+    app.register_blueprint(pattern_screen_bp)
+    app.register_blueprint(pattern_screen_api)
+
     from app.main import main_bp
     app.register_blueprint(main_bp)
 

app/api/pattern_screen_api.py

@@ -0,0 +1,47 @@
+"""形态选股 API 端点。"""
+from flask import Blueprint, request, jsonify
+from loguru import logger
+
+pattern_screen_api = Blueprint('pattern_screen_api', __name__, url_prefix='/api/pattern-screen')
+
+
+@pattern_screen_api.route('/groups', methods=['GET'])
+def get_groups():
+    """返回形态分组元数据（含命中数）。"""
+    try:
+        from app.services.pattern_screen_service import get_pattern_screen_service
+        svc = get_pattern_screen_service()
+        groups = svc.get_groups()
+        return jsonify({'code': 200, 'message': '成功', 'data': groups})
+    except Exception as e:
+        logger.error(f"获取形态分组失败: {e}")
+        return jsonify({'code': 500, 'message': f'服务器错误: {str(e)}', 'data': None}), 500
+
+
+@pattern_screen_api.route('/screen', methods=['POST'])
+def screen():
+    """执行形态筛选，返回结果表格。"""
+    try:
+        data = request.get_json() or {}
+        patterns = data.get('patterns', [])
+        sort_by = data.get('sort_by', 'pct_chg')
+        order = data.get('order', 'desc')
+        limit = data.get('limit', 50)
+        offset = data.get('offset', 0)
+
+        from app.services.pattern_screen_service import get_pattern_screen_service
+        svc = get_pattern_screen_service()
+        result = svc.screen(
+            patterns=patterns,
+            sort_by=sort_by,
+            order=order,
+            limit=limit,
+            offset=offset,
+        )
+        return jsonify({'code': 200, 'message': '成功', 'data': result})
+    except ValueError as e:
+        logger.warning(f"形态筛选参数错误: {e}")
+        return jsonify({'code': 400, 'message': str(e), 'data': None}), 400
+    except Exception as e:
+        logger.error(f"形态筛选失败: {e}")
+        return jsonify({'code': 500, 'message': f'服务器错误: {str(e)}', 'data': None}), 500

app/routes/heatmap.py

@@ -0,0 +1,30 @@
+"""板块热力图页面路由。"""
+from flask import Blueprint, render_template
+from loguru import logger
+from app.services.heatmap_service import HeatmapService
+
+heatmap_routes = Blueprint('heatmap_routes', __name__, url_prefix='/heatmap')
+
+
+@heatmap_routes.route('/')
+def index():
+    """板块热力图页面。"""
+    try:
+        service = HeatmapService()
+        sectors, stocks = service.get_heatmap_data()
+        trade_date = sectors[0]['trade_date'] if sectors else ''
+        return render_template(
+            'heatmap.html',
+            sectors_json=sectors,
+            stocks_json=stocks,
+            trade_date=trade_date,
+        )
+    except Exception as e:
+        logger.error(f"热力图加载失败: {e}")
+        return render_template(
+            'heatmap.html',
+            sectors_json=[],
+            stocks_json=[],
+            trade_date='',
+            error='数据加载失败，请确认 data/data.parquet 是否存在',
+        )

app/routes/pattern_screen.py

@@ -0,0 +1,10 @@
+"""形态选股页面路由。"""
+from flask import Blueprint, render_template
+
+pattern_screen_bp = Blueprint('pattern_screen', __name__)
+
+
+@pattern_screen_bp.route('/pattern-screen/')
+def index():
+    """形态选股页面。"""
+    return render_template('pattern_screen.html')

app/services/heatmap_service.py

@@ -0,0 +1,57 @@
+"""板块热力图数据服务 — 读取 data/data.parquet 并按行业聚合。"""
+import os
+import pandas as pd
+import numpy as np
+from loguru import logger
+
+
+class HeatmapService:
+    """板块热力图数据聚合服务。"""
+
+    def __init__(self):
+        self._data_path = os.path.join(
+            os.path.dirname(os.path.dirname(os.path.dirname(__file__))),
+            'data', 'data.parquet'
+        )
+
+    def get_heatmap_data(self):
+        """读取 parquet，返回 (sectors_json, stocks_json)。
+
+        Returns:
+            tuple: (list[dict], list[dict])
+                - sectors: 板块聚合数据，按 total_mv 降序
+                - stocks: 全量个股数据（已过滤停牌）
+        """
+        df = pd.read_parquet(self._data_path)
+        trade_date = str(df['trade_date'].iloc[0])
+
+        # 过滤停牌/退市
+        df = df[df['close'] > 0].copy()
+
+        # 板块聚合
+        sectors = []
+        for industry, group in df.groupby('industry'):
+            total_mv_sum = group['total_mv'].sum()
+            if total_mv_sum == 0:
+                continue
+            avg_pct_chg = np.average(group['pct_chg'], weights=group['total_mv'])
+            sectors.append({
+                'name': industry,
+                'avg_pct_chg': round(avg_pct_chg, 2),
+                'total_mv': round(total_mv_sum, 2),
+                'stock_count': len(group),
+                'up_count': int((group['pct_chg'] > 0).sum()),
+                'down_count': int((group['pct_chg'] < 0).sum()),
+                'net_mf_amount': round(group['net_mf_amount'].sum(), 2),
+                'trade_date': trade_date,
+            })
+
+        sectors.sort(key=lambda x: x['total_mv'], reverse=True)
+
+        # 个股明细
+        stock_cols = ['ts_code', 'name', 'industry', 'pct_chg', 'close',
+                      'total_mv', 'net_mf_amount', 'turnover_rate']
+        stocks_df = df[stock_cols].sort_values('pct_chg', ascending=False)
+        stocks = stocks_df.where(stocks_df.notna(), None).to_dict(orient='records')
+
+        return sectors, stocks