新增建材价格指数趋势监控仪表盘

2026-07-24 12:01:08 +08:00
parent 4b4469528f
commit f6c54971e4
3 changed files with 585 additions and 0 deletions
@@ -0,0 +1,89 @@
+"""拉取建材价格指数，更新 data.json 并刷新 index.html。"""
+import json
+import pandas as pd
+import akshare as ak
+
+df = ak.macro_china_construction_index()
+df['日期'] = pd.to_datetime(df['日期'])
+df = df.sort_values('日期').reset_index(drop=True)
+
+for w in [5, 10, 20, 60]:
+    df[f'MA{w}'] = df['最新值'].rolling(w).mean().round(1)
+    df[f'MA{w}_dir'] = df[f'MA{w}'].diff().apply(lambda x: 'up' if x > 0 else ('down' if x < 0 else 'flat'))
+
+latest = df.iloc[-1]
+
+signals = []
+if latest['最新值'] > latest['MA5']:
+    signals.append(('短期', '偏多', '价格 > MA5'))
+else:
+    signals.append(('短期', '偏空', '价格 < MA5'))
+if latest['MA5'] > latest['MA20']:
+    signals.append(('中期', '偏多', 'MA5 > MA20'))
+else:
+    signals.append(('中期', '偏空', 'MA5 < MA20'))
+if latest['MA20'] > latest['MA60']:
+    signals.append(('长期', '偏多', 'MA20 > MA60'))
+else:
+    signals.append(('长期', '偏空', 'MA20 < MA60'))
+
+momentum_5d = latest['最新值'] - df.iloc[-6]['最新值']
+signals.append(('动量(5日)', '偏多' if momentum_5d > 0 else '偏空', f"{momentum_5d:+d}"))
+
+bull_count = sum(1 for _, s, _ in signals if s == '偏多')
+if bull_count >= 3:
+    overall = ('偏多', '#16a34a')
+elif bull_count <= 1:
+    overall = ('偏空', '#dc2626')
+else:
+    overall = ('震荡', '#d97706')
+
+summary = {
+    'date': latest['日期'].strftime('%Y-%m-%d'),
+    'value': int(latest['最新值']),
+    'change': round(float(latest['涨跌幅']), 4),
+    'chg_3m': round(float(latest['近3月涨跌幅']), 4),
+    'chg_6m': round(float(latest['近6月涨跌幅']), 4),
+    'chg_1y': round(float(latest['近1年涨跌幅']), 4),
+}
+
+mas = {}
+for w in [5, 10, 20, 60]:
+    mas[f'MA{w}'] = {
+        'value': float(latest[f'MA{w}']),
+        'direction': latest[f'MA{w}_dir'],
+        'price_vs_ma': 'above' if latest['最新值'] > latest[f'MA{w}'] else 'below'
+    }
+
+rows = []
+for _, r in df.tail(30).iterrows():
+    rows.append({
+        'date': r['日期'].strftime('%m-%d'),
+        'value': int(r['最新值']),
+        'chg': round(float(r['涨跌幅']), 4),
+        'MA5': None if pd.isna(r['MA5']) else round(float(r['MA5']), 1),
+        'MA20': None if pd.isna(r['MA20']) else round(float(r['MA20']), 1),
+        'MA60': None if pd.isna(r['MA60']) else round(float(r['MA60']), 1),
+    })
+
+output = {
+    'summary': summary,
+    'mas': mas,
+    'signals': [{'period': p, 'signal': s, 'detail': d} for p, s, d in signals],
+    'overall': {'signal': overall[0], 'color': overall[1]},
+    'recent': rows,
+}
+
+with open('data.json', 'w') as f:
+    json.dump(output, f, ensure_ascii=False, indent=2)
+
+SENTINEL = '/*__DATA_SENTINEL__*/{}'
+html = open('index.html').read()
+html = html.replace(SENTINEL, json.dumps(output, ensure_ascii=False))
+open('index.html', 'w').write(html)
+
+print(f"刷新完成: {summary['date']} → {summary['value']} (日涨跌 {summary['change']:+.2f}%)")
+print(f"综合信号: {overall[0]}")
+print("信号明细:")
+for p, s, d in signals:
+    print(f"  {p}: {s} ({d})")