initial-import: 2026-04-11 21:18:55

2026-04-11 21:18:55 +08:00
commit 5e6b2d73eb
264 changed files with 117047 additions and 0 deletions
@@ -0,0 +1,192 @@
+#!/bin/bash
+# 在容器内导入数据
+
+echo "🚀 在容器内导入510300.SSE数据..."
+echo "============================================================"
+
+# 创建脚本文件并执行
+cat > /tmp/import_data.py << 'EOF'
+import pandas as pd
+import sqlite3
+import os
+from datetime import datetime
+
+print("🚀 在容器内导入510300.SSE数据...")
+print("=" * 60)
+
+# 配置
+parquet_path = "/volume1/stock-data/sanguo_quant_live/zhaoyun-data/data/raw/daily/sh510300_daily.parquet"
+db_path = "/volume1/stock/sanguo_vnpy/data/database_test.db"
+symbol = "510300.SSE"
+exchange = "SSE"
+interval = "1d"
+
+print("源数据: " + parquet_path)
+print("目标数据库: " + db_path)
+print("标的: " + symbol)
+
+# 检查源文件存在
+if not os.path.exists(parquet_path):
+    print("❌ 源文件不存在: " + parquet_path)
+    exit(1)
+
+print("✅ 源文件存在")
+
+# 读取parquet
+print("\n📥 读取parquet数据...")
+df = pd.read_parquet(parquet_path)
+print("   读取成功: " + str(len(df)) + " 行")
+
+# 创建数据库
+print("\n💾 创建vn.py数据库...")
+
+if os.path.exists(db_path):
+    os.remove(db_path)
+    print("   删除旧数据库")
+
+os.makedirs(os.path.dirname(db_path), exist_ok=True)
+
+conn = sqlite3.connect(db_path)
+cursor = conn.cursor()
+
+# 创建vn.py标准表结构
+cursor.execute("""
+CREATE TABLE dbbardata (
+    symbol TEXT NOT NULL,
+    exchange TEXT,
+    interval TEXT NOT NULL,
+    datetime INTEGER NOT NULL,
+    open REAL NOT NULL,
+    high REAL NOT NULL,
+    low REAL NOT NULL,
+    close REAL NOT NULL,
+    volume INTEGER NOT NULL,
+    open_interest REAL,
+    turnover REAL,
+    PRIMARY KEY (symbol, interval, datetime)
+);
+""")
+
+# 创建索引
+cursor.execute("CREATE INDEX ix_dbbardata_symbol ON dbbardata(symbol);")
+cursor.execute("CREATE INDEX ix_dbbardata_symbol_interval ON dbbardata(symbol, interval);")
+
+# 导入数据
+print("\n📊 导入数据...")
+
+imported = 0
+errors = 0
+
+for idx, row in df.iterrows():
+    # 获取日期
+    date_val = row['date']
+    
+    if isinstance(date_val, pd.Timestamp):
+        dt = date_val.to_pydatetime()
+    else:
+        date_str = str(date_val)
+        if '-' in date_str:
+            dt = datetime.strptime(date_str, '%Y-%m-%d')
+        else:
+            dt = datetime.strptime(date_str, '%Y%m%d')
+    
+    timestamp = int(dt.timestamp())
+    
+    # 获取价格数据
+    open_price = float(row['open'])
+    high_price = float(row['high'])
+    low_price = float(row['low'])
+    close_price = float(row['close'])
+    volume = int(float(row['volume']))
+    
+    # 成交额
+    if 'amount' in row:
+        turnover = float(row['amount'])
+    else:
+        turnover = volume * close_price
+    
+    # 插入
+    try:
+        cursor.execute("""
+        INSERT INTO dbbardata (
+            symbol, exchange, interval, datetime,
+            open, high, low, close, volume, turnover
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        """, (
+            symbol,
+            exchange,
+            interval,
+            timestamp,
+            open_price,
+            high_price,
+            low_price,
+            close_price,
+            volume,
+            turnover
+        ))
+        
+        imported = imported + 1
+        
+        if imported % 500 == 0:
+            print("   已导入 " + str(imported) + " 行...")
+            
+    except Exception as e:
+        print("   ⚠️  第" + str(idx) + "行导入失败: " + str(e))
+        errors = errors + 1
+
+# 提交
+conn.commit()
+
+# 验证
+print("\n🔍 验证导入结果...")
+cursor.execute("SELECT COUNT(*) FROM dbbardata WHERE symbol = ?", (symbol,))
+count = cursor.fetchone()[0]
+
+cursor.execute("SELECT MIN(datetime), MAX(datetime) FROM dbbardata WHERE symbol = ?", (symbol,))
+min_ts_max_ts = cursor.fetchone()
+min_ts = min_ts_max_ts[0]
+max_ts = min_ts_max_ts[1]
+
+if min_ts and max_ts:
+    min_dt = datetime.fromtimestamp(min_ts).strftime('%Y-%m-%d')
+    max_dt = datetime.fromtimestamp(max_ts).strftime('%Y-%m-%d')
+else:
+    min_dt = 'N/A'
+    max_dt = 'N/A'
+
+cursor.execute("SELECT MIN(close), MAX(close), AVG(volume) FROM dbbardata WHERE symbol = ?", (symbol,))
+min_close_max_close_avg_volume = cursor.fetchone()
+min_close = min_close_max_close_avg_volume[0]
+max_close = min_close_max_close_avg_volume[1]
+avg_volume = min_close_max_close_avg_volume[2]
+
+conn.close()
+
+# 统计
+print("\n" + "="*60)
+print("✅ 导入完成！")
+print("源文件: " + parquet_path)
+print("目标数据库: " + db_path)
+print("标的: " + symbol)
+print("源数据行数: " + str(len(df)))
+print("成功导入: " + str(imported))
+print("导入失败: " + str(errors))
+print("数据库验证: " + str(count) + " 行")
+print("时间范围: " + min_dt + " -> " + max_dt)
+print("价格范围: " + f"{min_close:.2f}" + " ~ " + f"{max_close:.2f}")
+print("平均成交量: " + f"{avg_volume:.0f}")
+print("="*60)
+
+# 显示文件大小
+if os.path.exists(db_path):
+    size_kb = os.path.getsize(db_path) / 1024
+    print("\n📦 数据库文件大小: " + f"{size_kb:.1f} KB")
+
+print("\n🎯 完成！")
+print("数据库已创建在容器可访问路径: " + db_path)
+print("现在可以重启API服务了")
+EOF
+
+# 执行脚本
+ssh admin@192.168.2.154 "export PATH=\$PATH:/var/packages/Docker/target/usr/bin && docker cp /tmp/import_data.py sanguo_vnpy:/app/scripts/"
+ssh admin@192.168.2.154 "export PATH=\$PATH:/var/packages/Docker/target/usr/bin && docker exec sanguo_vnpy python3 /app/scripts/import_data.py