完成回测的基本计算

sql2dataframe.ipynb

@@ -0,0 +1,72 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "host = '81.71.3.24'\n",
+    "port = 6785\n",
+    "database = 'leopard_dev'\n",
+    "username = 'leopard'\n",
+    "password = '9NEzFzovnddf@PyEP?e*AYAWnCyd7UhYwQK$pJf>7?ccFiN^x4$eKEZ5~E<7<+~X'"
+   ],
+   "id": "1e8d815ee9b8c936"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import psycopg2\n",
+    "\n",
+    "dailies_df = pd.DataFrame()\n",
+    "\n",
+    "with psycopg2.connect(host=host, port=port, database=database, user=username, password=password) as connection:\n",
+    "    with connection.cursor() as cursor:\n",
+    "        # language=PostgreSQL\n",
+    "        cursor.execute(\n",
+    "            \"\"\"select trade_date, open, close, high, low, factor\n",
+    "from leopard_daily daily\n",
+    "         left join leopard_stock stock on stock.id = daily.stock_id\n",
+    "where stock.code = '000001.SZ'\n",
+    "  and daily.trade_date between '2025-01-01 00:00:00' and '2025-12-31 23:59:59'\n",
+    "order by daily.trade_date\"\"\"\n",
+    "            )\n",
+    "        rows = cursor.fetchall()\n",
+    "\n",
+    "        dailies_df = pd.DataFrame.from_records(rows, columns=['trade_date', 'open', 'close', 'high', 'low', 'factor'])\n",
+    "\n",
+    "dailies_df"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}