{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "initial_id",
   "metadata": {
    "jupyter": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "from operator import index\n",
    "\n",
    "import tushare as ts\n",
    "import pandas as pd\n",
    "import time\n",
    "\n",
    "ts.set_token('3a0741c702ee7e5e5f2bf1f0846bafaafe4e320833240b2a7e4a685f')\n",
    "pro = ts.pro_api()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f448da220816bf98",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-26T10:23:18.517518100Z",
     "start_time": "2025-04-09T14:57:27.392846Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据已经成功存储到index_data.h5文件中\n"
     ]
    }
   ],
   "source": [
    "# 定义四个指数\n",
    "index_list = [\n",
    "    # '399300.SZ', \n",
    "    '000905.SH', \n",
    "    '000852.SH', \n",
    "    '399006.SZ'\n",
    "              ]\n",
    "\n",
    "# 获取并存储数据\n",
    "all_data = []\n",
    "\n",
    "for ts_code in index_list:\n",
    "    df = pro.index_daily(ts_code=ts_code)  # 可根据需要设置日期\n",
    "    df['ts_code'] = ts_code  # 添加ts_code列来区分数据\n",
    "    # print(df)\n",
    "    all_data.append(df)\n",
    "\n",
    "# 合并所有数据\n",
    "final_df = pd.concat(all_data, ignore_index=True)\n",
    "\n",
    "# 存储到H5文件\n",
    "final_df.to_hdf('/mnt/d/PyProject/NewStock/data/index_data.h5', key='index_data', mode='w')\n",
    "\n",
    "print(\"数据已经成功存储到index_data.h5文件中\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "907f732d3c397bf",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-26T10:23:18.552166300Z",
     "start_time": "2025-04-09T14:57:37.695917Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         ts_code trade_date      close       open       high        low  \\\n",
      "0      000905.SH   20251010  7398.2241  7499.3917  7509.1161  7373.9841   \n",
      "1      000905.SH   20251009  7548.9226  7470.0474  7559.0920  7437.3242   \n",
      "2      000905.SH   20250930  7412.3684  7372.5240  7428.0307  7372.0634   \n",
      "3      000905.SH   20250929  7350.5599  7251.5221  7377.2217  7216.7357   \n",
      "4      000905.SH   20250926  7240.9114  7311.8433  7351.7931  7237.0459   \n",
      "...          ...        ...        ...        ...        ...        ...   \n",
      "13810  399006.SZ   20100607  1069.4680  1005.0280  1075.2250  1001.7020   \n",
      "13811  399006.SZ   20100604  1027.6810   989.6810  1027.6810   986.5040   \n",
      "13812  399006.SZ   20100603   998.3940  1002.3550  1026.7020   997.7750   \n",
      "13813  399006.SZ   20100602   997.1190   967.6090   997.1190   952.6110   \n",
      "13814  399006.SZ   20100601   973.2330   986.0150   994.7930   948.1180   \n",
      "\n",
      "       pre_close    change  pct_chg           vol        amount  \n",
      "0      7548.9226 -150.6985  -1.9963  2.622566e+08  5.021274e+08  \n",
      "1      7412.3684  136.5542   1.8422  2.831308e+08  5.357568e+08  \n",
      "2      7350.5599   61.8085   0.8409  2.207075e+08  4.449564e+08  \n",
      "3      7240.9114  109.6485   1.5143  2.335394e+08  4.338645e+08  \n",
      "4      7341.3238 -100.4124  -1.3678  2.114441e+08  4.301976e+08  \n",
      "...          ...       ...      ...           ...           ...  \n",
      "13810  1027.6810   41.7870   4.0661  2.655275e+06  9.106095e+06  \n",
      "13811   998.3940   29.2870   2.9334  1.500295e+06  5.269441e+06  \n",
      "13812   997.1190    1.2750   0.1279  1.616805e+06  6.240835e+06  \n",
      "13813   973.2330   23.8860   2.4543  1.074628e+06  4.001206e+06  \n",
      "13814  1000.0000  -26.7670  -2.6767  1.356285e+06  4.924177e+06  \n",
      "\n",
      "[13815 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "h5_filename = '/mnt/d/PyProject/NewStock/data/index_data.h5'\n",
    "key = '/index_data'\n",
    "with pd.HDFStore(h5_filename, mode='r') as store:\n",
    "    df = store[key]\n",
    "    print(df)\n"
   ]
  }
 ],
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