{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "initial_id",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:57:27.092313Z",
     "start_time": "2025-04-09T14:57:26.124592Z"
    }
   },
   "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": 6,
   "id": "f448da220816bf98",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:57:37.680808Z",
     "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": 7,
   "id": "907f732d3c397bf",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:57:37.730922Z",
     "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   20250530  5671.0723  5704.7710  5704.7710  5665.5177   \n",
      "1      000905.SH   20250529  5719.9101  5637.0633  5724.5185  5637.0633   \n",
      "2      000905.SH   20250528  5637.2378  5651.8755  5660.4696  5628.4165   \n",
      "3      000905.SH   20250527  5652.1454  5666.3027  5667.8710  5629.1343   \n",
      "4      000905.SH   20250526  5669.4609  5653.2063  5693.6250  5644.5794   \n",
      "...          ...        ...        ...        ...        ...        ...   \n",
      "13546  399006.SZ   20100607  1069.4680  1005.0280  1075.2250  1001.7020   \n",
      "13547  399006.SZ   20100604  1027.6810   989.6810  1027.6810   986.5040   \n",
      "13548  399006.SZ   20100603   998.3940  1002.3550  1026.7020   997.7750   \n",
      "13549  399006.SZ   20100602   997.1190   967.6090   997.1190   952.6110   \n",
      "13550  399006.SZ   20100601   973.2330   986.0150   994.7930   948.1180   \n",
      "\n",
      "       pre_close   change  pct_chg           vol        amount  \n",
      "0      5719.9101 -48.8378  -0.8538  1.099007e+08  1.376706e+08  \n",
      "1      5637.2378  82.6723   1.4665  1.146825e+08  1.480951e+08  \n",
      "2      5652.1454 -14.9076  -0.2638  9.490888e+07  1.199598e+08  \n",
      "3      5669.4609 -17.3155  -0.3054  9.514936e+07  1.252757e+08  \n",
      "4      5653.0436  16.4173   0.2904  9.717099e+07  1.273436e+08  \n",
      "...          ...      ...      ...           ...           ...  \n",
      "13546  1027.6810  41.7870   4.0661  2.655275e+06  9.106095e+06  \n",
      "13547   998.3940  29.2870   2.9334  1.500295e+06  5.269441e+06  \n",
      "13548   997.1190   1.2750   0.1279  1.616805e+06  6.240835e+06  \n",
      "13549   973.2330  23.8860   2.4543  1.074628e+06  4.001206e+06  \n",
      "13550  1000.0000 -26.7670  -2.6767  1.356285e+06  4.924177e+06  \n",
      "\n",
      "[13551 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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