examples/alpha_research/download_data_xt.ipynb · OSCHINA-MIRROR/mirrors-vn-py

OSCHINA-MIRROR/mirrors-vn-py

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download_data_xt.ipynb 180 КБ

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 准备数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "xtquant文档地址：http://dict.thinktrader.net/nativeApi/start_now.html\n"
     ]
    }
   ],
   "source": [
    "# 加载模块\n",
    "from datetime import datetime\n",
    "\n",
    "from tqdm import tqdm\n",
    "from xtquant import xtdata\n",
    "\n",
    "from vnpy.trader.database import DB_TZ\n",
    "from vnpy.trader.datafeed import get_datafeed\n",
    "from vnpy.trader.constant import Exchange, Interval\n",
    "from vnpy.trader.object import HistoryRequest\n",
    "\n",
    "from vnpy.alpha import AlphaLab, logger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 设置下载参数\n",
    "task_name = \"csi300\"\n",
    "index_symbol = \"000300.SSE\"\n",
    "xt_index_symbol = \"000300.SH\"\n",
    "\n",
    "start_date = \"20070101\"\n",
    "end_date = \"20231231\"\n",
    "\n",
    "intervals = [\n",
    "    Interval.DAILY,\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 创建投研实验室\n",
    "lab = AlphaLab(f\"./lab/{task_name}\")    # 指定数据文件夹"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 初始化数据服务（这里配置使用的迅投研）\n",
    "datafeed = get_datafeed()\n",
    "datafeed.init()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  'count': 85},\n",
       " '101732.BKZS': {'start_time': datetime.datetime(2016, 4, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2021, 9, 3, 0, 0),\n",
       "  'count': 13},\n",
       " '101733.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 452},\n",
       " '101734.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 8, 23, 20, 0, 0, 16000),\n",
       "  'count': 376},\n",
       " '101735.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 3, 26, 8, 50, 0, 3000),\n",
       "  'count': 22},\n",
       " '101736.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 11, 21, 20, 0, 0, 2000),\n",
       "  'count': 128},\n",
       " '101737.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 8, 12, 20, 0, 0, 2000),\n",
       "  'count': 22},\n",
       " '101738.BKZS': {'start_time': datetime.datetime(2016, 2, 5, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 1, 27, 0, 0),\n",
       "  'count': 73},\n",
       " '101739.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 298},\n",
       " '101740.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 5, 4, 8, 0, 0, 3000),\n",
       "  'count': 134},\n",
       " '101741.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 7, 11, 20, 0, 0, 2000),\n",
       "  'count': 53},\n",
       " '101742.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 300},\n",
       " '101743.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 3, 22, 8, 50, 0, 2000),\n",
       "  'count': 253},\n",
       " '101744.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 11, 21, 20, 0, 0, 2000),\n",
       "  'count': 102},\n",
       " '101745.BKZS': {'start_time': datetime.datetime(2017, 5, 31, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 5, 16, 0, 0),\n",
       "  'count': 8},\n",
       " '101746.BKZS': {'start_time': datetime.datetime(2016, 1, 4, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 492},\n",
       " '101747.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 10, 14, 20, 0, 0, 2000),\n",
       "  'count': 277},\n",
       " '101748.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 6, 26, 0, 0),\n",
       "  'count': 32},\n",
       " '101749.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2021, 9, 3, 0, 0),\n",
       "  'count': 76},\n",
       " '101750.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n",
       "  'count': 127},\n",
       " '101751.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2023, 6, 13, 0, 0),\n",
       "  'count': 74},\n",
       " '101752.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2023, 1, 3, 0, 0),\n",
       "  'count': 69},\n",
       " '101753.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 615},\n",
       " '101754.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 8, 15, 20, 0, 0, 2000),\n",
       "  'count': 84},\n",
       " '101755.BKZS': {'start_time': datetime.datetime(2016, 4, 11, 0, 0),\n",
       "  'end_time': datetime.datetime(2023, 8, 22, 0, 0),\n",
       "  'count': 41},\n",
       " '101756.BKZS': {'start_time': datetime.datetime(2018, 6, 14, 0, 0),\n",
       "  'end_time': datetime.datetime(2019, 3, 19, 0, 0),\n",
       "  'count': 4},\n",
       " '101757.BKZS': {'start_time': datetime.datetime(2017, 7, 21, 0, 0),\n",
       "  'end_time': datetime.datetime(2023, 11, 25, 0, 0),\n",
       "  'count': 48},\n",
       " '101758.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 214},\n",
       " '101759.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 12, 26, 18, 34, 7, 890000),\n",
       "  'count': 123},\n",
       " '101760.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n",
       "  'count': 110},\n",
       " '101761.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n",
       "  'count': 530},\n",
       " '101762.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 149},\n",
       " '101763.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 6, 13, 0, 0),\n",
       "  'count': 2},\n",
       " '101764.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 1, 27, 0, 0),\n",
       "  'count': 58},\n",
       " '101765.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 9, 5, 20, 0, 0, 2000),\n",
       "  'count': 82},\n",
       " '101766.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 9, 5, 20, 0, 0, 2000),\n",
       "  'count': 86},\n",
       " '101767.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 5, 8, 0, 0, 3000),\n",
       "  'count': 345},\n",
       " '101768.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2024, 8, 23, 20, 0, 0, 16000),\n",
       "  'count': 60},\n",
       " '101769.BKZS': {'start_time': datetime.datetime(2016, 5, 6, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 9, 22, 0, 0),\n",
       "  'count': 103},\n",
       " '101770.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2019, 3, 19, 0, 0),\n",
       "  'count': 4},\n",
       " '101771.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n",
       "  'count': 78},\n",
       " '101772.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 5, 4, 8, 0, 0, 3000),\n",
       "  'count': 115},\n",
       " '101773.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2021, 11, 26, 0, 0),\n",
       "  'count': 5},\n",
       " '101774.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2022, 9, 22, 0, 0),\n",
       "  'count': 36},\n",
       " '101775.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 3, 11, 8, 50, 0, 16000),\n",
       "  'count': 108},\n",
       " '101776.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 13, 10, 1, 17, 901000),\n",
       "  'count': 139},\n",
       " '101777.BKZS': {'start_time': datetime.datetime(2016, 1, 1, 0, 0),\n",
       "  'end_time': datetime.datetime(2025, 6, 4, 20, 0, 0, 2000),\n",
       "  'count': 146},\n",
       " ...}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 下载历史成分股信息\n",
    "xtdata.download_sector_data()\n",
    "\n",
    "xtdata.download_history_data(\"\", \"stocklistchange\", \"\", \"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 查询交易日历\n",
    "days = xtdata.get_trading_calendar(market=\"SZ\", start_time=start_date, end_time=end_date)\n",
    "\n",
    "# 轮询获取指数成本股\n",
    "index_components = {}\n",
    "end_datetime = datetime.strptime(end_date, \"%Y%m%d\")\n",
    "for i in days:\n",
    "    dt = datetime.strptime(i, \"%Y%m%d\")\n",
    "    if dt > end_datetime:\n",
    "        continue\n",
    "\n",
    "    xt_symbols = xtdata.get_stock_list_in_sector(xt_index_symbol, i)\n",
    "\n",
    "    vt_symbols: list = []\n",
    "    for xt_symbol in xt_symbols:\n",
    "        vt_symbol = xt_symbol.replace(\"SH\", \"SSE\").replace(\"SZ\", \"SZSE\")\n",
    "        vt_symbols.append(vt_symbol)\n",
    "\n",
    "    index_components[dt.strftime(\"%Y-%m-%d\")] = vt_symbols\n",
    "\n",
    "# 保存到数据中心\n",
    "lab.save_component_data(index_symbol, index_components)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 加载指数成分股代码\n",
    "component_symbols = lab.load_component_symbols(index_symbol, start_date, end_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████| 854/854 [01:21<00:00, 10.54it/s]\n"
     ]
    }
   ],
   "source": [
    "# 转换时间格式\n",
    "start = datetime.strptime(start_date, \"%Y%m%d\")\n",
    "start.replace(tzinfo=DB_TZ)\n",
    "\n",
    "end = datetime.strptime(end_date, \"%Y%m%d\")\n",
    "end.replace(tzinfo=DB_TZ)\n",
    "\n",
    "# 除了成分股，还要下载指数数据\n",
    "task_symbols = component_symbols + [index_symbol]\n",
    "\n",
    "# 遍历下载数据\n",
    "for vt_symbol in tqdm(task_symbols):\n",
    "    symbol, exchange_str = vt_symbol.split(\".\")\n",
    "\n",
    "    for interval in intervals:\n",
    "        req = HistoryRequest(symbol, Exchange(exchange_str), start, end, interval)\n",
    "        bars = datafeed.query_bar_history(req)\n",
    "\n",
    "        if bars:\n",
    "            lab.save_bar_data(bars)\n",
    "        else:\n",
    "            logger(interval, vt_symbol)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 添加回测参数配置\n",
    "for vt_symbol in component_symbols:\n",
    "    lab.add_contract_setting(\n",
    "        vt_symbol,\n",
    "        long_rate=5/10000,\n",
    "        short_rate=10/10000,\n",
    "        size=1,\n",
    "        pricetick=0.0001,\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.2"
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