{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import streamlit as st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main():\n",
    "    st.title(\"科研代码分析应用\")\n",
    "    uploaded_file = st.file_uploader(\"\", type=[\"py\"])\n",
    "\n",
    "    if uploaded_file is not None:\n",
    "        # 读取代码文件内容\n",
    "        code_content = uploaded_file.read()\n",
    "\n",
    "        # 在这里添加你的代码分析功能，例如解析、可视化等\n",
    "\n",
    "        # 显示代码内容\n",
    "        st.code(code_content, language=\"python\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-02-19 09:17:25.437 \n",
      "  \u001b[33m\u001b[1mWarning:\u001b[0m to view this Streamlit app on a browser, run it with the following\n",
      "  command:\n",
      "\n",
      "    streamlit run /data/home/wudezhi/anaconda3/envs/mlfold/lib/python3.8/site-packages/ipykernel_launcher.py [ARGUMENTS]\n"
     ]
    }
   ],
   "source": [
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "mlfold",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}