基本信息
源码名称:运维聚类(自然语言处理方法)的问答机器人
源码大小:58.17M
文件格式:.zip
开发语言:Python
更新时间:2021-11-22
   友情提示:(无需注册或充值,赞助后即可获取资源下载链接)

     嘿,亲!知识可是无价之宝呢,但咱这精心整理的资料也耗费了不少心血呀。小小地破费一下,绝对物超所值哦!如有下载和支付问题,请联系我们QQ(微信同号):813200300

本次赞助数额为: 4 元 
   源码介绍

当公司相关人员遇到运维问题时,将问题以文字描述,发送给运维机器人后,可得到相应解决方案,实现常见操作类运维问题自行解决。



"import pandas as pd\n",
    "import re\n",
    "import codecs\n",
    " \n",
    "#将excel转化为txt文件\n",
    "def exceltotxt(excel_dir, txt_dir):  \n",
    "    with codecs.open(txt_dir, 'w', 'utf-8') as f:\n",
    "        neg=pd.read_excel(excel_dir, header=None, index=None)\n",
    "        f.write(neg.to_string())\n",
    " \n",
    "\n",
    " #去除记录行首的数字和空格\n",
    "def del_linehead_number_speace(orig_txt_dir,saveas_txt_dir):\n",
    "    with open(orig_txt_dir,'r ',encoding='UTF-8') as f, open(saveas_txt_dir,'r ',encoding='UTF-8') as fw:\n",
    "        lines = f.readlines()\n",
    "        print(len(lines))   #行数\n",
    "        texts = [re.sub(r'(\\d) (\\s) ','',lines[num]) for num in range(len(lines)) ]\n",
    "        \n",
    "        texts = list(set(texts))  #去重如果要保留重复记录注释该行\n",
    " \n",
    "        line_num = len(texts)\n",
    "#         for num in range(line_num):                 #查看转化后的文本\n",
    "#             print(texts[num])\n",
    "        fw.writelines(texts)\n",
    "    \n",
    "exceltotxt('operation_issues.xlsx', 'operation_temp_issues.txt')    \n",
    "del_linehead_number_speace('operation_temp_issues.txt','operation_issues.txt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Dumping model to file cache C:\\Users\\hu\\AppData\\Local\\Temp\\jieba.cache\n",
      "Loading model cost 0.869 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [