test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df = pd.DataFrame(columns=['link','title','site_name','pagenum',])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "dict_info = pd.Series(dtype='object')\n",
    "dict_info['link'] = 'http://wellan.zuel.edu.cn' \n",
    "dict_info['title'] = 'title'\n",
    "dict_info['site_name'] = 'self.site_name'\n",
    "dict_info['pagenum'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df.shape[0]] = [1,2,3,4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[2]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list_a = []\n",
    "list_a.append(2)\n",
    "list_a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_21612\\4262856688.py:10: FutureWarning: The prefix argument has been deprecated and will be removed in a future version. Use a list comprehension on the column names in the future.\n",
      "\n",
      "\n",
      "  data = pd.read_csv(target_url,header=None,prefix=\"V\")\n"
     ]
    },
    {
     "data": {
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       "        text-align: right;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>V0</th>\n",
       "      <th>V1</th>\n",
       "      <th>V2</th>\n",
       "      <th>V3</th>\n",
       "      <th>V4</th>\n",
       "      <th>V5</th>\n",
       "      <th>V6</th>\n",
       "      <th>V7</th>\n",
       "      <th>V8</th>\n",
       "      <th>V9</th>\n",
       "      <th>...</th>\n",
       "      <th>V51</th>\n",
       "      <th>V52</th>\n",
       "      <th>V53</th>\n",
       "      <th>V54</th>\n",
       "      <th>V55</th>\n",
       "      <th>V56</th>\n",
       "      <th>V57</th>\n",
       "      <th>V58</th>\n",
       "      <th>V59</th>\n",
       "      <th>V60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0200</td>\n",
       "      <td>0.0371</td>\n",
       "      <td>0.0428</td>\n",
       "      <td>0.0207</td>\n",
       "      <td>0.0954</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>0.1601</td>\n",
       "      <td>0.3109</td>\n",
       "      <td>0.2111</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0027</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0159</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0090</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.0453</td>\n",
       "      <td>0.0523</td>\n",
       "      <td>0.0843</td>\n",
       "      <td>0.0689</td>\n",
       "      <td>0.1183</td>\n",
       "      <td>0.2583</td>\n",
       "      <td>0.2156</td>\n",
       "      <td>0.3481</td>\n",
       "      <td>0.3337</td>\n",
       "      <td>0.2872</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>0.0191</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0049</td>\n",
       "      <td>0.0052</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0262</td>\n",
       "      <td>0.0582</td>\n",
       "      <td>0.1099</td>\n",
       "      <td>0.1083</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>0.2431</td>\n",
       "      <td>0.3771</td>\n",
       "      <td>0.5598</td>\n",
       "      <td>0.6194</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0232</td>\n",
       "      <td>0.0166</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>0.0316</td>\n",
       "      <td>0.0164</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>0.0078</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0171</td>\n",
       "      <td>0.0623</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0205</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>0.1098</td>\n",
       "      <td>0.1276</td>\n",
       "      <td>0.0598</td>\n",
       "      <td>0.1264</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0121</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0150</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>0.0073</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>0.0044</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0762</td>\n",
       "      <td>0.0666</td>\n",
       "      <td>0.0481</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>0.0590</td>\n",
       "      <td>0.0649</td>\n",
       "      <td>0.1209</td>\n",
       "      <td>0.2467</td>\n",
       "      <td>0.3564</td>\n",
       "      <td>0.4459</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>0.0054</td>\n",
       "      <td>0.0105</td>\n",
       "      <td>0.0110</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>0.0072</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>0.0107</td>\n",
       "      <td>0.0094</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>0.0187</td>\n",
       "      <td>0.0346</td>\n",
       "      <td>0.0168</td>\n",
       "      <td>0.0177</td>\n",
       "      <td>0.0393</td>\n",
       "      <td>0.1630</td>\n",
       "      <td>0.2028</td>\n",
       "      <td>0.1694</td>\n",
       "      <td>0.2328</td>\n",
       "      <td>0.2684</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0116</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>0.0199</td>\n",
       "      <td>0.0033</td>\n",
       "      <td>0.0101</td>\n",
       "      <td>0.0065</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>0.0193</td>\n",
       "      <td>0.0157</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>0.0323</td>\n",
       "      <td>0.0101</td>\n",
       "      <td>0.0298</td>\n",
       "      <td>0.0564</td>\n",
       "      <td>0.0760</td>\n",
       "      <td>0.0958</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.1018</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>0.2154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0093</td>\n",
       "      <td>0.0135</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0067</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>0.0522</td>\n",
       "      <td>0.0437</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>0.0292</td>\n",
       "      <td>0.0351</td>\n",
       "      <td>0.1171</td>\n",
       "      <td>0.1257</td>\n",
       "      <td>0.1178</td>\n",
       "      <td>0.1258</td>\n",
       "      <td>0.2529</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>0.0029</td>\n",
       "      <td>0.0051</td>\n",
       "      <td>0.0062</td>\n",
       "      <td>0.0089</td>\n",
       "      <td>0.0140</td>\n",
       "      <td>0.0138</td>\n",
       "      <td>0.0077</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>0.0303</td>\n",
       "      <td>0.0353</td>\n",
       "      <td>0.0490</td>\n",
       "      <td>0.0608</td>\n",
       "      <td>0.0167</td>\n",
       "      <td>0.1354</td>\n",
       "      <td>0.1465</td>\n",
       "      <td>0.1123</td>\n",
       "      <td>0.1945</td>\n",
       "      <td>0.2354</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0086</td>\n",
       "      <td>0.0046</td>\n",
       "      <td>0.0126</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0035</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.0079</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0048</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>0.0260</td>\n",
       "      <td>0.0363</td>\n",
       "      <td>0.0136</td>\n",
       "      <td>0.0272</td>\n",
       "      <td>0.0214</td>\n",
       "      <td>0.0338</td>\n",
       "      <td>0.0655</td>\n",
       "      <td>0.1400</td>\n",
       "      <td>0.1843</td>\n",
       "      <td>0.2354</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0146</td>\n",
       "      <td>0.0129</td>\n",
       "      <td>0.0047</td>\n",
       "      <td>0.0039</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0115</td>\n",
       "      <td>M</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>208 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         V0      V1      V2      V3      V4      V5      V6      V7      V8  \\\n",
       "0    0.0200  0.0371  0.0428  0.0207  0.0954  0.0986  0.1539  0.1601  0.3109   \n",
       "1    0.0453  0.0523  0.0843  0.0689  0.1183  0.2583  0.2156  0.3481  0.3337   \n",
       "2    0.0262  0.0582  0.1099  0.1083  0.0974  0.2280  0.2431  0.3771  0.5598   \n",
       "3    0.0100  0.0171  0.0623  0.0205  0.0205  0.0368  0.1098  0.1276  0.0598   \n",
       "4    0.0762  0.0666  0.0481  0.0394  0.0590  0.0649  0.1209  0.2467  0.3564   \n",
       "..      ...     ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "203  0.0187  0.0346  0.0168  0.0177  0.0393  0.1630  0.2028  0.1694  0.2328   \n",
       "204  0.0323  0.0101  0.0298  0.0564  0.0760  0.0958  0.0990  0.1018  0.1030   \n",
       "205  0.0522  0.0437  0.0180  0.0292  0.0351  0.1171  0.1257  0.1178  0.1258   \n",
       "206  0.0303  0.0353  0.0490  0.0608  0.0167  0.1354  0.1465  0.1123  0.1945   \n",
       "207  0.0260  0.0363  0.0136  0.0272  0.0214  0.0338  0.0655  0.1400  0.1843   \n",
       "\n",
       "         V9  ...     V51     V52     V53     V54     V55     V56     V57  \\\n",
       "0    0.2111  ...  0.0027  0.0065  0.0159  0.0072  0.0167  0.0180  0.0084   \n",
       "1    0.2872  ...  0.0084  0.0089  0.0048  0.0094  0.0191  0.0140  0.0049   \n",
       "2    0.6194  ...  0.0232  0.0166  0.0095  0.0180  0.0244  0.0316  0.0164   \n",
       "3    0.1264  ...  0.0121  0.0036  0.0150  0.0085  0.0073  0.0050  0.0044   \n",
       "4    0.4459  ...  0.0031  0.0054  0.0105  0.0110  0.0015  0.0072  0.0048   \n",
       "..      ...  ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "203  0.2684  ...  0.0116  0.0098  0.0199  0.0033  0.0101  0.0065  0.0115   \n",
       "204  0.2154  ...  0.0061  0.0093  0.0135  0.0063  0.0063  0.0034  0.0032   \n",
       "205  0.2529  ...  0.0160  0.0029  0.0051  0.0062  0.0089  0.0140  0.0138   \n",
       "206  0.2354  ...  0.0086  0.0046  0.0126  0.0036  0.0035  0.0034  0.0079   \n",
       "207  0.2354  ...  0.0146  0.0129  0.0047  0.0039  0.0061  0.0040  0.0036   \n",
       "\n",
       "        V58     V59  V60  \n",
       "0    0.0090  0.0032    R  \n",
       "1    0.0052  0.0044    R  \n",
       "2    0.0095  0.0078    R  \n",
       "3    0.0040  0.0117    R  \n",
       "4    0.0107  0.0094    R  \n",
       "..      ...     ...  ...  \n",
       "203  0.0193  0.0157    M  \n",
       "204  0.0062  0.0067    M  \n",
       "205  0.0077  0.0031    M  \n",
       "206  0.0036  0.0048    M  \n",
       "207  0.0061  0.0115    M  \n",
       "\n",
       "[208 rows x 61 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pylab\n",
    "import sys\n",
    "from scipy import stats\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "\n",
    "data = pd.read_csv(target_url,header=None,prefix=\"V\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_21612\\1079493136.py:7: FutureWarning: The prefix argument has been deprecated and will be removed in a future version. Use a list comprehension on the column names in the future.\n",
      "\n",
      "\n",
      "  data = pd.read_csv(target_url,header=None,prefix=\"V\")\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import pylab\n",
    "from scipy import stats\n",
    "\n",
    "#read data from uci data repository\n",
    "target_url = (\"https://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data\")\n",
    "data = pd.read_csv(target_url,header=None,prefix=\"V\")\n",
    "# print(data)\n",
    "\n",
    "# plot\n",
    "stats.probplot(data.V3,dist=\"norm\",plot=pylab,rvalue=True)\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\"./data/urls.csv\",encoding='utf-8-sig')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "310"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re \n",
    "int(re.findall(\"/[1-9][0-9][0-9]\",string=\"共7440条  1/310 \")[0][1:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "共7440条  1/310 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from multiprocessing import cpu_count\n",
    "cpu_count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 1)\n",
      "(2, 2)\n",
      "(3, 3)\n"
     ]
    }
   ],
   "source": [
    "for i in zip([1,2,3],[1,2,3]):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1, '-')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(zip([1,2,3],\"\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1', '1', '1']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[\"1\"]*3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([\"1\"]*3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 1),\n",
       " (1, 1),\n",
       " (2, 1),\n",
       " (3, 1),\n",
       " (4, 1),\n",
       " (5, 1),\n",
       " (6, 1),\n",
       " (7, 1),\n",
       " (8, 1),\n",
       " (9, 1)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from itertools import product\n",
    "list(product(range(10),[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils.crawler import *\n",
    "import pandas as pd\n",
    "df = pd.read_csv(\"./data/urls.csv\",encoding='utf-8-sig')\n",
    "# subCrawl(save_path=\"./data/zuel_news/\",one_df = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['新闻网讯（通讯员 明媛 摄影 杜玥）10月4日下午，校党委中心组围绕习近平总书记在省部级主要领导干部“学习习近平总书记重要讲话精神，迎接党的二十大”专题研讨班上的重要讲话精神、《习近平谈治国理政》第四卷等开展专题学习。校党委书记、理论学习中心组组长栾永玉主持学习，校党委常委、民主党派校领导参加学习，党办、校办以及纪委办公室、监察工作部、党委巡察办公室，党委组织部主要负责人列席学习。与会人员集体学习了习近平总书记在省部级主要领导干部“学习习近平总书记重要讲话精神，迎接党的二十大”专题研讨班上的重要讲话精神。会议指出，习近平总书记的重要讲话系统总结了党的十九大以来的5年发展成就和新时代10年伟大变革，深刻阐明了关系党和国家事业发展的一系列重大理论和实践问题，指明了未来一个时期党和国家事业发展的大政方针和行动纲领，具有重大政治意义、理论意义、实践意义，为我们勇毅前行、团结奋斗，奋力谱写全面建设社会主义现代化国家崭新篇章指明了方向、提供了遵循，为党的二十大召开奠定了重要的思想、政治、理论基础。会议强调，要深刻学习领会习近平总书记重要讲话精神，进一步提高政治判断力、政治领悟力、政治执行力。会上，校党委副书记陈明领学统战工作相关文件，并传达中央统战工作会议精神和湖北省委统战工作会议精神。校党委副书记、纪委书记侯振发领学《习近平谈治国理政》第四卷选篇“在加快推进教育现代化的新征程中培养担当民族复兴大任的时代新人”，并汇报了学习体会。栾永玉在总结讲话中强调，党的二十大召开在即，迎接学习宣传贯彻党的二十大是我们当前和今后一个时期的首要政治任务。要将迎接学习宣传贯彻党的二十大，与学懂弄通做实习近平新时代中国特色社会主义思想相结合，与深学悟透《习近平谈治国理政》第四卷相结合，进一步深刻领悟“两个确立”的决定性意义，进一步增强“四个意识”、坚定“四个自信”、做到“两个维护”，将学习成果不断转化为推动学校“双一流”建设更上新台阶的磅礴力量，以扎实的学习成效和优异的工作成绩迎接党的二十大胜利召开！审核人：覃虹']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parse(url=\"http://wellan.zuel.edu.cn/2022/1005/c1668a308035/page.htm\",headers=one_header)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "res = requests.get(\"http://wellan.zuel.edu.cn/2022/1005/c1668a308035/page.htm\",headers=one_header).content.decode()\n",
    "# bs_onearticle = BeautifulSoup(res,'lxml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\AppData\\Local\\Temp\\ipykernel_14264\\2622355914.py:4: DeprecationWarning: executable_path has been deprecated, please pass in a Service object\n",
      "  newsWeb = webdriver.Firefox(options=web_option,executable_path = './utils/geckodriver.exe')\n"
     ]
    }
   ],
   "source": [
    "from selenium import webdriver\n",
    "from selenium.webdriver.firefox.options import Options\n",
    "web_option = Options()\n",
    "newsWeb = webdriver.Firefox(options=web_option,executable_path = './utils/geckodriver.exe')\n",
    "one_page = newsWeb.get('http://wellan.zuel.edu.cn/2022/1007/c1668a308459/page.htm')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'http://news.hust.edu.cn/info/1003/13647.htm'"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newsWeb.get('http://news.hust.edu.cn/zhxw/1.htm')\n",
    "newsWeb.find_elements(by='css selector',value='span.Article_Title > a')[2].get_attribute('href')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "with open('./data/test.txt',mode='w',encoding='utf-8') as f:\n",
    "    f.write(txt)\n",
    "    f.write(txt)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1002/1831'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = \"http://news.hust.edu.cn/info/1002/1831.htm\"\n",
    "a[29:-4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>link</th>\n",
       "      <th>title</th>\n",
       "      <th>site_name</th>\n",
       "      <th>pagenum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/18313.htm</td>\n",
       "      <td>2006年海峡两岸大学生荆楚文化之旅日前启动</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/18299.htm</td>\n",
       "      <td>教务新闻发布会：抓学风重实践促改革</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/18297.htm</td>\n",
       "      <td>杨叔子院士做客我校“科学精神与实践”讲座</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/18295.htm</td>\n",
       "      <td>校友巴曙松教授回校主讲中国金融业市场转型</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/18294.htm</td>\n",
       "      <td>西门子中国总裁郝睿强受聘我校名誉教授</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7373</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/46474.htm</td>\n",
       "      <td>【70周年校庆·要闻速递】全球合作院校祝福我校70周年华诞</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7374</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/46493.htm</td>\n",
       "      <td>【70周年校庆·要闻速递】国家数字建造技术创新中心第一届理事会第一次会议召开</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7375</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/46492.htm</td>\n",
       "      <td>【70周年校庆·要闻速递】国家智能设计与数控技术创新中心第一届理事会第一次会议召开</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7376</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/46490.htm</td>\n",
       "      <td>湖北省纪委副书记、监委副主任艾军来校调研检查</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7377</th>\n",
       "      <td>http://news.hust.edu.cn/info/1002/46486.htm</td>\n",
       "      <td>【辉煌的十年】学生思政工作：守正创新 培养担当民族复兴大任的时代新人​</td>\n",
       "      <td>华科学校要闻</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>7378 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             link  \\\n",
       "0     http://news.hust.edu.cn/info/1002/18313.htm   \n",
       "1     http://news.hust.edu.cn/info/1002/18299.htm   \n",
       "2     http://news.hust.edu.cn/info/1002/18297.htm   \n",
       "3     http://news.hust.edu.cn/info/1002/18295.htm   \n",
       "4     http://news.hust.edu.cn/info/1002/18294.htm   \n",
       "...                                           ...   \n",
       "7373  http://news.hust.edu.cn/info/1002/46474.htm   \n",
       "7374  http://news.hust.edu.cn/info/1002/46493.htm   \n",
       "7375  http://news.hust.edu.cn/info/1002/46492.htm   \n",
       "7376  http://news.hust.edu.cn/info/1002/46490.htm   \n",
       "7377  http://news.hust.edu.cn/info/1002/46486.htm   \n",
       "\n",
       "                                          title site_name  pagenum  \n",
       "0                        2006年海峡两岸大学生荆楚文化之旅日前启动    华科学校要闻        1  \n",
       "1                             教务新闻发布会：抓学风重实践促改革    华科学校要闻        2  \n",
       "2                          杨叔子院士做客我校“科学精神与实践”讲座    华科学校要闻        2  \n",
       "3                          校友巴曙松教授回校主讲中国金融业市场转型    华科学校要闻        2  \n",
       "4                            西门子中国总裁郝睿强受聘我校名誉教授    华科学校要闻        2  \n",
       "...                                         ...       ...      ...  \n",
       "7373              【70周年校庆·要闻速递】全球合作院校祝福我校70周年华诞    华科学校要闻      311  \n",
       "7374     【70周年校庆·要闻速递】国家数字建造技术创新中心第一届理事会第一次会议召开    华科学校要闻      311  \n",
       "7375  【70周年校庆·要闻速递】国家智能设计与数控技术创新中心第一届理事会第一次会议召开    华科学校要闻      311  \n",
       "7376                     湖北省纪委副书记、监委副主任艾军来校调研检查    华科学校要闻      311  \n",
       "7377       【辉煌的十年】学生思政工作：守正创新 培养担当民族复兴大任的时代新人​     华科学校要闻      311  \n",
       "\n",
       "[7378 rows x 4 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\"./data/husturls-学校要闻.csv\",encoding='utf-8-sig')\n",
    "df['link']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(range(4,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.13"
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 },
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}