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mathdeptv2/工具/目标挂钩简要清点.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"第一单元 . 总题数: 2213 , 完成对应题数: 1401\n",
"第二单元 . 总题数: 3472 , 完成对应题数: 2135\n",
"第三单元 . 总题数: 2426 , 完成对应题数: 395\n",
"第四单元 . 总题数: 1657 , 完成对应题数: 1037\n",
"第五单元 . 总题数: 1590 , 完成对应题数: 307\n",
"第六单元 . 总题数: 1555 , 完成对应题数: 431\n",
"第七单元 . 总题数: 1996 , 完成对应题数: 958\n",
"第八单元 . 总题数: 1526 , 完成对应题数: 525\n",
"第九单元 . 总题数: 473 , 完成对应题数: 101\n",
"暂无对应 . 总题数: 344 , 完成对应题数: 121\n",
"题库总题数: 18795, 已有单元标签题数: 16941, 未赋单元标签题数: 1854.\n",
"未赋标签的题号列表已保存至: 文本文件/题号筛选.txt\n"
]
}
],
"source": [
"import json,os\n",
"\n",
"filename = r\"文本文件/题号筛选.txt\"\n",
"with open(r\"..\\题库0.3\\Problems.json\",\"r\",encoding = \"u8\") as f:\n",
" database = f.read()\n",
"pro_dict = json.loads(database)\n",
"units = [\"第一单元\",\"第二单元\",\"第三单元\",\"第四单元\",\"第五单元\",\"第六单元\",\"第七单元\",\"第八单元\",\"第九单元\",\"暂无对应\"]\n",
"count1 = [0]*10\n",
"count2 = [0]*10\n",
"count3 = 0\n",
"untagged = []\n",
"for id in pro_dict:\n",
" for u in range(10):\n",
" unit = units[u]\n",
" if unit in \"\".join(pro_dict[id][\"tags\"]):\n",
" count1[u] += 1\n",
" if len(pro_dict[id][\"objs\"]) > 0:\n",
" count2[u] += 1\n",
" if len(pro_dict[id][\"tags\"]) == 0:\n",
" count3 += 1\n",
" untagged.append(id)\n",
"for u in range(len(units)):\n",
" print(units[u],\". 总题数:\",count1[u],\", 完成对应题数:\",count2[u])\n",
"print(\"题库总题数: %d, 已有单元标签题数: %d, 未赋单元标签题数: %d.\"%(len(pro_dict),len(pro_dict)-count3,count3))\n",
"with open (filename,\"w\",encoding = \"u8\") as f:\n",
" f.write(\",\".join(untagged))\n",
"print(\"未赋标签的题号列表已保存至: %s\" %(filename))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "mathdept",
"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": "3.9.15"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "ff3c292c316ba85de6f1ad75f19c731e79d694e741b6f515ec18f14996fe48dc"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}