226 lines
14 KiB
Plaintext
226 lines
14 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.948\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.861\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.767\t0.907\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.930\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.791\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.954\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.930\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.500\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.756\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.919\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.954\t0.895\t0.965\t0.802\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.954\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一11班\t0.733\t0.779\n",
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.943\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.932\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.795\t0.932\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.864\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.795\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.864\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t1.000\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.500\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.864\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.852\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t1.000\t0.898\t0.955\t0.693\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.909\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一12班\t0.705\t0.886\n",
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.866\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.829\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.780\t0.902\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.780\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.805\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.805\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.878\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.537\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.768\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.756\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.915\t0.829\t0.805\t0.695\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.793\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一01班\t0.720\t0.720\n",
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.963\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.927\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.805\t0.902\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.854\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.805\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.976\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.951\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.329\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.720\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.695\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.902\t0.842\t0.927\t0.683\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.780\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一02班\t0.658\t0.707\n",
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.942\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.846\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.692\t0.923\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.897\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.872\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.846\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.897\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.474\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.795\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.821\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.974\t0.936\t0.897\t0.692\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.872\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一06班\t0.795\t0.654\n",
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.934\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.842\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.789\t0.974\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.816\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.895\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.868\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.974\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.461\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.724\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.789\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.882\t0.842\t0.868\t0.526\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.776\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一08班\t0.632\t0.684\n",
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"题号: 021469 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.945\n",
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"题号: 021470 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.732\n",
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"题号: 021471 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.707\t0.976\n",
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"题号: 021472 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.951\n",
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"题号: 021473 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.854\n",
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"题号: 021474 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.854\n",
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"题号: 021475 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.951\n",
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"题号: 021476 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.598\n",
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"题号: 021477 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.756\n",
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"题号: 021478 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.756\n",
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"题号: 021479 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t1.000\t0.878\t0.976\t0.622\n",
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"题号: 021480 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.768\n",
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"题号: 021481 , 字段: usages 中已添加数据: 20230217\t2025届高一09班\t0.768\t0.768\n"
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]
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}
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],
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"source": [
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"import os,re,json\n",
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"\n",
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"\"\"\"---明确数据文件位置---\"\"\"\n",
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"datafile = \"文本文件/metadata.txt\"\n",
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"# 双回车分隔，记录内单回车分隔列表，首行为字段名\n",
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"\"\"\"---文件位置结束---\"\"\"\n",
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"\n",
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"def trim(string):\n",
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" string = re.sub(r\"^[ \\t\\n]*\",\"\",string)\n",
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" string = re.sub(r\"[ \\t\\n]*$\",\"\",string)\n",
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" return string\n",
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"def FloatToInt(string):\n",
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" f = float(string)\n",
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" if abs(f-round(f))<0.01:\n",
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" f = round(f)\n",
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" return f\n",
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"\n",
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"with open(datafile,\"r\",encoding=\"utf8\") as f:\n",
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" data = f.read().strip()\n",
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"pos = data.index(\"\\n\")\n",
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"field = data[:pos].strip()\n",
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"appending_data = data[pos:]\n",
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"\n",
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"with open(r\"../题库0.3/Problems.json\",\"r\",encoding = \"utf8\") as f:\n",
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" database = f.read()\n",
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"pro_dict = json.loads(database)\n",
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"with open(r\"../题库0.3/LessonObj.json\",\"r\",encoding = \"utf8\") as f:\n",
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" database = f.read()\n",
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"obj_dict = json.loads(database)\n",
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"\n",
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"#该字段列表可能需要更新\n",
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"fields = [\"content\",\"objs\",\"tags\",\"genre\",\"ans\",\"solution\",\"duration\",\"usages\",\"origin\",\"edit\",\"same\",\"related\",\"remark\",\"space\"]\n",
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"\n",
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"if field in fields:\n",
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" field_type = type(pro_dict[\"000001\"][field])\n",
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" datalist = [record.strip() for record in appending_data.split(\"\\n\\n\") if len(trim(record)) > 0]\n",
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" for record in datalist:\n",
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" id = re.findall(r\"^[\\d]{1,}\",record)[0]\n",
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" data = record[len(id):].strip()\n",
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" id = id.zfill(6)\n",
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" if not id in pro_dict:\n",
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" print(\"题号:\",id,\"不在数据库中.\")\n",
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" break\n",
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" \n",
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" #字符串类型字段添加数据\n",
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" elif field_type == str and data in pro_dict[id][field]:\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已有该数据:\",data)\n",
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" elif field_type == str and not data in pro_dict[id][field] and not field == \"ans\" and not field == \"space\":\n",
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" origin_data = pro_dict[id][field]\n",
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" new_data = trim(origin_data + \"\\n\" + data)\n",
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" pro_dict[id][field] = new_data\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已添加数据:\",data)\n",
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" elif field_type == str and not data in pro_dict[id][field] and field == \"ans\" or field == \"space\":\n",
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" pro_dict[id][field] = data\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已修改数据:\",data)\n",
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" \n",
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" #数值类型字段添加数据\n",
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" elif (field_type == int or field_type == float) and abs(float(data) - pro_dict[id][field])<0.01:\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已有该数据:\",FloatToInt(data))\n",
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" elif (field_type == int or field_type == float) and abs(float(data) - pro_dict[id][field])>=0.01:\n",
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" pro_dict[id][field] = FloatToInt(data)\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已修改数据:\",FloatToInt(data))\n",
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" \n",
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" #列表类型字段添加数据\n",
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" elif field_type == list:\n",
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" cell_data_list = [d.strip() for d in data.split(\"\\n\")]\n",
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" for cell_data in cell_data_list:\n",
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" if cell_data in pro_dict[id][field]:\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已有该数据:\",cell_data)\n",
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" elif not field == \"objs\":\n",
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" pro_dict[id][field].append(cell_data)\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已添加数据:\",cell_data)\n",
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" else:\n",
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" if not cell_data in obj_dict and not cell_data.upper() == \"KNONE\":\n",
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" print(\"题号:\",id,\", 字段:\",field,\"目标编号有误:\",cell_data)\n",
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" else:\n",
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" pro_dict[id][field].append(cell_data.upper())\n",
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" print(\"题号:\",id,\", 字段:\",field,\"中已添加数据:\",cell_data.upper())\n",
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"\n",
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"with open(r\"../题库0.3/Problems.json\",\"w\",encoding = \"utf8\") as f:\n",
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" f.write(json.dumps(pro_dict,indent=4,ensure_ascii=False))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "pythontest",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.15"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "91219a98e0e9be72efb992f647fe78b593124968b75db0b865552d6787c8db93"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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