219 lines
11 KiB
Plaintext
219 lines
11 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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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: 004548 , 字段: objs 中已添加数据: K0309001B\n",
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"题号: 003092 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 003094 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 003101 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 003102 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006100 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006115 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006116 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006117 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006120 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006123 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006125 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006126 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006128 , 字段: objs 中已添加数据: K0309003B\n",
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"题号: 006138 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006145 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003095 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003096 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003097 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003098 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003099 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003100 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003103 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003104 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003105 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003107 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003108 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006101 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006104 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006124 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006129 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006146 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006147 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006148 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006149 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006152 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006153 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006154 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006155 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006156 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006157 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006158 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006159 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006162 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006163 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006164 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006165 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006166 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006167 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006168 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006169 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006170 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006171 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006172 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006173 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006174 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006175 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006176 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006191 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006232 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 006257 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 008176 , 字段: objs 中已添加数据: K0310002B\n",
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"题号: 003093 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 004681 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 005086 , 字段: objs 中已有该数据: K0311002B\n",
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"题号: 006177 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 008169 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 008170 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 010251 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 009572 , 字段: objs 中已添加数据: K0311002B\n",
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"题号: 003112 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003113 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003114 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003115 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003117 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003125 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003126 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 003127 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 006190 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 006214 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 008385 , 字段: objs 中已添加数据: K0312003B\n",
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"题号: 008168 , 字段: objs 中已添加数据: K0313002B\n",
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"题号: 006286 , 字段: objs 中已添加数据: K0313003B\n",
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"题号: 006288 , 字段: objs 中已添加数据: K0313003B\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 = \"临时文件/关联目标.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()\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\":\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\":\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": "Python 3.8.8 ('base')",
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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": "3.8.8"
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"nbformat": 4,
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