145 lines
5.1 KiB
Plaintext
145 lines
5.1 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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"source": [
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"import os,re,json,time\n",
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"\n",
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"\"\"\"---设置原题目id与新题目id列表, 新id的数目不能小于旧id的数目---\"\"\"\n",
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"old_ids = \"603,604\"\n",
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"new_ids = \"50000:60000\"\n",
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"\"\"\"---设置完毕---\"\"\"\n",
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"\"\"\"---完成编辑后记得运行第二个单元格---\"\"\"\n",
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"\n",
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"# 题号转换\n",
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"def generate_number_set(string,dict):\n",
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" string = re.sub(r\"[\\n\\s]\",\"\",string)\n",
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" string_list = string.split(\",\")\n",
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" numbers_list = []\n",
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" for s in string_list:\n",
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" if not \":\" in s:\n",
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" numbers_list.append(s.zfill(6))\n",
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" else:\n",
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" start,end = s.split(\":\")\n",
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" for ind in range(int(start),int(end)+1):\n",
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" numbers_list.append(str(ind).zfill(6))\n",
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" return numbers_list\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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"\n",
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"old_id_list = generate_number_set(old_ids,pro_dict)\n",
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"new_id_list = generate_number_set(new_ids,pro_dict)\n",
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"\n",
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"\n",
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"\n",
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"\n",
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"#判断是否有已占用的题号\n",
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"occupied_flag = False\n",
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"for new_id in new_id_list:\n",
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" if new_id in pro_dict:\n",
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" print(\"ID\",new_id,\"已被使用.\")\n",
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" occupied_flag = True\n",
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"\n",
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"length_old = len(old_id_list)\n",
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"length_new = len(new_id_list)\n",
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"if length_old > length_new:\n",
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" print(\"新ID的个数不够\")\n",
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"\n",
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"\n",
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"# 将未修订的题目添加入数据库, 并作好关联\n",
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"used_new_id_list = []\n",
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"if not occupied_flag and length_new >= length_old:\n",
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" for pos in range(length_old):\n",
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" old_id = old_id_list[pos]\n",
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" new_id = new_id_list[pos]\n",
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" used_new_id_list.append(new_id)\n",
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" pro_dict[new_id] = {}\n",
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" for field in pro_dict[old_id]:\n",
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" if not field == \"id\":\n",
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" pro_dict[new_id][field] = pro_dict[old_id][field] if not type(pro_dict[old_id][field]) == list else pro_dict[old_id][field].copy()\n",
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" else:\n",
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" pro_dict[new_id][field] = new_id\n",
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" pro_dict[new_id][\"related\"].append(old_id)\n",
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" pro_dict[new_id][\"same\"] = []\n",
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" pro_dict[new_id][\"objs\"] = pro_dict[old_id][\"objs\"].copy()\n",
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" pro_dict[new_id][\"usages\"] = []\n",
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" pro_dict[new_id][\"edit\"].append(str(time.localtime().tm_year)+str(time.localtime().tm_mon).zfill(2)+str(time.localtime().tm_mday).zfill(2) + \"\\t\")\n",
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" pro_dict[old_id][\"related\"].append(new_id)\n",
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" pro_dict[new_id][\"origin\"] += \"-\" + str(time.localtime().tm_year)+str(time.localtime().tm_mon).zfill(2)+str(time.localtime().tm_mday).zfill(2) + \"修改\"\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))\n",
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" output_list = {}\n",
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" for id in used_new_id_list:\n",
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" output_list[id] = pro_dict[id].copy()\n",
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"\n",
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" with open(r\"临时文件/problem_edit.json\",\"w\",encoding=\"u8\") as f:\n",
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" f.write(json.dumps(output_list,indent = 4,ensure_ascii=False))\n",
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" os.system(r\"code -g 临时文件/problem_edit.json\")"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"\"\"\"编辑完成保存关闭后运行这个代码块\"\"\"\n",
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"with open(r\"临时文件/problem_edit.json\",\"r\",encoding=\"u8\") as f:\n",
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" datanew = f.read()\n",
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"new_pro = json.loads(datanew)\n",
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"for id in new_pro:\n",
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" pro_dict[id] = new_pro[id].copy()\n",
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"\n",
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"#按id排序生成字典\n",
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"sorted_dict_id = sorted(pro_dict)\n",
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"sorted_dict = {}\n",
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"for id in sorted_dict_id:\n",
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" sorted_dict[id] = pro_dict[id]\n",
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"#将排序后的字典转为json\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(sorted_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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