修正分年级数据导入中的一个日期bug并增加了全卷自动对应题号功能
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@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -10,7 +10,7 @@
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"import pandas as pd\n",
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"from pathlib import Path\n",
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"\n",
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"#设置工作目录, 要求工作目录中恰有一个.tex文件和一个.zip文件,其余不论\n",
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"#设置工作目录, 要求工作目录中恰有一些.tex(.txt)文件和一些.zip文件,对应的文件名需相同, 其余不论\n",
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"filepath = \"数据导入作业文件\"\n",
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"\n",
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"# date = str(time.localtime().tm_year)+str(time.localtime().tm_mon).zfill(2)+str(time.localtime().tm_mday).zfill(2)\n",
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@ -29,6 +29,10 @@
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" #生成文件名tex_file和zip_file\n",
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" zip_file, tex_file = fp\n",
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"\n",
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" newdate = input(os.path.split(zip_file)[-1][:4]+\"使用日期(\"+date+\", 不变按回车, 要变化仅需输入最后几位改变的数字):\")\n",
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" newdate = \"\".join(re.findall(r\"\\d\",newdate))\n",
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" change_len = len(newdate)\n",
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" date = date[:8-change_len]+newdate\n",
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"\n",
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" #获得题号数据,保存在problems_list中\n",
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" with open(tex_file,\"r\",encoding = \"utf8\") as f:\n",
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@ -47,12 +51,20 @@
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" extractedpath.rename(\"临时文件/statsfile.xlsx\")\n",
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" df = pd.read_excel(\"临时文件/statsfile.xlsx\")\n",
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" problems_indexes = list(df[df.columns[0]][2:])\n",
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" autofill = False\n",
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" for p in problems_indexes:\n",
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" t = input(os.path.split(zip_file)[-1][:4]+\"答题纸区域\"+p+\"的题号为(1-\"+str(len(problems_list))+\", a为自动对应点前的题号):\")\n",
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" if not autofill:\n",
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" t = input(os.path.split(zip_file)[-1][:4]+\"答题纸区域\"+p+\"的题号为(1-\"+str(len(problems_list))+\", a为自动对应点前的题号, u为之后完全自动对应):\")\n",
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" if t.upper() == \"A\":\n",
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" correspondence_dict[p] = problems_list[int(re.findall(r\"([\\d]+?)\\.\",p)[0])-1]\n",
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" elif t.upper() == \"U\":\n",
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" correspondence_dict[p] = problems_list[int(re.findall(r\"([\\d]+?)\\.\",p)[0])-1]\n",
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" autofill = True\n",
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" elif not (int(t)<1 or int(t)>len(problems_list)):\n",
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" correspondence_dict[p] = problems_list[int(t)-1]\n",
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" else:\n",
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" correspondence_dict[p] = problems_list[int(re.findall(r\"([\\d]+?)\\.\",p)[0])-1]\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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@ -85,67 +97,6 @@
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"zf.close()\n",
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"\n"
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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": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"''"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"t"
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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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"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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"data": {
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"text/plain": [
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"('数据导入作业文件', 'sj02.zip')"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"os.path.split(zip_file)"
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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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"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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