198 lines
11 KiB
Plaintext
198 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": 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: 012613 , 字段: ans 中已有该数据: $\\{2,4\\}$\n",
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"题号: 012614 , 字段: ans 中已有该数据: $(1,2)$\n",
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"题号: 012615 , 字段: ans 中已有该数据: $\\dfrac{\\sqrt{2}}2$\n",
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"题号: 012616 , 字段: ans 中已有该数据: $3$\n",
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"题号: 012617 , 字段: ans 中已有该数据: $3$\n",
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"题号: 012618 , 字段: ans 中已有该数据: \\textcircled{1}\\textcircled{4}\n",
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"题号: 012619 , 字段: ans 中已有该数据: $180$\n",
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"题号: 012620 , 字段: ans 中已有该数据: $4$\n",
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"题号: 012621 , 字段: ans 中已有该数据: $\\dfrac 52$\n",
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"题号: 012622 , 字段: ans 中已有该数据: $\\dfrac\\pi 4$\n",
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"题号: 012623 , 字段: ans 中已有该数据: $\\dfrac{8\\sqrt{2}\\pi}3$\n",
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"题号: 012624 , 字段: ans 中已有该数据: $\\dfrac{8\\sqrt{3}}3$\n",
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"题号: 012625 , 字段: ans 中已有该数据: A\n",
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"题号: 012626 , 字段: ans 中已有该数据: C\n",
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"题号: 012627 , 字段: ans 中已有该数据: D\n",
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"题号: 012628 , 字段: ans 中已有该数据: C\n",
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"题号: 012629 , 字段: ans 中已有该数据: (1) $b_n=3^{n-1}$; (2) $-8$\n",
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"题号: 012630 , 字段: ans 中已有该数据: (1) $\\dfrac \\pi 4$; (2) $1$\n",
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"题号: 012631 , 字段: ans 中已有该数据: (1) 证明略; (2) 证明略; (3) $\\dfrac\\pi 4$\n",
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"题号: 012632 , 字段: ans 中已有该数据: (1) $\\sqrt{2}$; (2) $y=x+1$; (3) 过定点$(-3,0)$和$(1,0)$\n",
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"题号: 012633 , 字段: ans 中已有该数据: (1) $y=x-1$; (2) 单调减区间为$(\\dfrac 12 1)$; 极小值为$-2$; (3) 证明略\n",
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"题号: 012571 , 字段: ans 中已有该数据: $\\{1\\}$\n",
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"题号: 012572 , 字段: ans 中已有该数据: $-1$\n",
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"题号: 012573 , 字段: ans 中已有该数据: $\\dfrac\\pi 6$\n",
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"题号: 012574 , 字段: ans 中已有该数据: $2$\n",
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"题号: 012575 , 字段: ans 中已有该数据: $16\\pi$\n",
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"题号: 012576 , 字段: ans 中已有该数据: $2800$, $31$\n",
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"题号: 012577 , 字段: ans 中已有该数据: $2$\n",
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"题号: 012578 , 字段: ans 中已有该数据: $(-\\infty,1)\\cup (1,3]$\n",
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"题号: 012579 , 字段: ans 中已有该数据: $5$\n",
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"题号: 012580 , 字段: ans 中已有该数据: $[\\dfrac 32,2]$\n",
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"题号: 012581 , 字段: ans 中已有该数据: $(\\dfrac 72,0,\\dfrac 72)$\n",
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"题号: 012582 , 字段: ans 中已有该数据: $\\dfrac{\\sqrt{3}}{20}v$\n",
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"题号: 012583 , 字段: ans 中已有该数据: A\n",
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"题号: 012584 , 字段: ans 中已有该数据: D\n",
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"题号: 012585 , 字段: ans 中已有该数据: C\n",
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"题号: 012586 , 字段: ans 中已有该数据: C\n",
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"题号: 012587 , 字段: ans 中已有该数据: (1) 证明略; (2) $\\dfrac{3\\sqrt{22}}{11}$\n",
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"题号: 012588 , 字段: ans 中已有该数据: (1) $\\dfrac 12$; (2) $a_n=\\dfrac{18}{2n+1}$\n",
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"题号: 012589 , 字段: ans 中已有该数据: (1) 例如: 非通勤时段的车辆使用情况; 油价和电价的变化; 工作单位能否提供免费充电; 电动车的国家减免政策的变化; 车辆的外观、内饰与品牌效应; 车牌费用等; (2) 解答略\n",
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"题号: 012590 , 字段: ans 中已有该数据: (1) $\\dfrac{x^2}4+\\dfrac{y^2}3=1$($y\\le 0$); (2) $P(-\\dfrac 32,\\dfrac{\\sqrt{3}}2)$, $Q(\\dfrac 32, \\dfrac{\\sqrt{3}}2)$; (3) $[\\sqrt{3}-1,\\sqrt{2}+1]$\n",
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"题号: 012591 , 字段: ans 中已有该数据: (1) 导数为$y'=\\dfrac{1-\\ln x}{x^2}$, 单调性证明略; (2) 判断$89^{99}>99^{89}$, 证明略, 推广可以是:``对于实数$a,b$, 若$\\mathrm{e}<a<b$, 则$a^b>b^a$; (3) 证明略\n",
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"题号: 010965 , 字段: ans 中已修改数据: $[0,2]$\n",
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"题号: 010966 , 字段: ans 中已修改数据: $(-\\infty,0)$\n",
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"题号: 030023 , 字段: ans 中已修改数据: $\\dfrac{3n^2-5n}2$\n",
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"题号: 010968 , 字段: ans 中已修改数据: $\\dfrac{8\\pi}3$\n",
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"题号: 010969 , 字段: ans 中已修改数据: $2(x+2)-(y-1)=0$\n",
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"题号: 010970 , 字段: ans 中已修改数据: $\\dfrac 32$\n",
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"题号: 030025 , 字段: ans 中已修改数据: $[0,\\dfrac 34]$\n",
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"题号: 010972 , 字段: ans 中已修改数据: $25$\n",
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"题号: 030024 , 字段: ans 中已修改数据: $\\dfrac 23(\\dfrac 1{4^n}-1)$\n",
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"题号: 010974 , 字段: ans 中已修改数据: $[1,+\\infty)$\n",
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"题号: 010975 , 字段: ans 中已修改数据: $\\sqrt{3}$\n",
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"题号: 010976 , 字段: ans 中已修改数据: $3-\\sqrt{3}$\n",
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"题号: 010977 , 字段: ans 中已修改数据: B\n",
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"题号: 002745 , 字段: ans 中已修改数据: C\n",
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"题号: 010979 , 字段: ans 中已修改数据: C\n",
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"题号: 010980 , 字段: ans 中已修改数据: B\n",
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"题号: 010981 , 字段: ans 中已修改数据: (1) $\\dfrac 23$; (2) $\\arctan {2\\sqrt{5}}5$\n",
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"题号: 010982 , 字段: ans 中已修改数据: (1) $\\log_2 3$; (2) $a=2b\\ne 0$\n",
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"题号: 010983 , 字段: ans 中已修改数据: (1) $\\sqrt{7}$千米; (2) 有$\\dfrac{8-\\sqrt{15}}7$小时, 两人不能通话\n",
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"题号: 010984 , 字段: ans 中已修改数据: (1) $y^2=4\\sqrt{5} x$或$y^2=-4\\sqrt{5} x$; (2) $M$的坐标为$(0,0)$或$(-\\dfrac{4\\sqrt{5}}5,0)$; (3) 证明略\n",
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"题号: 010985 , 字段: ans 中已修改数据: (1) $\\{-6,-3,-2,-1,0,1,2,3,4\\}$; (2) 证明略; (3) 元素个数为$\\dfrac 12 n(n+1)$; 元素之和为$\\dfrac{n+1}2(3^{n+1}-3)$\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()\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": "mathdept",
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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": "ff3c292c316ba85de6f1ad75f19c731e79d694e741b6f515ec18f14996fe48dc"
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"nbformat": 4,
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"nbformat_minor": 2
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}
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