import os,re,json # filename = "临时文件/相似题目.txt" filename = "临时文件/相似1.txt" # 读取题库数据并转换为字典 with open(r"../题库0.3/Problems.json","r",encoding = "utf8") as f: database = f.read() pro_dict = json.loads(database) # 读取已分类的相似文件列表 with open(filename,"r",encoding = "utf8") as f: similar_text = "\n"+f.read() similar_types = re.findall(r"\n[\d]\.[\d]{4}[\s]*([srSRnN])*[\s]*\n",similar_text) similar_problems = re.findall(r"\n([\d]{6})\s",similar_text) print(similar_types) print(similar_problems) samecount ,relcount, unrelcount = 0,0,0 if len(similar_types) * 2 == len(similar_problems): for i in similar_types: id1 = similar_problems.pop(0) id2 = similar_problems.pop(0) if i.upper() == "S": if not id2 in pro_dict[id1]["same"]: pro_dict[id1]["same"].append(id2) samecount += 1 print("相同题目已标注: %s <- %s"%(id1,id2)) if not id1 in pro_dict[id2]["same"]: pro_dict[id2]["same"].append(id1) samecount += 1 print("相同题目已标注: %s <- %s"%(id2,id1)) elif i.upper() == "R": if not id2 in pro_dict[id1]["related"]: pro_dict[id1]["related"].append(id2) relcount += 1 print("关联题目已标注: %s <- %s"%(id1,id2)) if not id1 in pro_dict[id2]["related"]: pro_dict[id2]["related"].append(id1) relcount += 1 print("关联题目已标注: %s <- %s"%(id2,id1)) elif i.upper() == "N": if not id2 in pro_dict[id1]["unrelated"]: pro_dict[id1]["unrelated"].append(id2) unrelcount += 1 print("无关题目已标注: %s <- %s"%(id1,id2)) if not id1 in pro_dict[id2]["unrelated"]: pro_dict[id2]["unrelated"].append(id1) unrelcount += 1 print("无关题目已标注: %s <- %s"%(id2,id1)) else: print("相似程度数据:",len(similar_types),"个, 相似题目:",len(similar_problems),"题. 数据有问题, 请检查.") print("已标注相同题目 %d 项, 关联题目 %d 项, 无关题目 %d 项"%(samecount,relcount,unrelcount)) # 将题库字典转换为json文件并保存至原位 database = json.dumps(pro_dict,indent=4,ensure_ascii=False) with open(r"../题库0.3/Problems.json","w",encoding = "utf8") as f: f.write(database)