import os,re,difflib,Levenshtein,time,json

# 重要!!! 范围
old_problems_range = "1:50000"
threshold = 0.85

# 待比对的文件
filename = r"C:\Users\weiye\Documents\wwy sync\临时工作区\自拟题目14.tex"

#生成数码列表, 逗号分隔每个区块, 区块内部用:表示整数闭区间
def generate_number_set(string):
    string = re.sub(r"[\n\s]","",string)
    string_list = string.split(",")
    numbers_list = []
    for s in string_list:
        if not ":" in s:
            numbers_list.append(s.zfill(6))
        else:
            start,end = s.split(":")
            for ind in range(int(start),int(end)+1):
                numbers_list.append(str(ind).zfill(6))
    return numbers_list

#字符串预处理
def pre_treating(string):
    string = re.sub(r"\\begin\{center\}[\s\S]*?\\end\{center\}","",string)
    string = re.sub(r"(bracket\{\d+\})|(blank\{\d+\})|(fourch)|(twoch)|(onech)|(mathrm)|(text)","",string)
    string = re.sub(r"[\s\\\{\}\$\(\)\[\]]","",string)
    string = re.sub(r"[\n\t]","",string)
    string = re.sub(r"(displaystyle)|(overrightarrow)","",string)
    string = re.sub(r"[,\.:;?]","",string)
    return string

#difflab字符串比较
def difflab_get_equal_rate(str1, str2):
    return difflib.SequenceMatcher(None, str1, str2).ratio()

#Levenshtein jaro字符串比较
def jaro_get_equal_rate(str1,str2):
    return Levenshtein.jaro(str1,str2)

#Levenshtein 字符串比较
def Lev_get_equal_rate(str1,str2):
    return Levenshtein.ratio(str1,str2)

def GenerateProblemListFromString(problem_string):
    try:
        data = re.findall(r"\\begin\{document\}([\s\S]*?)\\end\{document\}",problem_string)[0]
    except:
        data = problem_string
    data = re.sub(r"\n{2,}","\n",data)
    data = re.sub(r"\\item",r"\\enditem\\item",data)
    data = re.sub(r"\\end\{enumerate\}",r"\\enditem",data)
    ProblemList_raw = [p.strip() for p in re.findall(r"\\item([\s\S]*?)\\enditem",data)]
    ProblemsList = []
    for p in ProblemList_raw:
        startpos = data.index(p)
        tempdata = data[:startpos]
        suflist = re.findall(r"\n\%[\dA-Za-z]+",tempdata)
        if len(suflist) > 0:
            suffix = suflist[-1].replace("%","").strip()
        else:
            suffix = ""
        ProblemsList.append((p,suffix))
    return ProblemsList


#指定对比方法
sim_test = jaro_get_equal_rate

#读入题库
with open(r"../题库0.3/Problems.json","r",encoding = "utf8") as f:
    database = f.read()
pro_dict = json.loads(database)

output = ""

with open(filename,"r",encoding="u8") as f:
    newdatabase = f.read()
new_pro_list = GenerateProblemListFromString(newdatabase)

pro_dict_treated = {}
idrange_raw = generate_number_set(old_problems_range)
idrange = [id for id in pro_dict if id in idrange_raw]
for p in idrange:
    pro_dict_treated[p] = pre_treating(pro_dict[p]["content"])

new_dict_treated = {}
for i in range(len(new_pro_list)):
    new_dict_treated[i+1] = pre_treating(new_pro_list[i][0])

for i in new_dict_treated:
    new_p = new_dict_treated[i]
    maxsim = 0
    for p in pro_dict_treated:
        old_p = pro_dict_treated[p]
        sim = sim_test(new_p,old_p)
        if sim > maxsim:
            maxsim = sim
            argmax = p
    print("%.3f\t%d\t%s" %(maxsim,i,argmax))
    output += ("%.3f\t%d\t%s" %(maxsim,i,argmax)) + "\n"
    # print("\n新题: %s" %new_pro_list[i-1][0])
    # print("\n原题: %s\n\n\n" %pro_dict[]["content"])

with open("临时文件/新题相似相同.txt","w",encoding = "u8") as f:
    f.write(output)