diff --git a/工具v2/小闲平台大型考试数据导入.py b/工具v2/小闲平台大型考试数据导入.py
new file mode 100644
index 00000000..fd07aa33
--- /dev/null
+++ b/工具v2/小闲平台大型考试数据导入.py
@@ -0,0 +1,125 @@
+import zipfile,os,re
+import pandas as pd
+from pathlib import Path
+
+
+#设置工作目录, 要求工作目录中恰有一个.txt文件（或.tex文件)和一些.zip文件，其余不论
+# 第一行用"#"开头的作业数据不会被读取
+filepath = r"C:\Users\weiye\Documents\wwy sync\xiaoxian待导入"
+
+#设置届别与接受的比例阈值
+semester = 2023
+# threshold = 0.5 #当班级提交人数超过该比例时数据有效
+
+def getindex(string,pos = 2):
+    para = string.split(".")
+    return int(para[pos-1])
+
+def stringcount(string,list):
+    theitem = ""
+    count = 0
+    for item in list:
+        if string in item:
+            count += 1
+            theitem = item
+    return (count,theitem)
+
+
+shiftdict = {"高一": 3, "高二": 2, "高三": 1}
+patterns = [r"填空([\d\.]+)\((\d+)\)",r"单选([\d\.]+)\((\d+)\)",r"^([\d\.]+)第\d+(步)"]
+
+
+
+#生成文件名tex_file和zip_file
+files = [os.path.join(filepath,f) for f in os.listdir(filepath)]
+tex_file = [f for f in files if ".tex" in f or ".txt" in f][0]
+zip_files = [f for f in files if ".zip" in f]
+
+#分割各次作业数据
+with open(tex_file,"r",encoding = "utf8") as f:
+    tex_data = f.read().strip()
+tex_data = re.sub(r"\t+",r" ",tex_data)
+tex_data = re.sub(r"\n{2,}","---split---",tex_data)
+homeworklist = tex_data.split("---split---")
+
+#读取各次作业首行（文件名）与次行（日期）并组织字典结构
+homeworkdict = {}
+for hwk in homeworklist:
+    hwkdata = hwk.strip().split("\n")
+    id = hwkdata.pop(0).replace(" ","")
+    date = hwkdata.pop(0)
+    if not id.startswith("#"):
+        homeworkdict[id] = {}
+        homeworkdict[id]["date"] = date
+        homeworkdict[id]["usage_data"] = hwkdata
+
+#测试是否每一项都有相应的zip文件与之对应
+execflag = True
+for id in homeworkdict:
+    if stringcount(id,zip_files)[0] == 1:
+        print("zip文件在文件夹中:",id)
+    else:
+        execflag = False
+        print("!!!zip文件个数不对:",id)
+
+if execflag:
+    outputstr = "usages\n\n"
+    for hid in homeworkdict:
+        print("正在处理%s"%id)
+        date = homeworkdict[hid]["date"]
+        #在zip文件中找到包含正确率数据的文件
+        zip_file = os.path.join(filepath,stringcount(hid,zip_files)[1])
+        zf = zipfile.ZipFile(zip_file)
+        # statfiles = [f.filename for f in zf.filelist if "试题分析" in f.filename]
+        handinfiles = [f.filename for f in zf.filelist if "小题分_按学号" in f.filename]
+
+        if "statsfile.xlsx" in os.listdir("临时文件"):
+            os.remove("临时文件/statsfile.xlsx")
+        extractedpath = Path(zf.extract(handinfiles[0]))
+        extractedpath.rename("临时文件/statsfile.xlsx")
+        df = pd.read_excel("临时文件/statsfile.xlsx",skiprows=2)
+        indices = {}
+        for col in df.columns:
+            for pattern in patterns:
+                res = re.findall(pattern,col)
+                if len(res) > 0:
+                    id,mark = res[0]
+                    if not id in indices:
+                        indices[id] = {}
+                    if not "步" in mark:
+                        indices[id][col] = int(mark)
+                    else:
+                        indices[id][col] = int(input(f"{hid}-{col}的满分:"))
+
+        corresp_dict = {}
+        homework = homeworkdict[hid]
+        data = homework["date"]
+        for rawline in homework["usage_data"]:
+            line = re.sub(r"[\t\s]+"," ",rawline)
+            a,b = line.split(" ")
+            if a.strip() in indices:
+                corresp_dict[b.strip()]=indices[a].copy()
+        # print(corresp_dict)
+        for excelfile in handinfiles:
+            if "statsfile.xlsx" in os.listdir("临时文件"):
+                os.remove("临时文件/statsfile.xlsx")
+            extractedpath = Path(zf.extract(excelfile))
+            extractedpath.rename("临时文件/statsfile.xlsx")
+            df = pd.read_excel("临时文件/statsfile.xlsx",skiprows=2)[:-2]
+            gradename = re.findall(r"高[一二三]",excelfile)[0]
+            classname = str(semester+shiftdict[gradename])+"届"+gradename+re.findall(r"高[一二三]([\d]*?)班",excelfile)[0].zfill(2)+"班"
+            for id in corresp_dict:
+                colandmarks = corresp_dict[id]
+                currentstring = f"{id}\n{date}\t{classname}"
+                for col in colandmarks:
+                    mark = colandmarks[col]
+                    diff = df[col].mean()/mark
+                    currentstring += f"\t{diff:.3f}"
+                currentstring += "\n\n"
+                outputstr += currentstring 
+
+    with open("临时文件/自动转换结果.txt","w",encoding = "utf8") as f:
+        f.write(outputstr)
+    with open("文本文件/metadata.txt","w",encoding = "utf8") as f:
+        f.write(outputstr)
+    zf.close()
diff --git a/工具v2/工具面板.py b/工具v2/工具面板.py
index 9cd67d37..7c14d271 100644
--- a/工具v2/工具面板.py
+++ b/工具v2/工具面板.py
@@ -89,6 +89,7 @@ MaintainenceMenu.add_separator()
 MaintainenceMenu.add_command(label = "移除关联题号", command = lambda: SetButton("移除关联题号",["文本文件/metadata.txt"]))
 MaintainenceMenu.add_separator()
 MaintainenceMenu.add_command(label = "小闲平台使用数据导入", command = lambda: SetButton("小闲平台使用数据导入",["小闲平台使用数据导入.py"]))
+MaintainenceMenu.add_command(label = "小闲平台大型考试数据导入", command = lambda: SetButton("小闲平台大型考试数据导入",["小闲平台大型考试数据导入.py"]))
 MaintainenceMenu.add_separator()
 MaintainenceMenu.add_command(label = "分类题号字典生成", command = lambda: SetButton("分类题号字典生成",["分类题号字典生成.py"]))