收集使用记录功能已能使用, 可自适应考试卷与平时卷
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@ -1475,5 +1475,138 @@ def ExtractProblemIDs(paperdict,pro_dict):#从备课组材料的每一张讲义
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output.append(id)
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return(output)
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def ParseZipname(zipfilename): #小闲平台的zip文件中获得试卷编号, 返回试卷编号字符串
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xiaoxianpid = re.findall(r"^(\d*?)_",os.path.split(zipfilename)[1])
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return xiaoxianpid[0]
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def FindFile(dir,filename): #在指定目录及子目录下寻找特定文件名的文件, 返回文件所在的路径列表
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pathlist = []
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for path,m,filenames in os.walk(dir):
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if filename in filenames:
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pathlist.append(path)
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return pathlist
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def FindPaper(xiaoxianpid, answersheetpath): #根据小闲的试卷编号和答题纸对应json的根目录寻找题库的试卷编号,届别,题号, 返回(题库试卷编号,届别,题号列表), 如果未找到则返回False
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answersheetpathlist = FindFile(answersheetpath,"答题纸对应.json")
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foundpid = False
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for dir in answersheetpathlist:
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filepath = os.path.join(dir,"答题纸对应.json")
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anssheetjson = load_dict(filepath)
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if xiaoxianpid in anssheetjson:
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foundpid = True
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grade = "20"+re.findall(r"\d{2}届",dir)[0]
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pid = anssheetjson[xiaoxianpid]["id"]
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notesjson = load_dict(os.path.join(dir,"校本材料.json"))
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idlist = []
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for part in anssheetjson[xiaoxianpid]["parts"]:
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idlist += notesjson["notes"][pid][part].copy()
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if "marks" in anssheetjson[xiaoxianpid]:
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marks = anssheetjson[xiaoxianpid]["marks"]
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else:
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marks = []
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break
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if foundpid:
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return(pid,grade,idlist,marks)
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else:
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return False
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def CheckPaperType(filepath,filename): #根据filepath(通常是小闲的zip解压出的目录)和filename(通常是"小题分_按学号（数学）.xlsx")检测试卷类型, 未找到该文件则返回False, 找到文件且是日常试卷返回"日常卷", 找到文件且不是日常试卷返回"考试卷"
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statsfilepathlist = FindFile(filepath,filename)
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if statsfilepathlist == []:
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return False
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else:
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dir = statsfilepathlist[0]
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dfcurrent = pd.read_excel(os.path.join(dir,filename))
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if re.findall(r"第\d*步",str(dfcurrent.loc[1,:])) == []:
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return "日常卷"
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else:
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return "考试卷"
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def generateColIndexandMarks(filepath,statsfilename,paperinfo): #根据filepath(是一个有statsfilename的文件夹列表)中第一个路径中的数据文件, statsfilename数据文件名, 及paperinfo(FindPaper返回的结果)寻找excel文件中有效的列的位置和相应的满分分数
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dir = filepath[0]
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dfcurrent = pd.read_excel(os.path.join(dir,statsfilename))
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validcols = []
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for i in range(len(dfcurrent.columns)):
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colname = str(dfcurrent.iloc[1,i])
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if ("单选" in colname or "填空" in colname or "主观" in colname or "步" in colname) and re.findall("[ABCD]",colname) == []:
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validcols.append(i)
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for col in range(len(validcols)-1,-1,-1):
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colname = str(dfcurrent.iloc[1,validcols[col]])
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if "主观" in colname:
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colname_main = re.findall(r"^([\d\.]*)[\($]",colname[2:])[0]
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t = [dfcurrent.iloc[1,c] for c in validcols[col+1:]]
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t = str(t)
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if colname_main in t:
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validcols.pop(col)
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if paperinfo[3] == []:
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marks = [1] * len(validcols)
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else:
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marks = paperinfo[3]
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if len(marks) == len(validcols):
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return (validcols,marks)
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else:
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return False
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def CheckValidity(classpath,gradename,threshold): #根据文件夹classpath, 年级名gradename和提交比例threshold, 检测提交人数是否不小于threshold, 返回(班级名, 提交是否有效)
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classname_raw = re.findall(r"(高[一二三])(\d*?)班",classpath)[0]
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classname = gradename + classname_raw[0] + classname_raw[1].zfill(2) + "班"
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df = pd.read_excel(os.path.join(os.path.split(classpath)[0],"学科总体分析.xlsx"))
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totalstudents = df.loc[2,df.columns[1]]
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validstudents = df.loc[2,df.columns[2]]
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classvalidflag = False
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if threshold * totalstudents < validstudents:
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print(f"{classname} 有效, 共 {totalstudents} 人, 提交 {validstudents} 人")
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classvalidflag = True
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else:
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print(f"!!! {classname} 无效, 共 {totalstudents} 人, 提交 {validstudents} 人")
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return (classname,classvalidflag)
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def generateIDtoUsageCorrespondence(idlist,validcols,names): #根据idlist(题库ID列表), validcols(有效列位置列表), names(题目名称列表)自动生成一个字典, 键值为题库ID, 内容为该题对应的列位置列表
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corr_dict = {}
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for i in range(len(idlist)):
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ind = i+1
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collist = []
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for j in range(len(validcols)):
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n = names[j]
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if not "步" in n:
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name = re.findall(r"^([^\(]*)",n)[0]
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else:
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name = re.findall(r"^([^第]*)",n)[0]
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if ind == getindex(name):
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collist.append(j)
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corr_dict[idlist[i]] = collist
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return corr_dict
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def CalculateUsages(statsfilepathlist,statsfilename,gradename,threshold,marks,correspondence_dict,validcols,date): #根据统计数据所在的路径,文件名,年级,阈值,分数列表和题号列数(0-len(validcols))对应字典,以及原excel文件中的有效列位置validcols, 日期date, 生成usages的metadata.txt文件的内容, 如果有正确率大于1的则返回False
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output = "ans\n\n\n"
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validflag = True
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for dir in statsfilepathlist:
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classname, valid = CheckValidity(dir,gradename,threshold)
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if valid:
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dfcurrent = pd.read_excel(os.path.join(dir,statsfilename))
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means = dfcurrent.iloc[2:-2,validcols].mean()/marks
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if max(means)>1:
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print("满分数据有误!!!")
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validflag = False
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else:
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means_out = [f"{t:.3f}" for t in means]
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for id in correspondence_dict:
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cols = correspondence_dict[id]
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diffs = "\t".join([means_out[u] for u in cols])
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usages = f"{date}\t{classname}\t{diffs}"
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output += f"{id}\n{usages}\n\n\n"
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if validflag:
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return output
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else:
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return False
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def getindex(string,pos = 2):
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para = string.split(".")
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return int(para[pos-1])
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if __name__ == "__main__":
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print("数据库工具, import用.")
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129
工具v2/收集使用记录.py
129
工具v2/收集使用记录.py
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@ -1,97 +1,16 @@
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"""工程中"""
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zipfilepath = r"D:\temp\222817032234165544977_G20260160选择性必修第四章数列复习_高一_数学.zip"
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# zipfilepath = r"D:\temp\222817041862672707412_控江中学2023学年第一学期高一数学期末考试_高一_数学.zip"
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date = "20240126"
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threshold = 0.75 #设置最低提交人数比例
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from database_tools import *
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import zipfile,shutil
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zipfilepath = r"D:\temp\222817032234165544977_G20260160选择性必修第四章数列复习_高一_数学.zip"
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# zipfilepath = r"D:\temp\222817041862672707412_控江中学2023学年第一学期高一数学期末考试_高一_数学.zip"
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tempdir = "临时文件/zips"
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statsfilename = "小题分_按学号（数学）.xlsx"
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threshold = 0.96 #设置最低提交人数
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answersheetseekingpath = "../备课组"
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def ParseZipname(zipfilename): #小闲平台的zip文件中获得试卷编号, 返回试卷编号字符串
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xiaoxianpid = re.findall(r"^(\d*?)_",os.path.split(zipfilename)[1])
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return xiaoxianpid[0]
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def FindFile(dir,filename): #在指定目录及子目录下寻找特定文件名的文件, 返回文件所在的路径列表
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pathlist = []
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for path,m,filenames in os.walk(dir):
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if filename in filenames:
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pathlist.append(path)
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return pathlist
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def FindPaper(xiaoxianpid, answersheetpath): #根据小闲的试卷编号和答题纸对应json的根目录寻找题库的试卷编号,届别,题号, 返回(题库试卷编号,届别,题号列表), 如果未找到则返回False
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answersheetpathlist = FindFile(answersheetpath,"答题纸对应.json")
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foundpid = False
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for dir in answersheetpathlist:
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filepath = os.path.join(dir,"答题纸对应.json")
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anssheetjson = load_dict(filepath)
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if xiaoxianpid in anssheetjson:
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foundpid = True
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grade = "20"+re.findall(r"\d{2}届",dir)[0]
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pid = anssheetjson[xiaoxianpid]["id"]
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notesjson = load_dict(os.path.join(dir,"校本材料.json"))
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idlist = []
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for part in anssheetjson[xiaoxianpid]["parts"]:
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idlist += notesjson["notes"][pid][part].copy()
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if "marks" in anssheetjson[xiaoxianpid]:
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marks = anssheetjson[xiaoxianpid]["marks"]
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else:
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marks = []
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break
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if foundpid:
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return(pid,grade,idlist,marks)
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else:
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return False
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def CheckPaperType(filepath,filename): #根据filepath(通常是小闲的zip解压出的目录)和filename(通常是"小题分_按学号（数学）.xlsx")检测试卷类型, 未找到该文件则返回False, 找到文件且是日常试卷返回"日常卷", 找到文件且不是日常试卷返回"考试卷"
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statsfilepathlist = FindFile(filepath,filename)
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if statsfilepathlist == []:
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return False
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else:
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dir = statsfilepathlist[0]
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dfcurrent = pd.read_excel(os.path.join(dir,filename))
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if re.findall(r"第\d*步",str(dfcurrent.loc[1,:])) == []:
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return "日常卷"
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else:
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return "考试卷"
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def generateColIndexandMarks(filepath,paperinfo): #根据filepath(是一个有statsfilename的文件夹列表)中第一个路径中的数据文件及paperinfo(FindPaper返回的结果)寻找excel文件中有效的列的位置和相应的满分分数
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dir = filepath[0]
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dfcurrent = pd.read_excel(os.path.join(dir,statsfilename))
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validcols = []
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if papertype == "日常卷":
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for i in range(len(dfcurrent.columns)):
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colname = str(dfcurrent.iloc[1,i])
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if ("单选" in colname or "填空" in colname or "主观" in colname) and re.findall("[ABCD]",colname) == []:
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validcols.append(i)
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marks = [1] * len(validcols)
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elif papertype == "考试卷":
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for i in range(len(dfcurrent.columns)):
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colname = str(dfcurrent.iloc[1,i])
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if ("单选" in colname or "填空" in colname or "主观" in colname or "步" in colname) and re.findall("[ABCD]",colname) == []:
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validcols.append(i)
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for col in range(len(validcols)-1,-1,-1):
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colname = str(dfcurrent.iloc[1,validcols[col]])
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if "主观" in colname:
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colname_main = re.findall(r"^([\d\.]*)[\($]",colname[2:])[0]
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t = [dfcurrent.iloc[1,c] for c in validcols[col+1:]]
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t = str(t)
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if colname_main in t:
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validcols.pop(col)
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if paperinfo[3] == []:
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marks = [1] * len(validcols)
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else:
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marks = paperinfo[3]
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if len(marks) == len(validcols):
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return (validcols,marks)
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else:
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return False
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try:
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@ -100,40 +19,28 @@ try:
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except:
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pass
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xiaoxianpid = ParseZipname(zipfilepath)
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paperinfo = FindPaper(xiaoxianpid, answersheetseekingpath)
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gradename = paperinfo[1]
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idlist = paperinfo[2]
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zf = zipfile.ZipFile(zipfilepath)
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zf.extractall(tempdir) #解压zip文件中的所有内容到tempdir
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papertype = CheckPaperType(tempdir,statsfilename)
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# papertype = CheckPaperType(tempdir,statsfilename)
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statsfilepathlist = FindFile(tempdir,statsfilename)
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validcols,marks = generateColIndexandMarks(statsfilepathlist,statsfilename,paperinfo)
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dfcurrent = pd.read_excel(os.path.join(statsfilepathlist[0],statsfilename))
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correspondence_dict = generateIDtoUsageCorrespondence(idlist,validcols,dfcurrent.iloc[1,validcols])
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output = CalculateUsages(statsfilepathlist,statsfilename,gradename,threshold,marks,correspondence_dict,validcols,date)
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SaveTextFile(output,"文本文件/metadata.txt")
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print("数据文件已输出至metadata.txt")
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validcols,marks = generateColIndexandMarks(statsfilepathlist,paperinfo)
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pass
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# print(ParseZipname(zipfilepath))
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# df = pd.read_excel(os.path.join(os.path.split(dir)[0],"学科总体分析.xlsx"))
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# totalstudents = df.loc[2,df.columns[1]]
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# validstudents = df.loc[2,df.columns[2]]
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# classname = re.findall(r"高[一二三]\d*?班",dir)[0]
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# classvalidflag = False
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# if threshold * totalstudents < validstudents:
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# print(f"{classname} 有效, 共 {totalstudents} 人, 提交 {validstudents} 人")
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# classvalidflag = True
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# else:
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# print(f"!!! {classname} 无效, 共 {totalstudents} 人, 提交 {validstudents} 人")
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# if classvalidflag:
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