有哪位能看一下这个解析iTunes播放列表的程序？

import plistlib
import re,argparse
import sys
from matplotlib import pyplot
import numpy as np
def findDuplicates(fileName):
    print(f"在{fileName}中查找重复曲目")
    plist = plistlib.readPlist(fileName)
    tracks = plist['Tracks']
    trackNames = {}
    for trackID,track in tracks.items():
        try:
            name = track['Name']
            duration = track['Total Time']
            if name in trackNames:
                if duration//1000 == trackNames[name][0]//1000:
                    count = trackNames[name] = (duration,count+1)
            else:
                trackNames[name] = (duration,1)
        except:
            pass
    dups = []
    for k,v in trackNames.items():
        if v[1] > 1:
            dups.append((v[1],k))
    if len(dups) > 0:
        print(f"发现{len(dups)}重复。曲目名称保存到dup.txt")
    else:
        print("未找到重复曲目!")
    f = open("dups.txt","w")
    for val in dups:
        f.write(f"[{val[0]}] {val[1]}\n")
    f.close()
def findCommonTracks(fileNames):
    trackNameSets = []
    for filename in fileNames:
        trackNames = set()
        plist = plistlib.readPlist(filename)
        tracks = plist['Tracks']
        for trackID,track in tracks.items():
            try:
                trackNames.add(track['Name'])
            except:
                pass
    trackNameSets.append(trackNames)
    commonTracks = set.intersection(*trackNameSets)
    if len(commonTracks) > 0:
        f = open("common.txt","w")
        for val in commonTracks:
            s = f"{val}\n"
            f.write(s.encode("UTF-8"))
        f.close()
        print(f"{len(commonTracks)}找到常见轨迹"
              "写入common.txt的曲目名称")
    else:
        print("没有公共轨道!")
def plotStats(fileName):
    plist = plistlib.readPlist(fileName)
    tracks = plist['Tracks']
    ratings = []
    durations = []
    for trackID,track in tracks.items():
        try:
            ratings.append(track['Album Rating'])
            durations.append(track['Total Time'])
        except:
            pass
    if ratings == [] or durations == []:
        print(f"{fileName}中没有有效的唱片集评分/总时间数据")
        return
    x = np.array(durations,np.int32)
    x = x/60000.0
    y = np.array(ratings,np.int32)
    pyplot.subplot(2,1,1)
    pyplot.plot(x,y,'o')
    pyplot.axis([0,1.05*np.max(x),-1,110])
    pyplot.xlabel('轨道持续时间')
    pyplot.ylabel('轨道评级')
    pyplot.subplot(2,1,2)
    pyplot.xlabel('轨道持续时间')
    pyplot.ylabel('计数')
    pyplot.show()
def main():
    descStr = """
    此程序分析从iTunes导出的播放列表文件（.xml）
    """
    parser = argparse.ArgumentParser(description=descStr)
    group = parser.add_mutually_exclusive_group()
    group.add_argument('--common',nargs='*',dest='plFiles',required=False)
    group.add_argument('--stats',dest='plFile',required=False)
    group.add_argument('--dup',dest='plFileD',required=False)
    args = parser.parse_args()
    if args.plFiles:
        findCommonTracks(args.plFiles)
    elif args.plFile:
        plotStats(args.plFile)
    elif args.plFileD:
        findDuplicates(args.plFileD)
    else:
        print("这些不是你要找的曲目")
if __name__ == '__main__':
    main()

错误：

Traceback (most recent call last):
  File "/Users/fym/Desktop/*** 编程/playlist.py", line 102, in 
    main()
  File "/Users/fym/Desktop/*** 编程/playlist.py", line 94, in main
    findCommonTracks(args.plFiles)
  File "/Users/fym/Desktop/*** 编程/playlist.py", line 38, in findCommonTracks
    plist = plistlib.readPlist(filename)
AttributeError: module 'plistlib' has no attribute 'readPlist'

该回答引用GPTᴼᴾᴱᴺᴬᴵ,具体如下：

这个问题可能是因为 Python 版本不兼容导致的，因为在 Python 3.9 中，plistlib 模块中的 readPlist 方法已经被重命名为 load 方法。建议你使用 load 方法代替 readPlist 方法，代码如下：

import plistlib
import re,argparse
import sys
from matplotlib import pyplot
import numpy as np

def findDuplicates(fileName):
    print(f"在{fileName}中查找重复曲目")
    plist = plistlib.load(open(fileName, 'rb'))
    tracks = plist['Tracks']
    trackNames = {}
    for trackID,track in tracks.items():
        try:
            name = track['Name']
            duration = track['Total Time']
            if name in trackNames:
                if duration//1000 == trackNames[name][0]//1000:
                    count = trackNames[name] = (duration,count+1)
            else:
                trackNames[name] = (duration,1)
        except:
            pass
    dups = []
    for k,v in trackNames.items():
        if v[1] > 1:
            dups.append((v[1],k))
    if len(dups) > 0:
        print(f"发现{len(dups)}重复。曲目名称保存到dup.txt")
    else:
        print("未找到重复曲目!")
    f = open("dups.txt","w")
    for val in dups:
        f.write(f"[{val[0]}] {val[1]}\n")
    f.close()

def findCommonTracks(fileNames):
    trackNameSets = []
    for filename in fileNames:
        trackNames = set()
        plist = plistlib.load(open(filename, 'rb'))
        tracks = plist['Tracks']
        for trackID,track in tracks.items():
            try:
                trackNames.add(track['Name'])
            except:
                pass
        trackNameSets.append(trackNames)
    commonTracks = set.intersection(*trackNameSets)
    if len(commonTracks) > 0:
        f = open("common.txt","w")
        for val in commonTracks:
            s = f"{val}\n"
            f.write(s.encode("UTF-8"))
        f.close()
        print(f"{len(commonTracks)}找到常见轨迹"
              "写入common.txt的曲目名称")
    else:
        print("没有公共轨道!")

def plotStats(fileName):
    plist = plistlib.load(open(fileName, 'rb'))
    tracks = plist['Tracks']
    ratings = []
    durations = []
    for trackID,track in tracks.items():
        try:
            ratings.append(track['Album Rating'])
            durations.append(track['Total Time'])
        except:
            pass
    if ratings == [] or durations == []:
        print(f"{fileName}中没有有效的唱片集评分/总时间数据")
        return
    x = np.array(durations,np.int32)
    x = x/60000.0
    y = np.array(ratings,np.int32)
    pyplot.subplot(2,1,1)
    pyplot.plot(x,y,'o')
    pyplot.axis([0,1.05*np.max(x),-1,110])
    pyplot.xlabel('轨道持续时间')
    pyplot.ylabel('轨道评级')
    pyplot.subplot(2,1,2)
    pyplot.xlabel('轨道持续时间')
    pyplot.ylabel('计数')
    pyplot.show()

如果以上回答对您有所帮助，望采纳～谢谢