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Python练习：读取Apple Plist文件

Plist文件简介

1. ​​定义​​：Apple公司创建的基于XML结构的文件格式
2. ​​特点​​：采用XML语法组织数据，可存储键值对、数组等结构化信息
3. 文件扩展名​​：.plist
4. 应用场景:
   ​​iOS系统:​​ 应用描述文件（权限配置：蓝牙/网络访问/GameCenter等）IPA安装包中的配置信息 ​​
   macOS系统​​: .app应用的配置文件 系统偏好设置存储 ​​
   苹果生态​​ iTunes音乐播放列表 Xcode项目配置

Python操作库：plistlib

import plistlib

代码适配指南（Python 2 → Python 3）
​​废弃方法​​（Python 2旧版）

plist = plistlib.read(filename)

​​正确方法​​（Python 3新版）

with open(filename, 'rb') as plist_file:plist = plistlib.load(plist_file)

注意事项

1. 始终使用​​二进制模式​​（‘rb’）打开文件 Python
2. 3.4+ 支持load()/dump()替代旧版API
3. macOS内置plutil工具可验证文件有效性：bash 下运行下面的代码
   plutil -lint Example.plist

下文是练习代码，其中也包含了画图部分
练习代码：

import re, argparse
import sys
from matplotlib import pyplot
import plistlib
import numpy as np# 找到重复的音乐
def find_duplicates(file_name):print("Find duplicate tracks in %s..." % file_name)with open(file_name, 'rb') as f:plist = plistlib.load(f)# 读取playlist# 获取音轨目录tracks = plist['Tracks']# 创建音轨字典track_names = {}# 结构：{name:(duration,count)}# 遍历 添加for track_id, track in tracks.items():try:name = track['name']duration = track['Total Time']# 检查是不是以及在在字典里面了if name in track_names:# 匹配 歌曲名称和时长if duration // 1000 == track_names['name'][0] // 1000:count = track_names[name][1]track_names[name] = (duration, count + 1)else:# 不匹配的情况下track_names[name] = (duration, count)except:# ignorepass# 保存重复的音轨， name, countdups = []for k, v in track_names.items():if v[1] > 1:dups.append(k, v[1])# 保存到一个文件if len(dups) > 0:print("发现一共有%d个重复的文件， 以及保存到了dup.txt中" % len(dups))else:print("没有发现任何重复的文件")f = open("dups.txt", "w")for val in dups:f.writable("[%d] %s \n" % (val[0], val[1]))f.close()# 查找多个播放列表中的共同的音轨
def find_common_tracks(file_names):# a list of sets of track namestrack_name_sets = []# 遍历读取多个plist文件for file_name in file_names:track_names = set()with open(file_name, 'rb') as f:plist = plistlib.load(f)# 获取音轨节点tracks = plist.get("Tracks", {})# 遍历迭代for track_id, track in tracks.items():try:track_names.add(track['Name'])except:# ignorepass# 添加到track_name_sets中track_name_sets.append(track_names)# 交集处理common_tracks = set.intersection(*track_name_sets)# 写文件if len(common_tracks) > 0:f = open("common.txt", "w")for val in common_tracks:# s = "%s\n" % valf.write(f"{val}\n")f.close()print(f"Track names wirte to common.txt { len(common_tracks)}")else:print("No common tracks!")# 收集歌曲评分和时长
def plot_stats(file_name):# 读取播放列表with open(file_name, 'rb') as f:plist = plistlib.load(f)tracks = plist['Tracks']# 创建音轨排序和时长ratings = []durations = []for track_id, track in tracks.items():try:ratings.append(track['Album Rating'])durations.append(track['Total Time'])except:# ignorepass# 确保是有效数据if ratings == [] or durations == []:print(f"在文件中%s没有有效的Album Rating/Total Time  数据 {file_name}")return# scatter plot x= np.array(durations, np.int32) # convert to minutes 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('Track duration') pyplot.ylabel('Track rating') # plot histogram pyplot.subplot(2, 1, 2) pyplot.hist(x, bins=20) pyplot.xlabel('Track duration') pyplot.ylabel('Count') # show plot pyplot.show() def main():# create parserdescStr = """This program analyzes playlist files (.xml) exported from iTunes."""parser = argparse.ArgumentParser(description=descStr)# add a mutually exclusive group of argumentsgroup = parser.add_mutually_exclusive_group()# add expected argumentsgroup.add_argument('--common', nargs = '*', dest='plFiles', required=False)group.add_argument('--stats', dest='plFile', required=False)group.add_argument('--dup', dest='plFileD', required=False)# parse argsargs = parser.parse_args()if args.plFiles:# find common tracksfind_common_tracks(args.plFiles)elif args.plFile:# plot statsplot_stats(args.plFile)elif args.plFileD:# find duplicate tracksfind_duplicates(args.plFileD)else:print("These are not the tracks you are looking for.")if __name__ == "__main__":main()

最后这个是画图的部分，以后有兴趣再研究吧