果粉有福了！5分钟学会用Python统计自己最爱听的音乐(8)

在③、④和⑤行，指定了前面提到的命令行选项，并输入应该将解析值存入的变量名（args.plFiles、args.plFile和args.plFileD），实际解析在⑥行完成。参数解析后，就将它们传递给相应的函数，findCommonTracks()、plotStats()和findDuplicates()，本章前面讨论过这些函数。
要查看参数是否被解析，就测试args中相应的变量名。例如，如果用户没有使用--common选项（该选项找出播放列表之间的共同音轨），解析后args.plFiles应该设置为None。
在⑦行，处理用户未输入任何参数的情况。
完整代码
下面是完整的程序。你也可以找到本项目的代码和一些测试数据。
import re, argparseimport sysfrom matplotlib import pyplotimport plistlibimport numpy as npdef findCommonTracks(fileNames): """ Find common tracks in given playlist files, and save them to common.txt. """ # a list of sets of track names trackNameSets = [] for fileName in fileNames: # create a new set trackNames = set() # read in playlist plist = plistlib.readPlist(fileName) # get the tracks tracks = plist["Tracks"] # iterate through the tracks for trackId, track in tracks.items(): try: # add the track name to a set trackNames.add(track["Name"]) except: # ignore pass # add to list trackNameSets.append(trackNames) # get the set of common tracks commonTracks = set.intersection(*trackNameSets) # write to file if len(commonTracks) > 0: f = open("common.txt", "w") for val in commonTracks: s = "%s " % val f.write(s.encode("UTF-8")) f.close() print("%d common tracks found. " "Track names written to common.txt." % len(commonTracks)) else: print("No common tracks!") def plotStats(fileName): """ Plot some statistics by reading track information from playlist. """ # read in a playlist plist = plistlib.readPlist(fileName) # get the tracks from the playlist tracks = plist["Tracks"] # create lists of song ratings and track durations ratings = [] durations = [] # iterate through the tracks for trackId, track in tracks.items(): try: ratings.append(track["Album Rating"]) durations.append(track["Total Time"]) except: # ignore pass # ensure that valid data was collected if ratings == [] or durations == []: print("No valid Album Rating/Total Time data in %s." % fileName) 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 findDuplicates(fileName): """ Find duplicate tracks in given playlist. """ print("Finding duplicate tracks in %s..." % fileName) # read in playlist plist = plistlib.readPlist(fileName) # get the tracks from the Tracks dictionary tracks = plist["Tracks"] # create a track name dictionary trackNames = {} # iterate through tracks for trackId, track in tracks.items(): try: name = track["Name"] duration = track["Total Time"] # look for existing entries if name in trackNames: # if a name and duration match, increment the count # round the track length to the nearest second if duration//1000 == trackNames[name][0]//1000: count = trackNames[name][1] trackNames[name] = (duration, count 1) else: # add dictionary entry as tuple (duration, count) trackNames[name] = (duration, 1) except: # ignore pass # store duplicates as (name, count) tuples dups = [] for k, v in trackNames.items(): if v[1] > 1: dups.append((v[1], k)) # save duplicates to a file if len(dups) > 0: print("Found %d duplicates. Track names saved to dup.txt" % len(dups)) else: print("No duplicate tracks found!") f = open("dups.txt", "w") for val in dups: f.write("[%d] %s " % (val[0], val[1])) f.close() # gather our code in a main() function def main(): # create parser descStr = """ This program analyzes playlist files (.xml) exported from iTunes. """ parser = argparse.ArgumentParser(description=descStr) # add a mutually exclusive group of arguments group = parser.add_mutually_exclusive_group() # add expected arguments 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) # parse args args = parser.parse_args() if args.plFiles: # find common tracks findCommonTracks(args.plFiles) elif args.plFile: # plot stats plotStats(args.plFile) elif args.plFileD: # find duplicate tracks findDuplicates(args.plFileD) else: print("These are not the tracks you are looking for.")# main methodif __name__ == "__main__": main()