Spotipy：如何从播放列表中读取100多首曲目

Question

我正在尝试使用python的Spotipy library来提取某个播放列表中的所有曲目

无论参数限制如何，用户播放列表曲目功能限制为100首曲目。Spotipy文档将其描述为：

user_playlist_tracks(user, playlist_id=None, fields=None, limit=100, offset=0, market=None)

Get full details of the tracks of a playlist owned by a user.

Parameters:

• user
• the id of the user playlist_id
• the id of the playlist fields
• which fields to return limit
• the maximum number of tracks to return offset
• the index of the first track to return market
• an ISO 3166-1 alpha-2 country code.

在使用Spotify进行身份验证后，我目前正在使用类似以下内容：

username = xxxx
playlist = #fromspotipy
sp_playlist = sp.user_playlist_tracks(username, playlist_id=playlist)
tracks = sp_playlist['items']
print tracks

有没有办法返回100多首曲目？我尝试在函数参数中设置limit=None，但它返回了一个错误

Answer 1

我写了一个函数，它可以输出熊猫的数据帧，在那里它可以为超过100首歌曲的播放列表提取所有的元数据（不是所有的，因为我不想这样做，但你可以为此腾出一些空间）。我通过迭代每首歌曲，找到每首歌曲的元数据，将元数据保存到字典中，然后将字典连接到数据帧来实现。它以您的用户名和播放列表ID作为输入

# Function to extract MetaData from a playlist thats longer than 100 songs
def get_playlist_tracks_more_than_100_songs(username, playlist_id):
    results = sp.user_playlist_tracks(username,playlist_id)
    tracks = results['items']
    while results['next']:
        results = sp.next(results)
        tracks.extend(results['items'])
    results = tracks    

    playlist_tracks_id = []
    playlist_tracks_titles = []
    playlist_tracks_artists = []
    playlist_tracks_first_artists = []
    playlist_tracks_first_release_date = []
    playlist_tracks_popularity = []

    for i in range(len(results)):
        print(i) # Counter
        if i == 0:
            playlist_tracks_id = results[i]['track']['id']
            playlist_tracks_titles = results[i]['track']['name']
            playlist_tracks_first_release_date = results[i]['track']['album']['release_date']
            playlist_tracks_popularity = results[i]['track']['popularity']

            artist_list = []
            for artist in results[i]['track']['artists']:
                artist_list= artist['name']
            playlist_tracks_artists = artist_list

            features = sp.audio_features(playlist_tracks_id)
            features_df = pd.DataFrame(data=features, columns=features[0].keys())
            features_df['title'] = playlist_tracks_titles
            features_df['all_artists'] = playlist_tracks_artists
            features_df['popularity'] = playlist_tracks_popularity
            features_df['release_date'] = playlist_tracks_first_release_date
            features_df = features_df[['id', 'title', 'all_artists', 'popularity', 'release_date',
                                       'danceability', 'energy', 'key', 'loudness',
                                       'mode', 'acousticness', 'instrumentalness',
                                       'liveness', 'valence', 'tempo',
                                       'duration_ms', 'time_signature']]
            continue
        else:
            try:
                playlist_tracks_id = results[i]['track']['id']
                playlist_tracks_titles = results[i]['track']['name']
                playlist_tracks_first_release_date = results[i]['track']['album']['release_date']
                playlist_tracks_popularity = results[i]['track']['popularity']
                artist_list = []
                for artist in results[i]['track']['artists']:
                    artist_list= artist['name']
                playlist_tracks_artists = artist_list
                features = sp.audio_features(playlist_tracks_id)
                new_row = {'id':[playlist_tracks_id],
               'title':[playlist_tracks_titles],
               'all_artists':[playlist_tracks_artists],
               'popularity':[playlist_tracks_popularity],
               'release_date':[playlist_tracks_first_release_date],
               'danceability':[features[0]['danceability']],
               'energy':[features[0]['energy']],
               'key':[features[0]['key']],
               'loudness':[features[0]['loudness']],
               'mode':[features[0]['mode']],
               'acousticness':[features[0]['acousticness']],
               'instrumentalness':[features[0]['instrumentalness']],
               'liveness':[features[0]['liveness']],
               'valence':[features[0]['valence']],
               'tempo':[features[0]['tempo']],
               'duration_ms':[features[0]['duration_ms']],
               'time_signature':[features[0]['time_signature']]
               }

                dfs = [features_df, pd.DataFrame(new_row)]
                features_df = pd.concat(dfs, ignore_index = True)
            except:
                continue
                
    return features_df

Answer 2

另一种解决方法是编写for循环并执行以下操作：

offset +=100

然后，您可以在末尾连接轨迹，或者将它们放在数据帧中。 功能参考：

playlist_tracks(playlist_id, fields=None, limit=100, offset=0, market=None)

参考：https://spotipy.readthedocs.io/en/2.7.0/#spotipy.client.Spotify.playlist_tracks

Answer 3

许多spotipy方法返回分页结果，因此您必须滚动浏览它们才能查看的不仅仅是max limit。我在收集播放列表的完整曲目列表时经常遇到这种情况，因此创建了一个自定义方法来处理这种情况：

def get_playlist_tracks(username,playlist_id):
    results = sp.user_playlist_tracks(username,playlist_id)
    tracks = results['items']
    while results['next']:
        results = sp.next(results)
        tracks.extend(results['items'])
    return tracks