app to download last.fm data How to Grab Music from Last.fm as MP3. Last.fm is a music website that founded in 2002, which contains a great amount of music and allows you to listen to thousands of music on it. However, to enjoy Last.fm music online need network connection, otherwise, you cannot listen to the Last.fm songs at all. In order to solve this issue, you need to download Last.fm music to your computer. In fact, it is not a hard thing to get songs from Last.fm. Now, let's see how to grab music from Last.fm as MP3 in this post. Part 1. The Music Capture You Are Worth to Use. When it comes to get Last.fm music and play them offline, a music recorder for Last.fm is needed. Here the DRmare Last.fm Audio Grabber for Mac is highly recommended, because it is a smart all-round audio recording software. With the advanced technology of audio capturing, the DRmare Music Downloader can detect and record Last.fm songs with high quality and keep ID3 tags. In addition, you can save the Last.fm audio tracks as MP3 or other audio formats. And it can capture several music tracks without interrupting with each other at the same time. After recording, you could edit for the recorded Last.fm audio and trim them into small segments as you want. At the below, we provide the free trial version of DRmare Music Capture for you, you can just click "Download" button to download and install it on your computer. And then follow the tutorial to start to extract Last.fm music and save on your computer. DRmare Music Recorder for Last.fm. Grab songs from Last.fm with high audio quality Catch several audio tracks simultaneous Save recorded Last.fm music as MP3, AAC, etc. Transfer and play Last.fm songs on any other devices. Part 2. How to Record Last.fm Songs with DRmare Music Grabber Program. Part 3. More Details about Last.fm. Last.fm is a little bit different compares to other usual music websites, here we will illustrate the distinction of Last.fm for you. The Last.fm website gives its users to start their own profiles, because it uses a music recommender system called "Scrobble" or "Audioscrobble". It can record the details of the tracks that the users frequently listen to on the database. That is to say, if you are listening to certain songs either from Internet radio stations or on your computer, those songs will be got on the scrobble. Then the Scrobble will send the list of the songs to Last.fm's database and you will get songs recommendations on the basic of the songs you heard before. As for how the information gets to Last.fm database, you could find the answer here. The data is transferred via the music player or the plugin when you are listening to the songs through the Internet radio station or on your computer. Then the information will be displayed on the user's profile that you create on Last.fm. Part 4. The Verdict. Now, with the assistance of DRmare Music Downloader for Last.fm, you can easily grab music from Last.fm as MP3. Then you could listen to Last.fm music offline on any other devices. In addition, the DRmare program can not only capture audio tracks from Last.fm, but also can record music files from websites and music streaming services, such as YouTube Video, Pandora, iHeartRadio, etc. Hope you can enjoy music with this powerful software. If you have any other issue, please feel free to write down at the comment section and we will do our best to help you. The Last.fm Dataset. WARNING: we found matching errors between songs and tracks, you can read about it in this blog post. Last.fm data was matched using songs, so it is likely affected. We have the beginning of a fix, a list of song - track pairs that should not be trusted, get it here. Welcome to the Last.fm dataset , the official song tag and song similarity dataset of the Million Song Dataset. The MSD team is proud to partner with Last.fm in order to bring you the largest research collection of song-level tags and precomputed song-level similarity. All the data is associated with MSD tracks, which makes it easy to link it to other MSD resources: audio features, artist data, lyrics, etc. Some numbers. Before you read the full description, you might want to know that the Last.fm dataset is big. How big? 943,347 matched tracks MSD <-> Last.fm 505,216 tracks with at least one tag 584,897 tracks with at least one similar track 522,366 unique tags 8,598,630 (track - tag) pairs 56,506,688 (track - similar track) pairs. Description. The Last.fm dataset consists of two kinds of data at the song level: tags and similar songs . If you are familiar with the Last.fm API, it corresponds to the track methods 'getTopTags' and 'getSimilar'. Below is a list of the top tags with their total frequencies in the dataset. The graph lets you glance at the total (log) frequencies of the top 200K tags. Below is the list of similar tracks for Kenny Loggins - Footloose (TRRQSYC128F92DF7C8). The first number is a "similarity measure". Note that we have removed duplicates, see this blog entry regarding the duplicates issue in the MSD. We are releasing the data as a set of json-encoded text files. In Python, use simplejson to load the data as a dictionary. The dataset comes in two zipped folders, one for training and one for testing. The split is the same as for artist tags from The Echo Nest. If you're using Last.fm song similarity, please use the same split if possible. Here is what the file TRVABRY128F1476445.json looks like. Keys are artist , title , timestamp , similars and tags . Getting the dataset. Here is the actual data. As is commonly the case, especially for large datasets, it's difficult to find one format that suits everyone's needs. We start by releasing the "raw data" to make sure everyone can access everything. raw data Raw data consist of one JSON file for each track we were able to match to Last.fm. Each JSON object contains a dict with the following keywords artist , title , timestamp , similars and tags . Some files don't have tags, some files don't have similar songs, some don't have either. The artist and title field are the one used to query Last.fm. If you believe there is a mismatch with Echo Nest data, you can check for yourself. Data is split in train / test based on the split for artist-level tags. No data was removed! You can merge the two folders and get the full data. We also provide a subset, corresponding to tracks from the 10K songs in the MSD subset. It's the best way to get acquainted with the data. SUBSET -- TRAIN SET --- TEST SET SQLite databases Because going over JSON files is inefficient, and most people will only work on similarity or tags, we provide two SQLite databases with the data. In each case we also provide demo code that should explain what are the tables and how to get specific information. TAG SQLITE --- TAG SQLITE DEMO SIMILARS SQLITE --- SIMILARS SQLITE DEMO Full list of tags The full list of tags, ordered by frequency (which is also specified). The frequency is simply the number of tracks associated with each tag. We did not sum the count Last.fm provides (an integer between 0 and 100). LIST OF TAGS List of tracks List of tracks with at least one tag, and list of tracks with at least one similar song. TRACKS WITH TAG(S) TRACKS WITH SIMILAR(S) Last.fm API. This dataset was created using the great Last.fm API, using a special key to give us unlimited access. You can recreate, update or complement the dataset using the API, provided you keep strictly to the API Terms of Service. This dataset was solely built using the calls: 'track.search', 'track.getTopTags' and 'track.getSimilar', but many thanks to the Last.fm team who did most of the name matching for us. There are many ways to call the API, we used pylast, slightly modified to better handle illegal XML characters. Can I use this dataset without the rest of the MSD? Sure, every file contains an artist name and song title, that's all you need. If you want to quickly know the metadata for a given track ID in the MSD, use one of the MSD SQLite databases (demo) I find duplicates, why? It's the MSD's fault, it is actually a known problem. When getting the Last.fm data for a set of duplicate tracks, we assigned it to all tracks. We have to do that, we don't know which subset of tracks you might be using. If you want to remove the duplicates, you can use the MSD list of duplicates, or more efficiently look at the artist name / title in the files. If they are the same, it means we got the same info from the Last.fm API, hence a dupe. Why a train and test subset? The goal of the MSD is to promote research. Making research statistically valid requires a train / test split, and making research reproducible requires the split to be the same for everyone. We distribute the dataset already split to make it easy for you. Note that we did not remove any data because of the split! If you put all the test files back in the train folder, you have the complete set. When was the dataset created? Each file has a timestamp in it, but in general between July and September 2011. This explains why you might not get the same data if you call the Last.fm API now, APIs are living things. What is the link between Last.fm and the Million Song Dataset? Last.fm allowed the MSD team to use their API ('getTopTags' and 'getSimilar') to create this dataset. Otherwise, the MSD is not affiliated in any way with Last.fm and vice versa. Many thanks to Last.fm for giving this data to the research community. What is the licensing? Research only, strictly non-commercial. For details, or if you are unsure, please contact Last.fm. Also, Last.fm has the right to advertise and refer to any work derived from the dataset. How to cite the dataset? You should cite this publication [bib]. Additionally, you can mention / link to this web resource: Work using the dataset. This is a list of publications that use this dataset. See also the complete list of MSD publications. If you think your work should be included, send us an email! App to download last.fm data. Simple, robust LastFM API client (for public data) Why this package? The most useful data on LastFM is the public music data. When building an app that incorporates music data from LastFM, lots of functionality provided by the LastFM API isn't necessary – authorizing as a user, liking tracks, adding/removing tags, getting a list of songs in the user's "library", etc. This package only provides the LastFM API methods that use GET requests to fetch data, making it smaller and simpler than the other LastFM libraries. If this matches your use case, consider using this package. Powered by the LastFM API Lightweight library, only provides the GET methods from the Last.fm API. First, get an API key from Last.fm. lastfm = new LastFM(key, [opts]) Create a new LastFM API client with the given public API key . Since all the LastFM calls supported by this module access public data, the secret key is not required. If opts is provided, it can contain the following options: opts.userAgent - String to use as the User-Agent header in http requests opts.minArtistListeners - Exclude artist results with fewer than this number of "listeners" (default: 0 ) opts.minTrackListeners - Exclude track results with fewer than this number of "listeners" (default: 0 ) Note: Unfortunately, there is no opts.minAlbumListeners since the Last.fm API does not include listener numbers in album results (even though the data exists when you get an individual album via lastfm.albumInfo ) These APIs are not part of the LastFM documentation, but they use data from the API and process it into a more useful form. lastfm.search(opts, (err, data) => <>) This returns the "top result" across all result types, prioritizing an exact query match, if one exists. Otherwise, the most popular result by number of "listeners" is used. Exist. We use last.fm music stats in Exist. Far from leaving Spotify, Apple Music, Deezer and other music app users out in the cold, this actually lets us get data from many more apps all in one go. Last.fm can connect to most major music apps, scrobbling (tracking) what you listen to with just a one-time setup. Then you can use Exist to get insights about your music listening habits and how listening to music affects your mood, your sleep patterns and your likelihood to exercise. Here are some of the correlations I have from my last.fm data: Here's how to get your music app connected to last.fm: Set up a last.fm account. If you don't have one already, set up a new last.fm account. When you're all setup, login and go to the scrobbling page on last.fm. Then skip to the instructions for your music app below. iTunes. For your iTunes tracks to scrobble to your last.fm profile, you'll need the last.fm desktop app. Once you've downloaded the app, sign in and open the settings/preferences menu. In here, you'll find a menu option called "Scrobbling" where you can adjust your preferences. The app can also show you stats about your listening habits and your last.fm profile: If you listen to music on an iPod, those tracks will be scrobbled when you sync your iPod with iTunes. Spotify. Spotify has a built-in last.fm app, which you can find in the apps menu on desktop, or in the settings menu on mobile. When you add the last.fm app, you'll need to login to your last.fm account to enable scrobbling. Once you're in, your songs from Spotify will be scrobbled to your last.fm account and will update your stats. You can also see last.fm music recommendations inside Spotify: iPad, iPhone, iPod Touch. On iOS, you can download the last.fm scrobbler app to scrobble tracks to your account. The app lets you play your music library and scrobbles tracks to your account. Unfortunately, you can't scrobble tracks from the standard music player or other music apps like Spotify, as far as I can tell. You'll need to listen via the scrobbler app to make your tracks count. The app is free, though, and includes some extra features like automatic playlists based on artists in your last.fm account and extra details like which artists from your phone's music library are currently on tour. You can also hit a button on the "now playing" screen to make last.fm play similar music to the current song. Android. On Android you can download the last.fm app and scrobble tracks from any music player on most Android phones. The app can also use your phone's GPS to tell you about music events nearby, and in some countries you can access your last.fm personal radio stations as well. Something else. If we haven't included your favourite music app here, don't worry—over 600 apps connect to last.fm. You can find out if yours is one of them on the Does it scrobble? page. Sign up for an Exist account to start tracking and understanding your life. Subscribe Keep up to date with the Exist blog. Delivered to your inbox. Exist is made with by Hello Code in Melbourne, Australia. Copyright 2021. How can I export track.scrobble data from last.fm? What's the best way to export a complete history of my last.fm scrobbles? The data seems to be there on the website so in theory it could be screen scraped if all else fails but is there an easier way? 7 Answers 7. As Backing up Last.FM scrobbles explains you should be able to use the script lastexport.py in LastToLibre. To use it: Run it with the following terminal command: Note that this requires you to have Python installed and that you replace last.fm_user_name with your last.fm user name. Also note that if you got real time stats hidden (under privacy settings) you have to enable it for this to work. You can now find the exported tracks in the same directory as the script. By default it will be named exported_tracks.txt. The script also allows for exporting loved and banned tracks. By default it exports scrobbles but you can change the behavior by setting the flags -t to either loved or banned . If you want to backup loved songs you can use sync_songs . It requires Ruby which can be installed via. on Debian-based systems. The simplest way to install sync_songs is via RubyGems (which can be installed via sudo apt-get install rubygems1.9.1 on Debian-based systems):