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('A beets plugin that extracts music descriptors from your audio files',)

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Xtractor (Beets Plugin)

The beets-xtractor plugin lets you, through the use of the Essentia extractors, to obtain low and high level musical information about your songs.

Currently, the following attributes are extracted for each library item: average_loudness, bpm, danceable, gender, genre_rosamerica, voice_instrumental, mood_acoustic, mood_aggressive, mood_electronic, mood_happy, mood_party, mood_relaxed, mood_sad (some more to come soon)


The plugin can be installed via:

$ pip install beets-xtractor

and activated the usual way by adding xtractor to the list of plugins in your configuration:

    - xtractor

Install the Essentia extractors

You will also need the two binary extractors from the Essentia project. They are called:

  • streaming_extractor_music
  • streaming_extractor_music_svm

Unfortunately, only the first extractor is readily available for download whilst to have the second one you will need to compile it yourself. The official installation documentation is somewhat complex but with some cross searching on internet you will make it. If you are stuck you can use the Issue tracker. Make sure you compile with Gaia support (--with-gaia) otherwise your second streaming_extractor_music_svm will not be built.

Download the SVM models

The second extractor uses prebuilt trained models for prediction. You need to download these from here: SVM Models I suggest that you download the more recent beta5 version. This means that your binaries must match this version. Put the downloaded models in any folder from which they can be accessed.


All your configuration will need to go under the xtractor key. This is what your configuration should look like:

    auto: no
    dry-run: no
    write: yes
    threads: 1
    force: no
    quiet: no
    items_per_run: 0
    keep_output: yes
    keep_profiles: no
    output_path: /mnt/data/xtraction_data
    low_level_extractor: /mnt/data/extractors/beta5/streaming_extractor_music
    high_level_extractor: /mnt/data/extractors/beta5/streaming_extractor_music_svm
                - /mnt/data/extractors/beta5/svm_models/danceability.history
                - /mnt/data/extractors/beta5/svm_models/gender.history
                - /mnt/data/extractors/beta5/svm_models/genre_rosamerica.history
                - /mnt/data/extractors/beta5/svm_models/mood_acoustic.history
                - /mnt/data/extractors/beta5/svm_models/mood_aggressive.history
                - /mnt/data/extractors/beta5/svm_models/mood_electronic.history
                - /mnt/data/extractors/beta5/svm_models/mood_happy.history
                - /mnt/data/extractors/beta5/svm_models/mood_party.history
                - /mnt/data/extractors/beta5/svm_models/mood_relaxed.history
                - /mnt/data/extractors/beta5/svm_models/mood_sad.history
                - /mnt/data/extractors/beta5/svm_models/voice_instrumental.history

First of all, you will need adjust all paths. Put the paths of the extractor binaries in low_level_extractorand high_level_extractor, substitute the location of the SVM models with your local path under the svm_models desction. And finally, set the output_path to indicate where the extracted data files will be stored. I you do not set this, a temporary path will be used.

By default both keep_output and keep_profile options are set to no. This means that after extraction (and the storage of the important information) the profile files used to pass to the extractors and the json files created by the extractors will be deleted. There are various reasons you might want to keep these files. One is for debugging purposes. Another is to see what else is in these files (there is a lot) and maybe to use them with some other projects of yours. Lastly, you might want to keep these because the plugin only extracts data if these files are not present. If you store them, on a successive extraction, the plugin will skip the extraction and use these files (they are named by mb_trackid) - speeding up the process a lot.

The items_per_run set to 0 will execute on all items. If you want to limit the number of items per execution (maybe because you want to run a nightly cron job in a limited timeframe) you can use this.

The force option instructs the plugin to execute on items which already have the required properties.

The threads option sets the number of concurrent executions. If you remove this option the number of cores present on your machine will be used. The extraction is quite a CPU intensive process so there might be cases when you want to limit it to just 1.

The write option instructs the plugin to write the extracted attributes to the media file right away. Note that only bpm is actually written to the media file, all the other attributes are flex attributes and are only stored in the database.

The dry-run option shows what would be done without actually doing it.

NOTE: Please note that the auto option is not yet implemented. For now you will have to call the xtractor plugin manually.


Invoke the plugin as:

$ beet xtractor [options] [QUERY...]

For a more verbose reporting use the -v flag on beet:

$ beet -v xtractor [options] [QUERY...]

The plugin has also got a shorthand xt so you can also invoke it like this:

$ beet xt [options] [QUERY...]

The following command line options are available:

--dry-run [-d]: Only show what would be done - displays the extracted values but does not store them in the library.

--write [-w]: Write the values (bpm only) to the media files.

--threads=THREADS [-t THREADS]: The number of concurrently running executions.

--force [-f]: Force the analysis of all items (skip attribute checks).

--count-only [-c]: Show the number of items to be processed and exit. Extraction will not be executed.

--quiet [-q]: Run without any output.

--version [-v]: Display the version number of the plugin. Useful when you need to report some issue and you have to state the version of the plugin you are using.

These command line options will override those specified in the configuration file.


  • If something is not working as expected please use the Issue tracker.
  • If the documentation is not clear please use the Issue tracker.
  • If you have a feature request please use the Issue tracker.
  • In any other situation please use the Issue tracker.

Other plugins by the same author


Essentia is an open-source C++ library with Python bindings for audio analysis and audio-based music information retrieval. It is released under the Affero GPLv3 license and is also available under proprietary license upon request. This plugin is just a mere wrapper around this library. Learn more about the Essentia project


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