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334 lines
12 KiB
Python
334 lines
12 KiB
Python
# This file is part of beets.
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# Copyright 2015-2016, Ohm Patel.
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#
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# Permission is hereby granted, free of charge, to any person obtaining
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# a copy of this software and associated documentation files (the
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# "Software"), to deal in the Software without restriction, including
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# without limitation the rights to use, copy, modify, merge, publish,
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# distribute, sublicense, and/or sell copies of the Software, and to
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# permit persons to whom the Software is furnished to do so, subject to
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# the following conditions:
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#
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# The above copyright notice and this permission notice shall be
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# included in all copies or substantial portions of the Software.
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"""Fetch various AcousticBrainz metadata using MBID.
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"""
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from collections import defaultdict
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import requests
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from beets import plugins, ui
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from beets.dbcore import types
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ACOUSTIC_BASE = "https://acousticbrainz.org/"
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LEVELS = ["/low-level", "/high-level"]
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ABSCHEME = {
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'highlevel': {
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'danceability': {
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'all': {
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'danceable': 'danceable'
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}
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},
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'gender': {
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'value': 'gender'
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},
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'genre_rosamerica': {
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'value': 'genre_rosamerica'
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},
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'mood_acoustic': {
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'all': {
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'acoustic': 'mood_acoustic'
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}
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},
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'mood_aggressive': {
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'all': {
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'aggressive': 'mood_aggressive'
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}
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},
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'mood_electronic': {
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'all': {
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'electronic': 'mood_electronic'
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}
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},
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'mood_happy': {
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'all': {
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'happy': 'mood_happy'
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}
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},
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'mood_party': {
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'all': {
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'party': 'mood_party'
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}
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},
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'mood_relaxed': {
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'all': {
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'relaxed': 'mood_relaxed'
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}
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},
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'mood_sad': {
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'all': {
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'sad': 'mood_sad'
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}
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},
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'moods_mirex': {
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'value': 'moods_mirex'
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},
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'ismir04_rhythm': {
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'value': 'rhythm'
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},
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'tonal_atonal': {
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'all': {
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'tonal': 'tonal'
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}
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},
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'timbre': {
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'value': 'timbre'
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},
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'voice_instrumental': {
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'value': 'voice_instrumental'
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},
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},
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'lowlevel': {
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'average_loudness': 'average_loudness'
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},
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'rhythm': {
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'bpm': 'bpm'
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},
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'tonal': {
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'chords_changes_rate': 'chords_changes_rate',
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'chords_key': 'chords_key',
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'chords_number_rate': 'chords_number_rate',
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'chords_scale': 'chords_scale',
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'key_key': ('initial_key', 0),
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'key_scale': ('initial_key', 1),
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'key_strength': 'key_strength'
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}
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}
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class AcousticPlugin(plugins.BeetsPlugin):
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item_types = {
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'average_loudness': types.Float(6),
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'chords_changes_rate': types.Float(6),
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'chords_key': types.STRING,
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'chords_number_rate': types.Float(6),
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'chords_scale': types.STRING,
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'danceable': types.Float(6),
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'gender': types.STRING,
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'genre_rosamerica': types.STRING,
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'initial_key': types.STRING,
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'key_strength': types.Float(6),
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'mood_acoustic': types.Float(6),
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'mood_aggressive': types.Float(6),
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'mood_electronic': types.Float(6),
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'mood_happy': types.Float(6),
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'mood_party': types.Float(6),
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'mood_relaxed': types.Float(6),
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'mood_sad': types.Float(6),
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'moods_mirex': types.STRING,
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'rhythm': types.Float(6),
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'timbre': types.STRING,
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'tonal': types.Float(6),
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'voice_instrumental': types.STRING,
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}
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def __init__(self):
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super().__init__()
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self.config.add({
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'auto': True,
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'force': False,
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'tags': []
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})
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if self.config['auto']:
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self.register_listener('import_task_files',
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self.import_task_files)
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def commands(self):
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cmd = ui.Subcommand('acousticbrainz',
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help="fetch metadata from AcousticBrainz")
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cmd.parser.add_option(
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'-f', '--force', dest='force_refetch',
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action='store_true', default=False,
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help='re-download data when already present'
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)
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def func(lib, opts, args):
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items = lib.items(ui.decargs(args))
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self._fetch_info(items, ui.should_write(),
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opts.force_refetch or self.config['force'])
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cmd.func = func
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return [cmd]
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def import_task_files(self, session, task):
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"""Function is called upon beet import.
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"""
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self._fetch_info(task.imported_items(), False, True)
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def _get_data(self, mbid):
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data = {}
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for url in _generate_urls(mbid):
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self._log.debug('fetching URL: {}', url)
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try:
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res = requests.get(url)
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except requests.RequestException as exc:
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self._log.info('request error: {}', exc)
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return {}
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if res.status_code == 404:
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self._log.info('recording ID {} not found', mbid)
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return {}
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try:
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data.update(res.json())
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except ValueError:
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self._log.debug('Invalid Response: {}', res.text)
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return {}
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return data
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def _fetch_info(self, items, write, force):
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"""Fetch additional information from AcousticBrainz for the `item`s.
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"""
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tags = self.config['tags'].as_str_seq()
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for item in items:
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# If we're not forcing re-downloading for all tracks, check
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# whether the data is already present. We use one
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# representative field name to check for previously fetched
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# data.
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if not force:
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mood_str = item.get('mood_acoustic', '')
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if mood_str:
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self._log.info('data already present for: {}', item)
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continue
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# We can only fetch data for tracks with MBIDs.
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if not item.mb_trackid:
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continue
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self._log.info('getting data for: {}', item)
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data = self._get_data(item.mb_trackid)
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if data:
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for attr, val in self._map_data_to_scheme(data, ABSCHEME):
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if not tags or attr in tags:
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self._log.debug('attribute {} of {} set to {}',
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attr,
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item,
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val)
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setattr(item, attr, val)
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else:
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self._log.debug('skipping attribute {} of {}'
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' (value {}) due to config',
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attr,
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item,
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val)
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item.store()
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if write:
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item.try_write()
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def _map_data_to_scheme(self, data, scheme):
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"""Given `data` as a structure of nested dictionaries, and `scheme` as a
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structure of nested dictionaries , `yield` tuples `(attr, val)` where
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`attr` and `val` are corresponding leaf nodes in `scheme` and `data`.
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As its name indicates, `scheme` defines how the data is structured,
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so this function tries to find leaf nodes in `data` that correspond
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to the leafs nodes of `scheme`, and not the other way around.
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Leaf nodes of `data` that do not exist in the `scheme` do not matter.
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If a leaf node of `scheme` is not present in `data`,
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no value is yielded for that attribute and a simple warning is issued.
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Finally, to account for attributes of which the value is split between
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several leaf nodes in `data`, leaf nodes of `scheme` can be tuples
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`(attr, order)` where `attr` is the attribute to which the leaf node
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belongs, and `order` is the place at which it should appear in the
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value. The different `value`s belonging to the same `attr` are simply
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joined with `' '`. This is hardcoded and not very flexible, but it gets
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the job done.
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For example:
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>>> scheme = {
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'key1': 'attribute',
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'key group': {
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'subkey1': 'subattribute',
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'subkey2': ('composite attribute', 0)
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},
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'key2': ('composite attribute', 1)
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}
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>>> data = {
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'key1': 'value',
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'key group': {
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'subkey1': 'subvalue',
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'subkey2': 'part 1 of composite attr'
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},
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'key2': 'part 2'
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}
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>>> print(list(_map_data_to_scheme(data, scheme)))
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[('subattribute', 'subvalue'),
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('attribute', 'value'),
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('composite attribute', 'part 1 of composite attr part 2')]
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"""
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# First, we traverse `scheme` and `data`, `yield`ing all the non
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# composites attributes straight away and populating the dictionary
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# `composites` with the composite attributes.
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# When we are finished traversing `scheme`, `composites` should
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# map each composite attribute to an ordered list of the values
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# belonging to the attribute, for example:
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# `composites = {'initial_key': ['B', 'minor']}`.
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# The recursive traversal.
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composites = defaultdict(list)
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yield from self._data_to_scheme_child(data,
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scheme,
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composites)
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# When composites has been populated, yield the composite attributes
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# by joining their parts.
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for composite_attr, value_parts in composites.items():
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yield composite_attr, ' '.join(value_parts)
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def _data_to_scheme_child(self, subdata, subscheme, composites):
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"""The recursive business logic of :meth:`_map_data_to_scheme`:
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Traverse two structures of nested dictionaries in parallel and `yield`
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tuples of corresponding leaf nodes.
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If a leaf node belongs to a composite attribute (is a `tuple`),
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populate `composites` rather than yielding straight away.
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All the child functions for a single traversal share the same
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`composites` instance, which is passed along.
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"""
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for k, v in subscheme.items():
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if k in subdata:
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if type(v) == dict:
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yield from self._data_to_scheme_child(subdata[k],
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v,
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composites)
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elif type(v) == tuple:
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composite_attribute, part_number = v
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attribute_parts = composites[composite_attribute]
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# Parts are not guaranteed to be inserted in order
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while len(attribute_parts) <= part_number:
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attribute_parts.append('')
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attribute_parts[part_number] = subdata[k]
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else:
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yield v, subdata[k]
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else:
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self._log.warning('Acousticbrainz did not provide info'
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'about {}', k)
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self._log.debug('Data {} could not be mapped to scheme {} '
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'because key {} was not found', subdata, v, k)
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def _generate_urls(mbid):
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"""Generates AcousticBrainz end point urls for given `mbid`.
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"""
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for level in LEVELS:
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yield ACOUSTIC_BASE + mbid + level
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