beets/beetsplug/lastid.py
Adrian Sampson def0f2c0e5 update lastid plugin for Album/TrackInfo objects
The plugin's deprecated, but there's no reason not to keep it in working order
with the recent changes to the autotagging workflow.
2011-12-06 18:32:27 -08:00

145 lines
5 KiB
Python

# This file is part of beets.
# Copyright 2011, Adrian Sampson.
#
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
"""Adds Last.fm acoustic fingerprinting support to the autotagger.
Requires the pylastfp library.
"""
from __future__ import with_statement
from beets import plugins
from beets.autotag import mb
from beets.autotag import match
from beets.util import plurality
import lastfp
import logging
# The amplification factor for distances calculated from fingerprinted
# data. With this set to 2.0, for instance, "fingerprinted" track titles
# will be considered twice as important as track titles from ID3 tags.
DISTANCE_SCALE = 2.0
log = logging.getLogger('beets')
_match_cache = {}
def last_match(path, metadata=None):
"""Gets the metadata from Last.fm for the indicated track. Returns
a dictionary with these keys: rank, artist, artist_mbid, title,
track_mbid. May return None if fingerprinting or lookup fails.
Caches the result, so multiple calls may be made efficiently.
"""
if path in _match_cache:
return _match_cache[path]
# Actually perform fingerprinting and lookup.
try:
xml = lastfp.gst_match(plugins.LASTFM_KEY, path, metadata)
matches = lastfp.parse_metadata(xml)
except lastfp.FingerprintError:
# Fail silently and cache the failure.
matches = None
top_match = matches[0] if matches else None
_match_cache[path] = top_match
return top_match
def get_cur_artist(items):
"""Given a sequence of items, returns the current artist and
artist ID that is most popular among the fingerprinted metadata
for the tracks.
"""
# Get "fingerprinted" artists for each track.
artists = []
artist_ids = []
for item in items:
last_data = last_match(item.path)
if last_data:
artists.append(last_data['artist'])
if last_data['artist_mbid']:
artist_ids.append(last_data['artist_mbid'])
# Vote on the most popular artist.
artist, _ = plurality(artists)
artist_id, _ = plurality(artist_ids)
return artist, artist_id
class LastIdPlugin(plugins.BeetsPlugin):
def track_distance(self, item, info):
last_data = last_match(item.path)
if not last_data:
# Match failed.
return 0.0, 0.0
dist, dist_max = 0.0, 0.0
# Track title distance.
dist += match.string_dist(last_data['title'],
info.title) \
* match.TRACK_TITLE_WEIGHT
dist_max += match.TRACK_TITLE_WEIGHT
# MusicBrainz track ID.
if last_data['track_mbid']:
# log.debug('Last track ID match: %s/%s' %
# (last_data['track_mbid'], track_data['id']))
if last_data['track_mbid'] != last_data['id']:
dist += match.TRACK_ID_WEIGHT
dist_max += match.TRACK_ID_WEIGHT
# log.debug('Last data: %s; distance: %f' %
# (str(last_data), dist/dist_max if dist_max > 0.0 else 0.0))
return dist * DISTANCE_SCALE, dist_max * DISTANCE_SCALE
def album_distance(self, items, info):
last_artist, last_artist_id = get_cur_artist(
[item for item in items if item]
)
# Compare artist to MusicBrainz metadata.
dist, dist_max = 0.0, 0.0
if last_artist:
dist += match.string_dist(last_artist, info.artist) \
* match.ARTIST_WEIGHT
dist_max += match.ARTIST_WEIGHT
log.debug('Last artist (%s/%s) distance: %f' %
(last_artist, info.artist,
dist/dist_max if dist_max > 0.0 else 0.0))
#fixme: artist MBID currently ignored (as in vanilla tagger)
return dist, dist_max
def candidates(self, items):
last_artist, last_artist_id = get_cur_artist(items)
# Search MusicBrainz based on Last.fm metadata.
cands = list(mb.match_album(last_artist, '', len(items)))
log.debug('Matched last candidates: %s' %
', '.join([cand.album for cand in cands]))
return cands
def item_candidates(self, item):
last_data = last_match(item.path)
if not last_data:
return ()
# Search MusicBrainz.
cands = list(mb.match_track(last_data['artist'],
last_data['track']))
log.debug('Matched last track candidates: %s' %
', '.join([cand.title for cand in cands]))
return cands