def tag_item(item,
timid=False,
search_artist=None,
search_title=None,
search_id=None):
"""Attempts to find metadata for a single track. Returns a
`(candidates, recommendation)` pair where `candidates` is a list of
TrackMatch objects. `search_artist` and `search_title` may be used
to override the current metadata for the purposes of the MusicBrainz
title; likewise `search_id`.
"""
# Holds candidates found so far: keys are MBIDs; values are
# (distance, TrackInfo) pairs.
candidates = {}
# First, try matching by MusicBrainz ID.
trackid = search_id or item.mb_trackid
if trackid:
log.debug('Searching for track ID: ' + trackid)
track_info = hooks._track_for_id(trackid)
if track_info:
dist = track_distance(item, track_info, incl_artist=True)
candidates[track_info.track_id] = \
hooks.TrackMatch(dist, track_info)
# If this is a good match, then don't keep searching.
rec = recommendation(candidates.values())
if rec == RECOMMEND_STRONG and not timid:
log.debug('Track ID match.')
return candidates.values(), rec
# If we're searching by ID, don't proceed.
if search_id is not None:
if candidates:
return candidates.values(), rec
else:
return [], RECOMMEND_NONE
# Search terms.
if not (search_artist and search_title):
search_artist, search_title = item.artist, item.title
log.debug(u'Item search terms: %s - %s' % (search_artist, search_title))
# Get and evaluate candidate metadata.
for track_info in hooks._item_candidates(item, search_artist,
search_title):
dist = track_distance(item, track_info, incl_artist=True)
candidates[track_info.track_id] = hooks.TrackMatch(dist, track_info)
# Sort by distance and return with recommendation.
log.debug('Found %i candidates.' % len(candidates))
candidates = sorted(candidates.itervalues())
rec = recommendation(candidates)
return candidates, rec
def tag_item(item, search_artist=None, search_title=None,
search_id=None):
"""Attempts to find metadata for a single track. Returns a
`(candidates, recommendation)` pair where `candidates` is a list of
TrackMatch objects. `search_artist` and `search_title` may be used
to override the current metadata for the purposes of the MusicBrainz
title; likewise `search_id`.
"""
# Holds candidates found so far: keys are MBIDs; values are
# (distance, TrackInfo) pairs.
candidates = {}
# First, try matching by MusicBrainz ID.
trackid = search_id or item.mb_trackid
if trackid:
log.debug('Searching for track ID: ' + trackid)
track_info = hooks._track_for_id(trackid)
if track_info:
dist = track_distance(item, track_info, incl_artist=True)
candidates[track_info.track_id] = \
hooks.TrackMatch(dist, track_info)
# If this is a good match, then don't keep searching.
rec = recommendation(candidates.values())
if rec == RECOMMEND_STRONG and not config['import']['timid']:
log.debug('Track ID match.')
return candidates.values(), rec
# If we're searching by ID, don't proceed.
if search_id is not None:
if candidates:
return candidates.values(), rec
else:
return [], RECOMMEND_NONE
# Search terms.
if not (search_artist and search_title):
search_artist, search_title = item.artist, item.title
log.debug(u'Item search terms: %s - %s' % (search_artist, search_title))
# Get and evaluate candidate metadata.
for track_info in hooks._item_candidates(item, search_artist, search_title):
dist = track_distance(item, track_info, incl_artist=True)
candidates[track_info.track_id] = hooks.TrackMatch(dist, track_info)
# Sort by distance and return with recommendation.
log.debug('Found %i candidates.' % len(candidates))
candidates = sorted(candidates.itervalues())
rec = recommendation(candidates)
return candidates, rec
def tag_item(item, timid=False, search_artist=None, search_title=None,
search_id=None):
"""Attempts to find metadata for a single track. Returns a
`(candidates, recommendation)` pair where `candidates` is a list
of `(distance, track_info)` pairs. `search_artist` and
`search_title` may be used to override the current metadata for
the purposes of the MusicBrainz title; likewise `search_id`.
"""
candidates = []
# First, try matching by MusicBrainz ID.
trackid = search_id or item.mb_trackid
if trackid:
log.debug('Searching for track ID: ' + trackid)
track_info = hooks._track_for_id(trackid)
if track_info:
dist = track_distance(item, track_info, incl_artist=True)
candidates.append((dist, track_info))
# If this is a good match, then don't keep searching.
rec = recommendation(candidates)
if rec == RECOMMEND_STRONG and not timid:
log.debug('Track ID match.')
return candidates, rec
# If we're searching by ID, don't proceed.
if search_id is not None:
if candidates:
return candidates, rec
else:
return [], RECOMMEND_NONE
# Search terms.
if not (search_artist and search_title):
search_artist, search_title = item.artist, item.title
log.debug(u'Item search terms: %s - %s' % (search_artist, search_title))
# Get and evaluate candidate metadata.
for track_info in hooks._item_candidates(item, search_artist, search_title):
dist = track_distance(item, track_info, incl_artist=True)
candidates.append((dist, track_info))
# Sort by distance and return with recommendation.
log.debug('Found %i candidates.' % len(candidates))
candidates.sort()
rec = recommendation(candidates)
return candidates, rec
