def _album_candidates(items, artist, album, va_likely): """Search for album matches. ``items`` is a list of Item objects that make up the album. ``artist`` and ``album`` are the respective names (strings), which may be derived from the item list or may be entered by the user. ``va_likely`` is a boolean indicating whether the album is likely to be a "various artists" release. """ out = [] # Base candidates if we have album and artist to match. if artist and album: try: out.extend(mb.match_album(artist, album, len(items))) except mb.MusicBrainzAPIError as exc: exc.log(log) # Also add VA matches from MusicBrainz where appropriate. if va_likely and album: try: out.extend(mb.match_album(None, album, len(items))) except mb.MusicBrainzAPIError as exc: exc.log(log) # Candidates from plugins. out.extend(plugins.candidates(items)) return out
def tag_album(items, timid=False, search_artist=None, search_album=None, search_id=None): """Bundles together the functionality used to infer tags for a set of items comprised by an album. Returns everything relevant: - The current artist. - The current album. - A list of (distance, items, info) tuples where info is a dictionary containing the inferred tags and items is a reordered version of the input items list. The candidates are sorted by distance (i.e., best match first). - A recommendation, one of RECOMMEND_STRONG, RECOMMEND_MEDIUM, or RECOMMEND_NONE; indicating that the first candidate is very likely, it is somewhat likely, or no conclusion could be reached. If search_artist and search_album or search_id are provided, then they are used as search terms in place of the current metadata. May raise an AutotagError if existing metadata is insufficient. """ # Get current metadata. cur_artist, cur_album, artist_consensus = current_metadata(items) log.debug('Tagging %s - %s' % (cur_artist, cur_album)) # The output result tuples (keyed by MB album ID). out_tuples = {} # Try to find album indicated by MusicBrainz IDs. if search_id: log.debug('Searching for album ID: ' + search_id) id_info = mb.album_for_id(search_id) else: id_info = match_by_id(items) if id_info: validate_candidate(items, out_tuples, id_info) rec = recommendation(out_tuples.values()) log.debug('Album ID match recommendation is ' + str(rec)) if out_tuples and not timid: # If we have a very good MBID match, return immediately. # Otherwise, this match will compete against metadata-based # matches. if rec == RECOMMEND_STRONG: log.debug('ID match.') return cur_artist, cur_album, out_tuples.values(), rec # If searching by ID, don't continue to metadata search. if search_id is not None: if out_tuples: return cur_artist, cur_album, out_tuples.values(), rec else: return cur_artist, cur_album, [], RECOMMEND_NONE # Search terms. if not (search_artist and search_album): # No explicit search terms -- use current metadata. search_artist, search_album = cur_artist, cur_album log.debug(u'Search terms: %s - %s' % (search_artist, search_album)) # Get candidate metadata from search. if search_artist and search_album: candidates = mb.match_album(search_artist, search_album, len(items), MAX_CANDIDATES) candidates = list(candidates) else: candidates = [] # Possibly add "various artists" search. if search_album and ((not artist_consensus) or \ (search_artist.lower() in VA_ARTISTS) or \ any(item.comp for item in items)): log.debug(u'Possibly Various Artists; adding matches.') candidates.extend(mb.match_album(None, search_album, len(items), MAX_CANDIDATES)) # Get candidates from plugins. candidates.extend(plugins.candidates(items)) # Get the distance to each candidate. log.debug(u'Evaluating %i candidates.' % len(candidates)) for info in candidates: validate_candidate(items, out_tuples, info) # Sort by distance. out_tuples = out_tuples.values() out_tuples.sort() rec = recommendation(out_tuples) return cur_artist, cur_album, out_tuples, rec