def copy_files(self, objects):
mimeData = QtCore.QMimeData()
mimeData.setUrls([
QtCore.QUrl.fromLocalFile(f.filename)
for f in iter_files_from_objects(objects)
])
self.clipboard().setMimeData(mimeData)
def extract_and_submit_acousticbrainz_features(self, objs):
"""Extract AcousticBrainz features and submit them."""
if not self.ab_extractor.available():
return
for file in iter_files_from_objects(objs):
# Skip unmatched files
if not file.can_extract():
log.warning(
"AcousticBrainz requires a MusicBrainz Recording ID, but file does not have it: %s"
% file.filename)
# And process matched ones
else:
file.set_pending()
# Check if file was either already processed or sent to the AcousticBrainz server
if file.acousticbrainz_features_file:
results = (file.acousticbrainz_features_file, 0,
"Writing results")
ab_extractor_callback(self, file, results, False)
elif file.acousticbrainz_is_duplicate:
results = (None, 0, "Duplicate")
ab_extractor_callback(self, file, results, False)
else:
file.acousticbrainz_error = False
# Launch the acousticbrainz on a separate process
log.debug("Extracting AcousticBrainz features from %s" %
file.filename)
ab_feature_extraction(
self, file.metadata["musicbrainz_recordingid"],
file.filename,
partial(ab_extractor_callback, self, file))
def analyze(self, objs):
"""Analyze the file(s)."""
if not self.use_acoustid:
return
for file in iter_files_from_objects(objs):
if file.can_analyze():
file.set_pending()
self._acoustid.analyze(file, partial(file._lookup_finished, File.LOOKUP_ACOUSTID))
def play(self):
"""Play selected tracks with an internal player"""
self._player.stop()
playlist = QtMultimedia.QMediaPlaylist(self)
playlist.setPlaybackMode(QtMultimedia.QMediaPlaylist.Sequential)
playlist.addMedia([QtMultimedia.QMediaContent(QtCore.QUrl.fromLocalFile(file.filename))
for file in iter_files_from_objects(self._selected_objects)])
self._player.setPlaylist(playlist)
self._player.play()
def test_iterate_only_unique(self):
f1 = Mock()
f2 = Mock()
f3 = Mock()
obj1 = Mock()
obj1.iterfiles = Mock(return_value=[f1, f2])
obj2 = Mock()
obj2.iterfiles = Mock(return_value=[f2, f3])
result = iter_files_from_objects([obj1, obj2])
self.assertTrue(isinstance(result, Iterator))
self.assertEqual([f1, f2, f3], list(result))
def generate_fingerprints(self, objs):
"""Generate the fingerprints without matching the files."""
if not self.use_acoustid:
return
def finished(file, result):
file.clear_pending()
for file in iter_files_from_objects(objs):
file.set_pending()
self._acoustid.fingerprint(file, partial(finished, file))
def cluster(self, objs, callback=None):
"""Group files with similar metadata to 'clusters'."""
log.debug("Clustering %r", objs)
files = iter_files_from_objects(objs)
try:
file = next(files)
except StopIteration:
files = self.unclustered_files.files
else:
files = itertools.chain([file], files)
thread.run_task(partial(self._do_clustering, list(files)),
partial(self._clustering_finished, callback))
def save(self, objects):
"""Save the specified objects."""
for file in iter_files_from_objects(objects, save=True):
file.save()
def get_files_from_objects(self, objects, save=False):
"""Return list of unique files from list of albums, clusters, tracks or files.
Note: Consider using picard.util.iter_files_from_objects instead, which returns an iterator.
"""
return list(iter_files_from_objects(objects, save=save))
