def track_attributes(self, item):
spotify_uri = item['track']['uri']
spotify_track_name = item['track']['name']
spotify_album_name = item['track']['album']['name']
spotify_album_cover_url = item['track']['album']['images'][0]['url']
try:
t = track.track_from_id(spotify_uri)
res = {
'name': spotify_track_name,
'spotify_uri': spotify_uri,
'spotify_album_cover_url': spotify_album_cover_url,
'spotify_album_name': spotify_album_name,
'echonest_id': t.id,
'speechiness': t.speechiness,
'key': t.key,
'energy': t.energy,
'liveness': t.liveness,
'tempo': t.tempo,
'acousticness': t.acousticness,
'instrumentalness': t.instrumentalness,
'mode': t.mode,
'time_signature': t.time_signature,
'duration': t.duration,
'loudness': t.loudness,
'valence': t.valence,
'danceability': t.danceability
}
return res
except:
print("Error occurred finding track '" + spotify_uri + "' using Echonest.")
def dump_loudness(id):
t = track.track_from_id(id)
print "# ID ", id
print "#", t.title, 'by', t.artist
print "#"
weighted = []
half_track = t.duration / 2
first_half = 0
second_half = 0
for seg in t.segments:
loudness = seg['loudness_max']
weighted.append(loudness)
if len(weighted) > WEIGHT:
weighted.pop(0)
avg = sum(weighted) / len(weighted)
seg_loudness = seg['loudness_max'] * seg['duration']
if seg['start'] < half_track:
first_half += seg_loudness
else:
second_half += seg_loudness
ramp_factor = second_half / half_track - first_half / half_track
#print seg['start'], loudness, avg, first_half, second_half, ramp_factor
print "%8.6f %9.4f %9.4f %12.6f %12.6f %12.6f" % (seg['start'], loudness, avg, first_half, second_half, ramp_factor)
print "#"
print "#", 'ramp factor', ramp_factor
def plot(self):
"""Plot song data"""
songs = echosong.search(title=self.title, artist=self.artist, results=1)
if songs:
# Search for the track through all catalogues
for catalog in CATALOGS:
# Fails when the API Key can't access a catalogue
try:
tracks = songs[0].get_tracks(catalog)
except EchoNestAPIError:
continue
# Get track or go to next catalogue
if not tracks:
continue
track = echotrack.track_from_id(tracks[0]['id'])
# Adjust start and end
self.start = self.start < track.duration and self.start or 0
self.end = self.end < track.duration and self.end or track.duration
# Get full aoustic analysis
track.get_analysis()
# Loudness (from segments)
x = np.array([segment.get('start') for segment in track.segments if self._inrange(segment)])
y = np.array([segment.get('loudness_max') for segment in track.segments if self._inrange(segment)])
plt.plot(x, y)
plt.xlabel('Duration')
plt.ylabel('Loudness')
# Use sections as a grid
[plt.axvline(section.get('start')+section.get('duration'), color='k', linestyle='--') for section in track.sections]
# Add caption and show plot
plt.suptitle('%s - %s' %(self.artist, self.title))
plt.show()
return
def getAnalysis(artist_name, track_name):
"""
pulls audio features that are stored, dumps in json format
"""
track_id, terms = getTrackID(artist_name, track_name)
# if the track is not found
if track_id == 0:
g = open("./output/failed.txt", "a")
g.write(str(artist_name) + ", " + str(track_name) + " does not exist")
return
#pull audio analsis
tmp = track.track_from_id(track_id)
if not tmp:
return
tmp.get_analysis()
filename = "./output/json/" + track_name + ".json"
filename.replace(" ", "")
with open(filename, 'w') as f:
json.dump(
{
'artist': artist_name,
'track': track_name,
'terms': terms,
'features': data
}, f)
def track_attributes(self, item):
spotify_uri = item['track']['uri']
spotify_track_name = item['track']['name']
spotify_album_name = item['track']['album']['name']
spotify_album_cover_url = item['track']['album']['images'][0]['url']
try:
t = track.track_from_id(spotify_uri)
res = {
'name': spotify_track_name,
'spotify_uri': spotify_uri,
'spotify_album_cover_url': spotify_album_cover_url,
'spotify_album_name': spotify_album_name,
'echonest_id': t.id,
'speechiness': t.speechiness,
'key': t.key,
'energy': t.energy,
'liveness': t.liveness,
'tempo': t.tempo,
'acousticness': t.acousticness,
'instrumentalness': t.instrumentalness,
'mode': t.mode,
'time_signature': t.time_signature,
'duration': t.duration,
'loudness': t.loudness,
'valence': t.valence,
'danceability': t.danceability
}
return res
except:
print("Error occurred finding track '" + spotify_uri +
"' using Echonest.")
def analyzeTracks(songToTrack):
"""
Creates a list of songs for training. Limit allows us to get
a smaller dataset for testing purposes. Current dataset is based
on [Artist, Tempo, Danceability, Energy, Speech, Acoustic]
"""
data = []
for song, trackInfo in songToTrack.items():
trackId, artist, songName = trackInfo
while True:
try:
t = echotrack.track_from_id(trackId)
t.get_analysis()
tempo = t.tempo
dance = t.danceability
energy = t.energy
speech = t.speechiness
acoustic = t.acousticness
data.append([song, artist, tempo, dance, energy, speech, acoustic])
except echoutil.EchoNestAPIError: # We exceeded our access limit
print "too many accesses per minute - retry in a minute"
time.sleep(60)
continue
except IndexError: # The song wasn't found on echo nest
print "index error - skip"
break
except echoutil.EchoNestIOError: # Unknown error from echo nest
print "unknown error - retry"
continue
break # retry request
return data
def get_best_audio_track(song_id, catalog, pysong=None):
"""
Get the best (audio) track for a given song in the given catalog.
Returns a dict with {'track': ..., 'duration': ..., etc.}
"""
if not pysong:
pysong = song.Song(song_id)
tracks = pysong.get_tracks(catalog)
best_track = None
for t in tracks:
pytrack = track.track_from_id(t['id'])
if pytrack.__dict__.get('tempo'):
# track has audio features
best_track = pytrack
foreign_id = t['foreign_id']
break
if best_track:
result = {'track': best_track.id,
'title': best_track.title,
'duration': best_track.duration,
'tempo': pysong.audio_summary['tempo'],
'energy': pysong.audio_summary['energy'],
'danceability': pysong.audio_summary['danceability'],
'loudness': best_track.loudness,
'foreign_id': foreign_id.split(':')[2],
'hotttnesss': pysong.song_hotttnesss,
'familiarity': pysong.artist_familiarity,
'song': pysong.id
}
return result
else:
return None
def create_track_file_from_trackid(maindir,
trackid,
song,
artist,
mbconnect=None):
"""
Get a track from a track id and calls for its creation.
We assume we already have song and artist.
We can have a connection to musicbrainz as an option.
This function should create only one file!
GOAL: mostly, it checks if we have the track already created before
calling EchoNest API. It saves some calls/time
Also, handles some errors.
INPUT
maindir - MillionSongDataset root directory
trackid - Echo Nest track ID (string: TRABC.....)
song - pyechonest song object for that track
artist - pyechonest artist object for that song/track
mbconnect - open musicbrainz pg connection
RETURN
true if a song file is created, false otherwise
"""
# CLOSED CREATION?
if CREATION_CLOSED:
return False
# do we already have this track in the dataset?
track_path = os.path.join(maindir, path_from_trackid(trackid))
if os.path.exists(track_path):
return False
# get that track!
try_cnt = 0
while True:
try:
try_cnt += 1
track = trackEN.track_from_id(trackid)
break
except KeyboardInterrupt:
close_creation()
raise
except urllib2.HTTPError, e:
print type(e), ':', e
print 'we dont retry for that error, trackid=', trackid, '(pid=' + str(
os.getpid()) + ')'
return False
except Exception, e:
print type(e), ':', e
print 'at time', time.ctime(
), 'in create_track_file_from_trackid, tid=', trackid, '(we wait', SLEEPTIME, 'seconds) (pid=' + str(
os.getpid()) + ')'
if try_cnt < 50:
time.sleep(SLEEPTIME)
continue
else:
print 'we give up after', try_cnt, 'tries.'
return False
def create_track_file_from_trackid(maindir,trackid,song,artist,mbconnect=None):
"""
Get a track from a track id and calls for its creation.
We assume we already have song and artist.
We can have a connection to musicbrainz as an option.
This function should create only one file!
GOAL: mostly, it checks if we have the track already created before
calling EchoNest API. It saves some calls/time
Also, handles some errors.
INPUT
maindir - MillionSongDataset root directory
trackid - Echo Nest track ID (string: TRABC.....)
song - pyechonest song object for that track
artist - pyechonest artist object for that song/track
mbconnect - open musicbrainz pg connection
RETURN
true if a song file is created, false otherwise
"""
# CLOSED CREATION?
if CREATION_CLOSED:
return False
# do we already have this track in the dataset?
track_path = os.path.join(maindir,path_from_trackid(trackid))
if os.path.exists(track_path):
return False
# get that track!
try_cnt = 0
while True:
try:
try_cnt += 1
track = trackEN.track_from_id(trackid)
break
except KeyboardInterrupt:
close_creation()
raise
except urllib.error.HTTPError as e:
print(type(e),':',e)
print('we dont retry for that error, trackid=',trackid,'(pid='+str(os.getpid())+')')
return False
except Exception as e:
print(type(e),':',e)
print('at time',time.ctime(),'in create_track_file_from_trackid, tid=',trackid,'(we wait',SLEEPTIME,'seconds) (pid='+str(os.getpid())+')')
if try_cnt < 50:
time.sleep(SLEEPTIME)
continue
else:
print('we give up after',try_cnt,'tries.')
return False
# we have everything, launch create track file
res = create_track_file(maindir,trackid,track,song,artist,mbconnect=mbconnect)
return res
def analyze(self, item):
log.info("analyze")
# md5 = '96fa0180d225f14e9f8cbfffbf5eb81d'
t = None
if item.echonest_id:
try:
log.debug("query by echonest id: %s" % item.echonest_id)
t = track.track_from_id(item.echonest_id)
except EchoNestAPIError, e:
print e
def track_attributes(self, spotify_uri):
try:
t = track.track_from_id(spotify_uri)
res = {
'danceability': t.danceability,
'loudness': t.loudness,
'energy': t.energy,
'speechiness': t.speechiness,
'liveness': t.liveness,
'acousticness': t.acousticness,
'instrumentalness': t.instrumentalness
}
return res
except:
return { 'error': "Error occurred finding track '" + spotify_uri + "'." }
def __init__(self, name, track_ids=None):
self.name = name
# Add it to the dictionary containing all the keystreams
total[name] = self
# Get some random tracks from the specified catalog UNLESS track_ids is specified
if track_ids:
# FIXME make sure list contains no empty strings in the first place
self.tracks = [track.track_from_id(track_id) for track_id in track_ids if track_id != ""]
else:
self.tracks = echonest.get_catalog_tracks()
tracks_data = [echonest.get_track_data(each_track) for each_track in self.tracks]
# This should be fixed - don't save the raw track data, just save the track names etc
self.bitstream = "0".join(["0".join(x) for x in utils.do_something_weird(tracks_data)])
self.encrypt_pointer = 0
self.decrypt_pointer = 0
repickle()
def getSegments():
# import track
t = track.track_from_id('TRJQYJG14AD4E8352A')
# get the track analysis
t.get_analysis()
# prints the metadata
t.meta
#access to the tatums list
#print t.tatums
segs = t.segments
for seg in segs:
print seg['timbre']
def track_with_file(filename, mp3=None, track_id=None):
if track_id:
nest_track = track.track_from_id(track_id)
else:
nest_track = track.track_from_filename(mp3 or filename)
audio_track = audiolab.Sndfile(filename)
nest_track.samplerate = rate = audio_track.samplerate
nest_track.nframes = audio_track.nframes
cur_frame = 0
for seg in nest_track.segments:
num_frames = rate * seg["duration"]
if cur_frame != seg["start"] * rate:
num_frames += seg["start"] * rate - cur_frame
if cur_frame + num_frames > audio_track.nframes:
num_frames = audio_track.nframes - cur_frame
seg["raw"] = audio_track.read_frames(num_frames)
cur_frame += num_frames
return nest_track
def get_catalog_tracks(variety=0.8):
print "getting catalog tracks"
p = playlist.static(type='catalog-radio', seed_catalog=settings.seed_catalog, variety=variety, results=100) # lol
print "done getting catalog tracks"
tracks = []
while len(tracks) < settings.songs_per_keystream:
try:
#s = p.get_next_song()
s = p.pop()
t = track.track_from_id(s.get_tracks('7digital')[0]['id'])
tracks.append(t)
print t
except IndexError:
pass
if len(p) == 0:
p = playlist.static(type='catalog-radio', seed_catalog=settings.seed_catalog, variety=variety, results=100)
return tracks
def analyzeTracksNoArtist(songToTrack):
"""
Creates a list of songs for training. Limit allows us to get
a smaller dataset for testing purposes. Current dataset is based
on [Tempo, Danceability, Energy]
"""
data = []
for song, trackIds in songToTrack.items():
if len(trackIds) == 0: continue
trackId = trackIds[0]
while True:
try:
t = echotrack.track_from_id(trackId)
t.get_analysis()
tempo = t.tempo
dance = t.danceability
energy = t.energy
speech = t.speechiness
acoustic = t.acousticness
data.append([song, tempo, dance, energy, speech, acoustic])
except echoutil.EchoNestAPIError: # We exceeded our access limit
print "too many accesses per minute - retry in a minute"
time.sleep(60)
continue
except IndexError: # The song wasn't found on echo nest
print "index error - skip"
break
except echoutil.EchoNestIOError: # Unknown error from echo nest
print "unknown error - retry"
continue
break # retry request
# Write to file every 1000 analyzes
if len(data) % 1000 == 0:
with open("data/analyzed_data.csv", "wb") as f:
writer = csv.writer(f)
writer.writerows(data)
return data
def get_playlist_track_analysis(playlist_tracks):
"""
Description:
Analyzes the audio features of a playlist's tracks through
Echonest, given a list of Spotify track IDs.
Return:
A list of track features for songs in the specified playlist
"""
set_api_key()
analysis = []
for i in range(len(playlist_tracks)):
if i % 10 == 0:
print 'On %dth track' % i
print playlist_tracks[i]
try:
next_track = track.track_from_id(playlist_tracks[i])
print next_track
print '---'
except util.EchoNestAPIError:
print 'Error extracting track profile: %s' % playlist_tracks[i]
pass
try:
if not contains_all_attributes(next_track):
# Try to get analysis, if missing attributes
next_track = next_track.get_analysis()
analysis.append(next_track)
except Exception:
print 'Error processing track: %s' % next_track
pass
time.sleep(3) # limited to 20 access/s
if i % 20 == 0 and i > 0:
print "Completed %d tracks" % i
return analysis
def get_track_features(start, stop):
for num, track_info in enumerate(track_list[start:stop]):
if num % 20 == 0:
time.sleep(15)
trk_id = track_info[0]
year, song_id, artist, track_name = track_info[1]
info_dict = dict()
info_dict['year'] = year
info_dict['artist'] = artist
info_dict['track_name'] = track_name
info_dict['track_id'] = trk_id
info_dict['song_id'] = song_id
tester = 0
try:
trk = track.track_from_id(trk_id)
info_dict['track_acousticness'] = trk.acousticness
info_dict['track_danceability'] = trk.danceability
info_dict['track_duration'] = trk.duration
info_dict['track_energy'] = trk.energy
info_dict['track_instrumentalness'] = trk.instrumentalness
info_dict['track_key'] = trk.key
info_dict['track_liveness'] = trk.liveness
info_dict['track_loudness'] = trk.loudness
info_dict['track_mode'] = trk.mode
info_dict['track_speechiness'] = trk.speechiness
info_dict['track_tempo'] = trk.tempo
info_dict['track_time_signature'] = trk.time_signature
info_dict['track_valence'] = trk.valence
except:
print num, ' - track fail'
tester += 1
try:
sawng = song.Song(song_id)
location = sawng.get_artist_location()
summary = sawng.get_audio_summary()
# location
info_dict['latitude'] = location['latitude']
info_dict['longitude'] = location['longitude']
info_dict['city'] = location['location']
# audio summary
info_dict['song_danceability'] = summary['danceability']
info_dict['song_duration'] = summary['duration']
info_dict['song_acousticness'] = summary['acousticness']
info_dict['analysis_url'] = summary['analysis_url']
info_dict['song_energy'] = summary['energy']
info_dict['song_instrumentalness'] = summary['instrumentalness']
info_dict['song_key'] = summary['key']
info_dict['song_liveness'] = summary['liveness']
info_dict['song_loudness'] = summary['loudness']
info_dict['song_mode'] = summary['mode']
info_dict['speechiness'] = summary['speechiness']
info_dict['song_tempo'] = summary['tempo']
info_dict['song_time_signature'] = summary['time_signature']
info_dict['song_valence'] = summary['valence']
# hotness, familiarity, and type
info_dict['song_type'] = sawng.get_song_type()
info_dict['artist_familiarity'] = sawng.get_artist_familiarity()
info_dict['artist_hotttnesss'] = sawng.get_artist_hotttnesss()
info_dict['song_currency'] = sawng.get_song_currency()
info_dict['song_hotttnesss'] = sawng.get_song_hotttnesss()
info_dict['artist_id'] = str(sawng.artist_id)
except:
print num, ' - song fail'
tester += 1
if tester < 2:
trackDict[trk_id] = info_dict
else:
pass
def dump_loudness(id, file=sys.stdout):
t = track.track_from_id(id)
title = t.title + ' by ' + t.artist
spotify_id = get_spotify_id(t.artist, t.title)
print >>file, "# ID ", id
print >>file, "#", title
print >>file, "# ARTIST ", t.artist
print >>file, "# TITLE ", t.title
print >>file, "# SONG_ID ", t.song_id
print >>file, "# SPOT_ID ", spotify_id
print >>file, "#"
weighted = []
half_track = t.duration / 2
first_half = 0
second_half = 0
xdata = []
ydata = []
for seg in t.segments:
sstart = seg['start']
sloudness = min(seg['loudness_max'], 0)
sloudness = max(sloudness, -60)
sduration = seg['duration']
send = sstart + sduration
weighted.append(sloudness)
if len(weighted) > WEIGHT:
weighted.pop(0)
avg = sum(weighted) / len(weighted)
if send <= half_track:
seg_loudness = sloudness * sduration
first_half += seg_loudness
elif sstart < half_track and send > half_track:
# this is the nasty segment that spans the song midpoint.
# apportion the loudness appropriately
first_seg_loudness = sloudness * (half_track - sstart)
first_half += first_seg_loudness
second_seg_loudness = sloudness * (send - half_track)
second_half += second_seg_loudness
else:
seg_loudness = sloudness * sduration
second_half += seg_loudness
xdata.append( sstart )
ydata.append( sloudness )
ramp_factor = second_half / half_track - first_half / half_track
#print >>file, seg['start'], sloudness, avg, first_half, second_half, ramp_factor
#print >>file, "%8.6f %9.4f %9.4f %12.6f %12.6f %12.6f" % (sstart, sloudness, avg, first_half, second_half, ramp_factor)
print >>file, "%8.6f %9.4f %9.4f" % (sstart, sloudness, avg)
correlation = pearsonr(xdata, ydata)
print >>file, "#"
print >>file, "#", 'ramp factor', ramp_factor
print >>file, "#", 'correlation', correlation
print >>file, "#", 'first', first_half / half_track
print >>file, "#", 'second', second_half / half_track
print >>file, "#"
return title, ramp_factor, first_half / half_track, second_half / half_track
def echo_nest_update():
"""
Updates the json with all EchoNest data available for this song """
from pyechonest import config
config.ECHO_NEST_API_KEY = ECHO_NEST_API_KEY
config.CALL_TIMEOUT = 60
while True:
json_data = yield
if json_data == STOP:
break
if json_data.get('echo_nest', ''):
continue
json_data['echo_nest'] = {}
track_title = ''
artist_name = ''
if json_data.get('lastfm', ''):
track_title = json_data['lastfm'].get('track', '')
artist_name = json_data['lastfm'].get('artist', '')
if not track_title:
track_title = json_data['id3'].get('title', '')
if not artist_name:
artist_name = json_data['id3'].get('artist', '')
a = None
try:
if artist_name:
a = artist.Artist(artist_name,
buckets=['biographies', 'blogs',
'doc_counts', 'familiarity',
'hotttnesss', 'genre',
'artist_location', 'news',
'reviews', 'urls', 'years_active'])
json_data['echo_nest']['artist_id'] = a.id
time.sleep(1)
json_data['echo_nest']['artist'] = a.name
time.sleep(1)
json_data['echo_nest']['bios'] = a.biographies
time.sleep(1)
json_data['echo_nest']['blogs'] = a.blogs
time.sleep(1)
json_data['echo_nest']['doc_counts'] = a.doc_counts
time.sleep(1)
json_data['echo_nest']['a_familiarity'] = a.familiarity
time.sleep(1)
json_data['echo_nest']['a_hotttnesss'] = a.hotttnesss
time.sleep(1)
json_data['echo_nest']['news'] = a.news
time.sleep(1)
json_data['echo_nest']['reviews'] = a.reviews
time.sleep(1)
json_data['echo_nest']['urls'] = a.urls
time.sleep(1)
json_data['echo_nest']['years_active'] = a.years_active
time.sleep(1)
json_data['echo_nest']['similar'] = [str(sim.name) for sim
in a.get_similar()]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if a and track_title:
try:
results = song.search(artist=a.name,
title=track_title,
buckets=['audio_summary',
'song_hotttnesss',
'song_discovery'])
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if results:
json_data['echo_nest']['id'] = results[0].id
time.sleep(1)
json_data['echo_nest']['summary'] =\
results[0].audio_summary
time.sleep(1)
json_data['echo_nest']['s_hotttnesss'] =\
results[0].song_hotttnesss
time.sleep(1)
json_data['echo_nest']['s_discovery'] =\
results[0].song_discovery
time.sleep(1)
time.sleep(1)
tr = None
if json_data['echo_nest'].get('id', ''):
try:
tr = track.track_from_id(json_data['echo_nest']['id'])
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if not tr:
continue
try:
tr.get_analysis()
time.sleep(1)
json_data['echo_nest']['analysis'] = {}
json_data['echo_nest']['analysis']['acousticness'] =\
tr.acousticness
json_data['echo_nest']['analysis']['analysis_url'] =\
tr.analysis_url
json_data['echo_nest']['analysis']['danceability'] =\
tr.danceability
json_data['echo_nest']['analysis']['duration'] =\
tr.duration
json_data['echo_nest']['analysis']['energy'] = tr.energy
json_data['echo_nest']['analysis']['key'] = tr.key
json_data['echo_nest']['analysis']['liveness'] =\
tr.liveness
json_data['echo_nest']['analysis']['loudness'] =\
tr.loudness
json_data['echo_nest']['analysis']['mode'] = tr.mode
json_data['echo_nest']['analysis']['speechiness'] =\
tr.speechiness
json_data['echo_nest']['analysis']['tempo'] =\
tr.tempo
json_data['echo_nest']['analysis']['time_signature'] =\
tr.time_signature
json_data['echo_nest']['analysis']['valence'] = tr.valence
json_data['echo_nest']['analysis']['analysis_channels'] =\
tr.analysis_channels
json_data['echo_nest']['analysis']['bars'] = tr.bars
json_data['echo_nest']['analysis']['beats'] = tr.beats
json_data['echo_nest']['analysis']['start_of_fade_out'] =\
tr.start_of_fade_out
json_data['echo_nest']['analysis']['end_of_fade_in'] =\
tr.end_of_fade_in
json_data['echo_nest']['analysis']['key_confidence'] =\
tr.key_confidence
json_data['echo_nest']['analysis']['meta'] = tr.meta
json_data['echo_nest']['analysis']['mode_confidence'] =\
tr.mode_confidence
json_data['echo_nest']['analysis']['num_samples'] =\
tr.num_samples
json_data['echo_nest']['analysis']['sections'] =\
tr.sections
json_data['echo_nest']['analysis']['segments'] =\
tr.segments
json_data['echo_nest']['analysis']['synchstring'] =\
tr.synchstring
json_data['echo_nest']['analysis']['tatums'] =\
tr.tatums
json_data['echo_nest']['analysis']['tempo_confidence'] =\
tr.tempo_confidence
json_data['echo_nest']['analysis']['sign_confidence'] =\
tr.time_signature_confidence
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
except Exception as e:
print(e)
time.sleep(1)
if a:
try:
json_data['echo_nest']['basic_song_list'] =\
['{} - {}'.format(s.artist_name, s.title) for s in
playlist.basic(type='song-radio',
artist_id=a.id,
song_id=tr.id)]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
try:
json_data['echo_nest']['basic_artist_list'] =\
['{} - {}'.format(s.artist_name, s.title) for s in
playlist.basic(artist_id=a.id, song_id=tr.id)]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
def echo_nest_update():
"""
Updates the json with all EchoNest data available for this song
('Echo Nest API Error 5: bucket - Invalid parameter:
bucket "id" is not one of "audio", "biographies", "blogs", "doc_counts",
"familiarity", "familiarity_rank", "genre", "hotttnesss",
"hotttnesss_rank", "discovery", "discovery_rank", "images",
"artist_location", "news", "reviews", "songs", "terms", "urls", "video",
"years_active", "id:7digital-US", "id:7digital-AU", "id:7digital-UK",
"id:facebook", "id:fma", "id:emi_bluenote", "id:emi_artists",
"id:twitter", "id:spotify-WW", "id:seatwave",
"id:lyricfind-US", "id:jambase", "id:musixmatch-WW", "id:rdio-US",
"id:rdio-AT", "id:rdio-AU", "id:rdio-BR", "id:rdio-CA", "id:rdio-CH",
"id:rdio-DE", "id:rdio-DK", "id:rdio-ES", "id:rdio-FI", "id:rdio-FR",
"id:rdio-IE", "id:rdio-IT", "id:rdio-NL", "id:rdio-NO", "id:rdio-NZ",
"id:rdio-PT", "id:rdio-SE", "id:emi_electrospective", "id:rdio-EE",
"id:rdio-LT", "id:rdio-LV", "id:rdio-IS", "id:rdio-BE", "id:rdio-MX",
"id:seatgeek", "id:rdio-GB", "id:rdio-CZ", "id:rdio-CO", "id:rdio-PL",
"id:rdio-MY", "id:rdio-HK", "id:rdio-CL", "id:twitter_numeric",
"id:7digital-ES", "id:openaura", "id:spotify", "id:spotify-WW",
"id:tumblr", or "id:<CATALOG ID>"
"""
from pyechonest import config
config.ECHO_NEST_API_KEY = ECHO_NEST_API_KEY
config.CALL_TIMEOUT = 60
while True:
json_data = yield
if json_data == STOP:
break
if json_data.get('echo_nest', ''):
continue
json_data['echo_nest'] = {}
track_title = ''
artist_name = ''
if json_data.get('lastfm', ''):
track_title = json_data['lastfm'].get('track', '')
artist_name = json_data['lastfm'].get('artist', '')
if not track_title:
track_title = json_data['id3'].get('title', '')
if not artist_name:
artist_name = json_data['id3'].get('artist', '')
a = None
try:
if artist_name:
a = artist.Artist(artist_name,
buckets=['biographies', 'blogs',
'doc_counts', 'familiarity',
'hotttnesss', 'genre',
'artist_location', 'news',
'reviews', 'urls', 'years_active'])
json_data['echo_nest']['artist_id'] = a.id
time.sleep(1)
json_data['echo_nest']['artist'] = a.name
time.sleep(1)
json_data['echo_nest']['bios'] = a.biographies
time.sleep(1)
json_data['echo_nest']['blogs'] = a.blogs
time.sleep(1)
json_data['echo_nest']['doc_counts'] = a.doc_counts
time.sleep(1)
json_data['echo_nest']['a_familiarity'] = a.familiarity
time.sleep(1)
json_data['echo_nest']['a_hotttnesss'] = a.hotttnesss
time.sleep(1)
json_data['echo_nest']['news'] = a.news
time.sleep(1)
json_data['echo_nest']['reviews'] = a.reviews
time.sleep(1)
json_data['echo_nest']['urls'] = a.urls
time.sleep(1)
json_data['echo_nest']['years_active'] = a.years_active
time.sleep(1)
json_data['echo_nest']['similar'] = [str(sim.name) for sim
in a.get_similar()]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if a and track_title:
try:
results = song.search(artist=a.name,
title=track_title,
buckets=['audio_summary',
'song_hotttnesss',
'song_discovery'])
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if results:
json_data['echo_nest']['id'] = results[0].id
time.sleep(1)
json_data['echo_nest']['summary'] =\
results[0].audio_summary
time.sleep(1)
json_data['echo_nest']['s_hotttnesss'] =\
results[0].song_hotttnesss
time.sleep(1)
json_data['echo_nest']['s_discovery'] =\
results[0].song_discovery
time.sleep(1)
time.sleep(1)
tr = None
if json_data['echo_nest'].get('id', ''):
try:
tr = track.track_from_id(json_data['echo_nest']['id'])
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if not tr:
continue
try:
tr.get_analysis()
time.sleep(1)
json_data['echo_nest']['analysis'] = {}
json_data['echo_nest']['analysis']['acousticness'] =\
tr.acousticness
json_data['echo_nest']['analysis']['analysis_url'] =\
tr.analysis_url
json_data['echo_nest']['analysis']['danceability'] =\
tr.danceability
json_data['echo_nest']['analysis']['duration'] =\
tr.duration
json_data['echo_nest']['analysis']['energy'] = tr.energy
json_data['echo_nest']['analysis']['key'] = tr.key
json_data['echo_nest']['analysis']['liveness'] =\
tr.liveness
json_data['echo_nest']['analysis']['loudness'] =\
tr.loudness
json_data['echo_nest']['analysis']['mode'] = tr.mode
json_data['echo_nest']['analysis']['speechiness'] =\
tr.speechiness
json_data['echo_nest']['analysis']['tempo'] =\
tr.tempo
json_data['echo_nest']['analysis']['time_signature'] =\
tr.time_signature
json_data['echo_nest']['analysis']['valence'] = tr.valence
json_data['echo_nest']['analysis']['analysis_channels'] =\
tr.analysis_channels
json_data['echo_nest']['analysis']['bars'] = tr.bars
json_data['echo_nest']['analysis']['beats'] = tr.beats
json_data['echo_nest']['analysis']['start_of_fade_out'] =\
tr.start_of_fade_out
json_data['echo_nest']['analysis']['end_of_fade_in'] =\
tr.end_of_fade_in
json_data['echo_nest']['analysis']['key_confidence'] =\
tr.key_confidence
json_data['echo_nest']['analysis']['meta'] = tr.meta
json_data['echo_nest']['analysis']['mode_confidence'] =\
tr.mode_confidence
json_data['echo_nest']['analysis']['num_samples'] =\
tr.num_samples
json_data['echo_nest']['analysis']['sections'] =\
tr.sections
json_data['echo_nest']['analysis']['segments'] =\
tr.segments
json_data['echo_nest']['analysis']['synchstring'] =\
tr.synchstring
json_data['echo_nest']['analysis']['tatums'] =\
tr.tatums
json_data['echo_nest']['analysis']['tempo_confidence'] =\
tr.tempo_confidence
json_data['echo_nest']['analysis']['sign_confidence'] =\
tr.time_signature_confidence
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
except Exception as e:
print(e)
time.sleep(1)
if a:
try:
json_data['echo_nest']['basic_song_list'] =\
['{} - {}'.format(s.artist_name, s.title) for s in
playlist.basic(type='song-radio',
artist_id=a.id,
song_id=tr.id)]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
try:
json_data['echo_nest']['basic_artist_list'] =\
['{} - {}'.format(s.artist_name, s.title) for s in
playlist.basic(artist_id=a.id, song_id=tr.id)]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
def play_segment(segment):
audiolab.play(segment["raw"].mean(axis=1))
def track_with_file(filename, mp3=None, track_id=None):
if track_id:
nest_track = track.track_from_id(track_id)
else:
nest_track = track.track_from_filename(mp3 or filename)
audio_track = audiolab.Sndfile(filename)
nest_track.samplerate = rate = audio_track.samplerate
nest_track.nframes = audio_track.nframes
cur_frame = 0
for seg in nest_track.segments:
num_frames = rate * seg["duration"]
if cur_frame != seg["start"] * rate:
num_frames += seg["start"] * rate - cur_frame
if cur_frame + num_frames > audio_track.nframes:
num_frames = audio_track.nframes - cur_frame
seg["raw"] = audio_track.read_frames(num_frames)
cur_frame += num_frames
return nest_track
if __name__ == "__main__":
chad = track.track_from_id(u'TRP8KVE11BC6E02570') #Chad VanGaalen - Willow Tree
#print "%s - %s"%(chad.artist, chad.title)
for seg in isegments(chad,min_confidence=0.85):
#print "[%7.2f -> %7.2f] %s"%(seg["start"], seg["end"], seg["keys"])
print """<span data-start="%0.2f" data-stop="%0.2f">%s</span>"""%(seg["start"], seg["end"], ", ".join(seg["keys"].keys()))
def main(argv):
"""main function for standalone usage"""
usage = "usage: %prog [options] dir dbfile"
parser = OptionParser(usage=usage)
parser.add_option('-r', '--replace', help='Replace existing BPM/key ID3 tags',
default=False, action='store_true')
(options, args) = parser.parse_args(argv)
if len(args) != 2:
parser.print_help()
return 2
# do stuff
mp3s = rwalk(args[0], '*.mp3')
# Initialize shelve db. Check for existing 'maxkey'.
db = shelve.open(args[1])
try:
idx = db['maxkey']
print('%sAppending to existing database at index %s%s' % (GREEN, idx, ENDC))
except KeyError:
print('%sStarting new database%s' % (GREEN, ENDC))
idx = u'0'
try:
for mp3 in mp3s:
tags = ID3(mp3)
# Skip already analyzed files
if not options.replace and 'TXXX:mashupid' in tags: continue
# Skip big files
if os.path.getsize(mp3) > MAXSIZE: continue
try:
echosong = retry(audio.LocalAnalysis, [mp3], (socket.error,), sleep=30)
except Exception:
# This is to handle the LocalAnalysis call in the event it fails for
# reasons out of my control. Print an error message and move on. When
# you have time you should change the library's source to use something
# smarter, say a specialized exception: AnalysisPendingException, etc.
sys.stderr.write('%sSong analysis failed, skipping %s%s\n' % (RED, mp3, ENDC))
continue
moreinfo = track_from_id(echosong.analysis.identifier)
# Add main tags
tags.add(TBPM(encoding=1, text=unicode(round(echosong.analysis.tempo['value']))))
try:
tags.add(TKEY(encoding=1, text=key(echosong)))
except KeyError:
sys.stderr.write('%sIncorrect key info; key: %d, mode: %d%s\n' %
(RED, echosong.analysis.key['value'], echosong.analysis.mode['value'], ENDC))
tags.add(TXXX(encoding=3, desc=u'danceability', text=unicode(moreinfo.danceability)))
tags.add(TXXX(encoding=3, desc=u'energy', text=unicode(moreinfo.energy)))
tags.add(TXXX(encoding=3, desc=u'loudness', text=unicode(moreinfo.loudness)))
# Update entry in DB if it exists, or...
if 'TXXX:mashupid' in tags:
db[tags.get('TXXX:mashupid').text[0]] = echosong
else: # create a new entry
tags.add(TXXX(encoding=3, desc=u'mashupid', text=idx))
db[idx] = echosong
idx = unicode(int(idx) + 1)
tags.save()
# So we don't hammer their servers
print('%sFinished analyzing %s, sleeping...%s' % (GREEN, mp3, ENDC))
sleep(randint(0, 3))
except KeyboardInterrupt:
sys.stderr.write('User termination, exiting...\n')
finally:
# Update 'maxkey'.
db['maxkey'] = idx
db.close()
print('Done!')
def dump_loudness(id, file=sys.stdout):
t = track.track_from_id(id)
title = t.title + ' by ' + t.artist
spotify_id = get_spotify_id(t.artist, t.title)
print >> file, "# ID ", id
print >> file, "#", title
print >> file, "# ARTIST ", t.artist
print >> file, "# TITLE ", t.title
print >> file, "# SONG_ID ", t.song_id
print >> file, "# SPOT_ID ", spotify_id
print >> file, "#"
weighted = []
half_track = t.duration / 2
first_half = 0
second_half = 0
xdata = []
ydata = []
for seg in t.segments:
sstart = seg['start']
sloudness = min(seg['loudness_max'], 0)
sloudness = max(sloudness, -60)
sduration = seg['duration']
send = sstart + sduration
weighted.append(sloudness)
if len(weighted) > WEIGHT:
weighted.pop(0)
avg = sum(weighted) / len(weighted)
if send <= half_track:
seg_loudness = sloudness * sduration
first_half += seg_loudness
elif sstart < half_track and send > half_track:
# this is the nasty segment that spans the song midpoint.
# apportion the loudness appropriately
first_seg_loudness = sloudness * (half_track - sstart)
first_half += first_seg_loudness
second_seg_loudness = sloudness * (send - half_track)
second_half += second_seg_loudness
else:
seg_loudness = sloudness * sduration
second_half += seg_loudness
xdata.append(sstart)
ydata.append(sloudness)
ramp_factor = second_half / half_track - first_half / half_track
#print >>file, seg['start'], sloudness, avg, first_half, second_half, ramp_factor
#print >>file, "%8.6f %9.4f %9.4f %12.6f %12.6f %12.6f" % (sstart, sloudness, avg, first_half, second_half, ramp_factor)
print >> file, "%8.6f %9.4f %9.4f" % (sstart, sloudness, avg)
correlation = pearsonr(xdata, ydata)
print >> file, "#"
print >> file, "#", 'ramp factor', ramp_factor
print >> file, "#", 'correlation', correlation
print >> file, "#", 'first', first_half / half_track
print >> file, "#", 'second', second_half / half_track
print >> file, "#"
return title, ramp_factor, first_half / half_track, second_half / half_track
def analyzeTracksNoArtist(songToTrack):
"""
Creates a list of songs for training. Limit allows us to get
a smaller dataset for testing purposes. Current dataset is based
on [SongId, Tempo, Danceability, Energy, Speech, Acoutsicness]
"""
data = []
skipped = 0
for song, trackIds in songToTrack.items():
if len(trackIds) == 0: continue
trackId = trackIds[0]
retryCount = 0
while True:
if retryCount == 10:
print "Retried 10 times - skipping"
skipped += 1
break
try:
t = echotrack.track_from_id(trackId)
t.get_analysis()
tempo = t.tempo
dance = t.danceability
energy = t.energy
speech = t.speechiness
acoustic = t.acousticness
data.append([song, tempo, dance, energy, speech, acoustic])
except echoutil.EchoNestAPIError: # We exceeded our access limit
print "too many accesses per minute - retry in a minute"
time.sleep(60)
retryCount += 1
continue
except IndexError: # The song wasn't found on echo nest
print "index error - skip"
skipped += 1
break
except echoutil.EchoNestIOError: # Unknown error from echo nest
print "IO error - retry"
retryCount += 1
continue
except Exception:
print "unknown exception - skip"
skipped += 1
break
break # retry request
# Write to file every 1000 analyzes
if len(data) % 500 == 0:
count = len(data)
print "total analyzed: ", count
with open(write_file, "w") as f:
for d in data:
# Convert list to string
dString = ""
for item in d:
dString += str(item) + ','
f.write(dString[:-1])
f.write('\n')
print "total skipped: ", skipped
return data
def get_track_features(start, stop):
for num, track_info in enumerate(track_list[start:stop]):
if num % 20 == 0:
time.sleep(15)
trk_id = track_info[0]
year, song_id, artist, track_name = track_info[1]
info_dict = dict()
info_dict['year'] = year
info_dict['artist'] = artist
info_dict['track_name'] = track_name
info_dict['track_id'] = trk_id
info_dict['song_id'] = song_id
tester = 0
try:
trk = track.track_from_id(trk_id)
info_dict['track_acousticness'] = trk.acousticness
info_dict['track_danceability'] = trk.danceability
info_dict['track_duration'] = trk.duration
info_dict['track_energy'] = trk.energy
info_dict['track_instrumentalness'] = trk.instrumentalness
info_dict['track_key'] = trk.key
info_dict['track_liveness'] = trk.liveness
info_dict['track_loudness'] = trk.loudness
info_dict['track_mode'] = trk.mode
info_dict['track_speechiness'] = trk.speechiness
info_dict['track_tempo'] = trk.tempo
info_dict['track_time_signature'] = trk.time_signature
info_dict['track_valence'] = trk.valence
except:
print num, ' - track fail'
tester += 1
try:
sawng = song.Song(song_id)
location = sawng.get_artist_location()
summary = sawng.get_audio_summary()
# location
info_dict['latitude'] = location['latitude']
info_dict['longitude'] = location['longitude']
info_dict['city'] = location['location']
# audio summary
info_dict['song_danceability'] = summary['danceability']
info_dict['song_duration'] = summary['duration']
info_dict['song_acousticness'] = summary['acousticness']
info_dict['analysis_url'] = summary['analysis_url']
info_dict['song_energy'] = summary['energy']
info_dict['song_instrumentalness'] = summary['instrumentalness']
info_dict['song_key'] = summary['key']
info_dict['song_liveness'] = summary['liveness']
info_dict['song_loudness'] = summary['loudness']
info_dict['song_mode'] = summary['mode']
info_dict['speechiness'] = summary['speechiness']
info_dict['song_tempo'] = summary['tempo']
info_dict['song_time_signature'] = summary['time_signature']
info_dict['song_valence'] = summary['valence']
# hotness, familiarity, and type
info_dict['song_type'] = sawng.get_song_type()
info_dict['artist_familiarity'] = sawng.get_artist_familiarity()
info_dict['artist_hotttnesss'] = sawng.get_artist_hotttnesss()
info_dict['song_currency'] = sawng.get_song_currency()
info_dict['song_hotttnesss'] = sawng.get_song_hotttnesss()
info_dict['artist_id'] = str(sawng.artist_id)
except:
print num, ' - song fail'
tester += 1
if tester < 2:
trackDict[trk_id] = info_dict
else:
pass
def getArtists():
songs = request.json['songs']
### API Key Configuration
from pyechonest import config
config.ECHO_NEST_API_KEY="YZZS9XI0IMOLQRKQ6"
###################### Getting Artists + Song Info ########################
## Basic info on the artists and song from the Echonest API based on a spotify ID sent to the
## app. This part also collects any available information on tempo, danceability and energy
## from the Echonest API for use in subsetting the recommended playlist
from pyechonest import track
artists = []
EchoNestSongId = []
EchoNestArtistId = []
energy = []
dance = []
tempo = []
for i in range(len(songs)):
songs[i] = songs[i].replace("spotify:track:", "spotify-WW:track:")
try:
t = track.track_from_id(songs[i])
EchoNestSongId.append(t.song_id)
EchoNestArtistId.append(t.id)
artists.append(t.artist)
if "energy" in vars(t):
energy.append(t.energy)
if "danceability" in vars(t):
dance.append(t.danceability)
if "tempo" in vars(t):
tempo.append(t.tempo)
except:
continue
###################### Terms Per Artist // All Terms ########################
### Building Terms from Artists
artist_dict = {}
terms = []
from pyechonest import artist
##Creates a dictionary with artists and terms associated with that artist, also creates a vector of all terms
for i in range(len(artists)):
artistTerm = artist.Artist(artists[i]).terms
find_term = []
limitTerms = 4
for artistT in artistTerm:
find_term.append(artistT['name'])
limitTerms -= 1
if limitTerms == 0:
break
artist_dict[artists[i]] = find_term;
terms.extend(find_term)
###################### Weights for Terms ########################
##Creates weights for each term based on the number of times it appeared in artist list
terms_dict = {}
for i in range(len(terms)):
if terms[i] not in terms_dict.items():
find_count = terms.count(terms[i])
terms_dict[terms[i]] = find_count
###################### Weights for Artists ########################
## Adds all of the weights per term per artist to get the overall weight for an artist
## 5 subtracted from total weight (number of terms used per artist, each guarenteed a count of 5)
weights = {}
for key in artist_dict:
getWeight=0
for value in artist_dict[key]:
if value in terms:
getWeight = getWeight+terms_dict[value]
weights[key] = getWeight
#checking weights
#for key in weights:
# print key +":" + str(weights[key])
#NOTE::: If we ever want to add more than 5 songs, we have to order the dictionary and select top 5 artists of terms.
###################### Finding Similar Artists w/Weights ########################
createURL = "http://developer.echonest.com/api/v4/artist/similar?api_key=YZZS9XI0IMOLQRKQ6"
for key in weights:
createURL += "&id=" +artist.Artist(key).id +"^" + str(weights[key])
simMake = urllib2.urlopen(createURL);
echonestSim = simMake.read();
findSimilarArtist = []
for artist in echonestSim.split(":"):
if "name" in artist:
artistShrink = artist.split(",")[0]
artistShrink= artistShrink.translate(None, string.punctuation)
artistShrink = artistShrink.strip()
findSimilarArtist.append(artistShrink)
findSimilarArtists = findSimilarArtist[1:30]
###################### Setting Limits on Audio for Song Rec ########################
### Used to find songs in range of input songs on danceability, enerygy, and tempo, and return full range
### values if there is not enough data to calculate an adjusted range
### NOTE: Currently - tempo and energy not used
if len(dance) > 1:
min_danceability = dance[dance.index(min(dance))]
max_danceability = dance[dance.index(max(dance))]
else:
min_danceability = 0
max_danceability = 1
if len(tempo) > 1:
min_tempo = tempo[tempo.index(min(tempo))]
max_tempo = tempo[tempo.index(max(tempo))]
else:
min_tempo = 0
max_tempo = 500
if len(energy) > 1:
min_energy = energy[energy.index(min(energy))]
max_energy = energy[energy.index(max(energy))]
else:
min_energy = 0
max_energy = 1
###################### Selecting Top Songs for Recommended Artists + Creates Playlist ########################
playlist = []
for i in findSimilarArtists:
createURL="http://developer.echonest.com/api/v4/song/search?api_key=YZZS9XI0IMOLQRKQ6&artist_id=" +i+ "&bucket=id:spotify-WW&bucket=tracks&sort=song_hotttnesss-desc&min_danceability=" + str(min_danceability) + "&max_danceability=" + str(max_danceability) + "&results=5"
getURL = urllib2.urlopen(createURL);
clean_page = getURL.read();
if "spotify-WW:track" in clean_page:
get_track = clean_page[clean_page.index("spotify-WW:track")-1:clean_page.index("spotify-WW:track")+60].replace(":", ",").split(",")[2].translate(None, string.punctuation)
playlist.append("spotify:track:" + get_track)
playlist = jsonify( { 'playlist': playlist} )
return(playlist)
import requests
from pyechonest import config, track
config.ECHO_NEST_API_KEY = "ERAACIJP7XRWDPHSZ"
# f = open("Kanye.mp3",'rb')
# t = track.track_from_file(f,"mp3")
t = track.track_from_id("TREZZIS139E66C60C4")
print t.id
print t.danceability
# print
print t.tempo
def run(self):
log.info('maintenance walker')
log.info('action: %s' % self.action)
if self.action == 'check_media':
from alibrary.models import Media
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter()[0:self.limit]
for item in items:
delete = False
if not item.master:
log.info('no master for: %s' % item)
if self.delete_missing:
log.info('delete item: %s' % item)
delete = True
else:
log.debug('got master for: %s' % item)
log.debug('path: %s' % item.master.path)
#print item.master.path
if os.path.isfile(item.master.path):
size = b = os.path.getsize(item.master.path)
log.debug('filesize: %s' % size)
if size < 10:
log.debug('size too small or zero > delete: %s' % size)
else:
log.debug('file does not exist')
delete = True
if delete and self.delete_missing:
log.info('delete item: %s' % item)
item.delete()
if not delete:
item.status = 1
item.save()
if self.action == 'echonest_media':
from alibrary.models import Media
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter(echonest_id=None)[0:self.limit]
for item in items:
log.info('analyze: %s' % item)
item.echonest_analyze()
if self.action == 'clean_playlists':
from alibrary.models import PlaylistItem
from alibrary.models import Media
items = PlaylistItem.objects.all()
for item in items:
log.info('clean: %s' % item.pk)
if not item.content_object:
log.info('no content object > delete: %s' % item.pk)
item.delete()
# m = Media.objects.get(pk=item.)
if self.action == 'self_check_playlists':
from alibrary.models.playlistmodels import self_check_playlists
# reset
# ps = Playlist.objects.all()
# ps.update(status=1)
self_check_playlists()
if self.action == 'degrade_playlists':
from alibrary.models.playlistmodels import Playlist
ps = Playlist.objects.filter(type='broadcast').exclude(status=1)
ps.update(type='playlist', status=1)
if self.action == 'map_tags':
from alibrary.models import Media
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter()[0:self.limit]
for item in items:
if item.tags.count() < 1:
print item
print 'map release tags'
if item.release and item.release.tags.count() > 0:
item.tags = item.release.tags
item.save()
if self.action == 'echonest_media__':
from alibrary.models import Media
from pyechonest.util import EchoNestAPIError
from pyechonest import track
from pyechonest import config as echonest_config
echonest_config.ECHO_NEST_API_KEY=ECHONEST_API_KEY
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter(status=0)[0:self.limit]
for item in items:
log.info('analyze: %s' % item)
#md5 = '96fa0180d225f14e9f8cbfffbf5eb81d'
t = None
if item.echonest_id:
try:
log.debug('query by echonest id: %s' % item.echonest_id)
t = track.track_from_id(item.echonest_id)
except EchoNestAPIError, e:
print e
if not t:
try:
f = open(item.master.path)
md5 = md5_for_file(f);
log.debug('query by md5: %s' % md5)
t = track.track_from_md5(md5)
except EchoNestAPIError, e:
print e
if not t:
try:
log.debug('query by file: %s' % item.master.path)
f = open(item.master.path)
t = track.track_from_file(f, 'mp3')
except EchoNestAPIError, e:
print e
def echo_nest_update():
"""
Updates the json with all EchoNest data available for this song
('Echo Nest API Error 5: bucket - Invalid parameter:
bucket "id" is not one of "audio", "biographies", "blogs", "doc_counts",
"familiarity", "familiarity_rank", "genre", "hotttnesss",
"hotttnesss_rank", "discovery", "discovery_rank", "images",
"artist_location", "news", "reviews", "songs", "terms", "urls", "video",
"years_active", "id:7digital-US", "id:7digital-AU", "id:7digital-UK",
"id:facebook", "id:fma", "id:emi_bluenote", "id:emi_artists",
"id:twitter", "id:spotify-WW", "id:seatwave",
"id:lyricfind-US", "id:jambase", "id:musixmatch-WW", "id:rdio-US",
"id:rdio-AT", "id:rdio-AU", "id:rdio-BR", "id:rdio-CA", "id:rdio-CH",
"id:rdio-DE", "id:rdio-DK", "id:rdio-ES", "id:rdio-FI", "id:rdio-FR",
"id:rdio-IE", "id:rdio-IT", "id:rdio-NL", "id:rdio-NO", "id:rdio-NZ",
"id:rdio-PT", "id:rdio-SE", "id:emi_electrospective", "id:rdio-EE",
"id:rdio-LT", "id:rdio-LV", "id:rdio-IS", "id:rdio-BE", "id:rdio-MX",
"id:seatgeek", "id:rdio-GB", "id:rdio-CZ", "id:rdio-CO", "id:rdio-PL",
"id:rdio-MY", "id:rdio-HK", "id:rdio-CL", "id:twitter_numeric",
"id:7digital-ES", "id:openaura", "id:spotify", "id:spotify-WW",
"id:tumblr", or "id:<CATALOG ID>"
"""
from pyechonest import config
config.ECHO_NEST_API_KEY = ECHO_NEST_API_KEY
config.CALL_TIMEOUT = 60
while True:
json_data = yield
if json_data == STOP:
break
if json_data.get('echo_nest', ''):
continue
json_data['echo_nest'] = {}
track_title = ''
artist_name = ''
if json_data.get('lastfm', ''):
track_title = json_data['lastfm'].get('track', '')
artist_name = json_data['lastfm'].get('artist', '')
if not track_title:
track_title = json_data['id3'].get('title', '')
if not artist_name:
artist_name = json_data['id3'].get('artist', '')
a = None
try:
if artist_name:
a = artist.Artist(artist_name,
buckets=[
'biographies', 'blogs', 'doc_counts',
'familiarity', 'hotttnesss', 'genre',
'artist_location', 'news', 'reviews',
'urls', 'years_active'
])
json_data['echo_nest']['artist_id'] = a.id
time.sleep(1)
json_data['echo_nest']['artist'] = a.name
time.sleep(1)
json_data['echo_nest']['bios'] = a.biographies
time.sleep(1)
json_data['echo_nest']['blogs'] = a.blogs
time.sleep(1)
json_data['echo_nest']['doc_counts'] = a.doc_counts
time.sleep(1)
json_data['echo_nest']['a_familiarity'] = a.familiarity
time.sleep(1)
json_data['echo_nest']['a_hotttnesss'] = a.hotttnesss
time.sleep(1)
json_data['echo_nest']['news'] = a.news
time.sleep(1)
json_data['echo_nest']['reviews'] = a.reviews
time.sleep(1)
json_data['echo_nest']['urls'] = a.urls
time.sleep(1)
json_data['echo_nest']['years_active'] = a.years_active
time.sleep(1)
json_data['echo_nest']['similar'] = [
str(sim.name) for sim in a.get_similar()
]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if a and track_title:
try:
results = song.search(artist=a.name,
title=track_title,
buckets=[
'audio_summary', 'song_hotttnesss',
'song_discovery'
])
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if results:
json_data['echo_nest']['id'] = results[0].id
time.sleep(1)
json_data['echo_nest']['summary'] =\
results[0].audio_summary
time.sleep(1)
json_data['echo_nest']['s_hotttnesss'] =\
results[0].song_hotttnesss
time.sleep(1)
json_data['echo_nest']['s_discovery'] =\
results[0].song_discovery
time.sleep(1)
time.sleep(1)
tr = None
if json_data['echo_nest'].get('id', ''):
try:
tr = track.track_from_id(json_data['echo_nest']['id'])
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
if not tr:
continue
try:
tr.get_analysis()
time.sleep(1)
json_data['echo_nest']['analysis'] = {}
json_data['echo_nest']['analysis']['acousticness'] =\
tr.acousticness
json_data['echo_nest']['analysis']['analysis_url'] =\
tr.analysis_url
json_data['echo_nest']['analysis']['danceability'] =\
tr.danceability
json_data['echo_nest']['analysis']['duration'] =\
tr.duration
json_data['echo_nest']['analysis']['energy'] = tr.energy
json_data['echo_nest']['analysis']['key'] = tr.key
json_data['echo_nest']['analysis']['liveness'] =\
tr.liveness
json_data['echo_nest']['analysis']['loudness'] =\
tr.loudness
json_data['echo_nest']['analysis']['mode'] = tr.mode
json_data['echo_nest']['analysis']['speechiness'] =\
tr.speechiness
json_data['echo_nest']['analysis']['tempo'] =\
tr.tempo
json_data['echo_nest']['analysis']['time_signature'] =\
tr.time_signature
json_data['echo_nest']['analysis']['valence'] = tr.valence
json_data['echo_nest']['analysis']['analysis_channels'] =\
tr.analysis_channels
json_data['echo_nest']['analysis']['bars'] = tr.bars
json_data['echo_nest']['analysis']['beats'] = tr.beats
json_data['echo_nest']['analysis']['start_of_fade_out'] =\
tr.start_of_fade_out
json_data['echo_nest']['analysis']['end_of_fade_in'] =\
tr.end_of_fade_in
json_data['echo_nest']['analysis']['key_confidence'] =\
tr.key_confidence
json_data['echo_nest']['analysis']['meta'] = tr.meta
json_data['echo_nest']['analysis']['mode_confidence'] =\
tr.mode_confidence
json_data['echo_nest']['analysis']['num_samples'] =\
tr.num_samples
json_data['echo_nest']['analysis']['sections'] =\
tr.sections
json_data['echo_nest']['analysis']['segments'] =\
tr.segments
json_data['echo_nest']['analysis']['synchstring'] =\
tr.synchstring
json_data['echo_nest']['analysis']['tatums'] =\
tr.tatums
json_data['echo_nest']['analysis']['tempo_confidence'] =\
tr.tempo_confidence
json_data['echo_nest']['analysis']['sign_confidence'] =\
tr.time_signature_confidence
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
except Exception as e:
print(e)
time.sleep(1)
if a:
try:
json_data['echo_nest']['basic_song_list'] =\
['{} - {}'.format(s.artist_name, s.title) for s in
playlist.basic(type='song-radio',
artist_id=a.id,
song_id=tr.id)]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
try:
json_data['echo_nest']['basic_artist_list'] =\
['{} - {}'.format(s.artist_name, s.title) for s in
playlist.basic(artist_id=a.id, song_id=tr.id)]
time.sleep(1)
except EchoNestException as e:
print(e)
except EchoNestIOError as e:
print(e)
except socket.timeout:
pass
time.sleep(1)
# Uncomment to set the API key explicitly. Otherwise Pyechonest will
# look in the ECHO_NEST_API_KEY environment variable for the key.
#from pyechonest import config
#config.ECHO_NEST_API_KEY='YOUR API KEY'
from pyechonest import song, track
rof_results = song.search(title='Ring of Fire', artist='Johnny Cash', buckets=['id:7digital'], limit=True)
if rof_results:
rof = rof_results[0]
rof_tracks = rof.get_tracks('7digital')
if rof_tracks:
roft = track.track_from_id(rof_tracks[0]['id'])
for attr in ['analysis_channels', 'analysis_sample_rate', 'analysis_url', 'artist', 'audio_md5', 'catalog', 'danceability', 'duration', 'end_of_fade_in', 'energy', 'foreign_id', 'foreign_release_id', 'id', 'key', 'key_confidence', 'loudness', 'md5', 'meta', 'mode', 'mode_confidence', 'num_samples', 'preview_url', 'release_image', 'sample_md5', 'song_id', 'start_of_fade_out', 'status', 'tempo', 'tempo_confidence', 'time_signature', 'time_signature_confidence', 'title']:
print '%-30s %s' % (attr, getattr(roft, attr))
print ''
for dicts_attr in ['bars', 'beats', 'sections', 'segments', 'tatums']:
print '"%s" example dict:' % (dicts_attr)
for key, val in getattr(roft, dicts_attr)[0].iteritems():
print ' %-26s %s' % (key, val)
print ''
else:
print 'No tracks found.'
else:
print 'No songs found.'
