def create_track_file(maindir, trackid, track, song, artist, mbconnect=None):
"""
Main function to create an HDF5 song file.
You got to have the track, song and artist already.
If you pass an open connection to the musicbrainz database, we also use it.
Returns True if song was created, False otherwise.
False can mean another thread is already doing that song.
We also check whether the path exists.
INPUT
maindir - main directory of the Million Song Dataset
trackid - Echo Nest track id of the track object
track - pyechonest track object
song - pyechonest song object
artist - pyechonest artist object
mbconnect - open musicbrainz pg connection
RETURN
True if a track file was created, False otherwise
"""
hdf5_path = os.path.join(maindir, path_from_trackid(trackid))
if os.path.exists(hdf5_path):
return False # file already exists, no stress
hdf5_path_tmp = hdf5_path + '_tmp'
# lock the file
got_lock = get_lock_track(trackid)
if not got_lock:
return False # someone is taking care of that file
if os.path.exists(hdf5_path):
release_lock_track(trackid)
return False # got the lock too late, file exists
# count errors (=tries), stop after 100 tries
try_cnt = 0
# create file and fill it
try:
while True: # try until we make it work!
try:
# we try one more time
try_cnt += 1
if not os.path.isdir(os.path.split(hdf5_path)[0]):
os.makedirs(os.path.split(hdf5_path)[0])
# check / delete tmp file if exist
if os.path.isfile(hdf5_path_tmp):
os.remove(hdf5_path_tmp)
# create tmp file
HDF5.create_song_file(hdf5_path_tmp)
h5 = HDF5.open_h5_file_append(hdf5_path_tmp)
HDF5.fill_hdf5_from_artist(h5, artist)
HDF5.fill_hdf5_from_song(h5, song)
HDF5.fill_hdf5_from_track(h5, track)
if mbconnect is not None:
HDF5.fill_hdf5_from_musicbrainz(h5, mbconnect)
# TODO billboard? lastfm? ...?
h5.close()
except KeyboardInterrupt:
close_creation()
raise
# we dont panic, delete file, wait and retry
except Exception as e:
# close hdf5
try:
h5.close()
except NameError, ValueError:
pass
# delete path
try:
os.remove(hdf5_path_tmp)
except IOError:
pass
# print and wait
print 'ERROR creating track:', trackid, 'on', time.ctime(
), '(pid=' + str(os.getpid()) + ')'
print e
if try_cnt < 100:
print '(try again in', SLEEPTIME, 'seconds)'
time.sleep(SLEEPTIME)
continue
# give up
else:
print 'we give up after', try_cnt, 'tries'
release_lock_track(trackid)
return False
# move tmp file to real file
shutil.move(hdf5_path_tmp, hdf5_path)
# release lock
release_lock_track(trackid)
break
# KeyboardInterrupt, we delete file, clean things up
except KeyboardInterrupt:
# close hdf5
try:
h5.close()
except NameError, ValueError:
pass
# delete path
try:
if os.path.isfile(hdf5_path_tmp):
os.remove(hdf5_path_tmp)
if os.path.isfile(hdf5_path):
os.remove(hdf5_path)
except IOError:
pass
raise
def convert_one_song(audiofile,output,mbconnect=None,verbose=0,DESTROYAUDIO=False):
"""
PRINCIPAL FUNCTION
Converts one given audio file to hdf5 format (saved in 'output')
by uploading it to The Echo Nest API
INPUT
audiofile - path to a typical audio file (wav, mp3, ...)
output - nonexisting hdf5 path
mbconnect - if not None, open connection to musicbrainz server
verbose - if >0 display more information
DESTROYAUDIO - Careful! deletes audio file if everything went well
RETURN
1 if we think a song is created, 0 otherwise
"""
# inputs + sanity checks
if not os.path.exists(audiofile):
print('ERROR: song file does not exist:',songfile)
return 0
if os.path.exists(output):
print('ERROR: hdf5 output file already exist:',output,', delete or choose new path')
return 0
# get EN track / song / artist for that song
if verbose>0: print('get analysis for file:',audiofile)
track = trackEN.track_from_filename(audiofile)
song_id = track.song_id
song = songEN.Song(song_id)
if verbose>0: print('found song:',song.title,'(',song_id,')')
artist_id = song.artist_id
artist = artistEN.Artist(artist_id)
if verbose>0: print('found artist:',artist.name,'(',artist_id,')')
# hack to fill missing values
try:
track.foreign_id
except AttributeError:
track.__setattr__('foreign_id','')
if verbose>0: print('no track foreign_id found')
try:
track.foreign_release_id
except AttributeError:
track.__setattr__('foreign_release_id','')
if verbose>0: print('no track foreign_release_id found')
# create HDF5 file
if verbose>0: print('create HDF5 file:',output)
HDF5.create_song_file(output,force=False)
# fill hdf5 file from track
if verbose>0:
if mbconnect is None:
print('fill HDF5 file with info from track/song/artist')
else:
print('fill HDF5 file with info from track/song/artist/musicbrainz')
h5 = HDF5.open_h5_file_append(output)
HDF5.fill_hdf5_from_artist(h5,artist)
HDF5.fill_hdf5_from_song(h5,song)
HDF5.fill_hdf5_from_track(h5,track)
if not mbconnect is None:
HDF5.fill_hdf5_from_musicbrainz(h5,mbconnect)
h5.close()
# done
if DESTROYAUDIO:
if verbose>0: print('We remove audio file:',audiofile)
os.remove(audiofile)
return 1
def create_track_file(maindir,trackid,track,song,artist,mbconnect=None):
"""
Main function to create an HDF5 song file.
You got to have the track, song and artist already.
If you pass an open connection to the musicbrainz database, we also use it.
Returns True if song was created, False otherwise.
False can mean another thread is already doing that song.
We also check whether the path exists.
INPUT
maindir - main directory of the Million Song Dataset
trackid - Echo Nest track id of the track object
track - pyechonest track object
song - pyechonest song object
artist - pyechonest artist object
mbconnect - open musicbrainz pg connection
RETURN
True if a track file was created, False otherwise
"""
hdf5_path = os.path.join(maindir,path_from_trackid(trackid))
if os.path.exists( hdf5_path ):
return False # file already exists, no stress
hdf5_path_tmp = hdf5_path + '_tmp'
# lock the file
got_lock = get_lock_track(trackid)
if not got_lock:
return False # someone is taking care of that file
if os.path.exists( hdf5_path ):
release_lock_track(trackid)
return False # got the lock too late, file exists
# count errors (=tries), stop after 100 tries
try_cnt = 0
# create file and fill it
try:
while True: # try until we make it work!
try:
# we try one more time
try_cnt += 1
if not os.path.isdir( os.path.split(hdf5_path)[0] ):
os.makedirs( os.path.split(hdf5_path)[0] )
# check / delete tmp file if exist
if os.path.isfile(hdf5_path_tmp):
os.remove(hdf5_path_tmp)
# create tmp file
HDF5.create_song_file(hdf5_path_tmp)
h5 = HDF5.open_h5_file_append(hdf5_path_tmp)
HDF5.fill_hdf5_from_artist(h5,artist)
HDF5.fill_hdf5_from_song(h5,song)
HDF5.fill_hdf5_from_track(h5,track)
if mbconnect is not None:
HDF5.fill_hdf5_from_musicbrainz(h5,mbconnect)
# TODO billboard? lastfm? ...?
h5.close()
except KeyboardInterrupt:
close_creation()
raise
# we dont panic, delete file, wait and retry
except Exception as e:
# close hdf5
try:
h5.close()
except NameError,ValueError:
pass
# delete path
try:
os.remove( hdf5_path_tmp )
except IOError:
pass
# print and wait
print 'ERROR creating track:',trackid,'on',time.ctime(),'(pid='+str(os.getpid())+')'
print e
if try_cnt < 100:
print '(try again in',SLEEPTIME,'seconds)'
time.sleep(SLEEPTIME)
continue
# give up
else:
print 'we give up after',try_cnt,'tries'
release_lock_track(trackid)
return False
# move tmp file to real file
shutil.move(hdf5_path_tmp, hdf5_path)
# release lock
release_lock_track(trackid)
break
# KeyboardInterrupt, we delete file, clean things up
except KeyboardInterrupt:
# close hdf5
try:
h5.close()
except NameError,ValueError:
pass
# delete path
try:
if os.path.isfile( hdf5_path_tmp ):
os.remove( hdf5_path_tmp )
if os.path.isfile( hdf5_path ):
os.remove( hdf5_path )
except IOError:
pass
raise
def convert_one_song(audiofile,
output,
mbconnect=None,
verbose=0,
DESTROYAUDIO=False):
"""
PRINCIPAL FUNCTION
Converts one given audio file to hdf5 format (saved in 'output')
by uploading it to The Echo Nest API
INPUT
audiofile - path to a typical audio file (wav, mp3, ...)
output - nonexisting hdf5 path
mbconnect - if not None, open connection to musicbrainz server
verbose - if >0 display more information
DESTROYAUDIO - Careful! deletes audio file if everything went well
RETURN
1 if we think a song is created, 0 otherwise
"""
# inputs + sanity checks
if not os.path.exists(audiofile):
print(('ERROR: song file does not exist:', songfile))
return 0
if os.path.exists(output):
print(('ERROR: hdf5 output file already exist:', output,
', delete or choose new path'))
return 0
# get EN track / song / artist for that song
if verbose > 0: print(('get analysis for file:', audiofile))
track = trackEN.track_from_filename(audiofile)
song_id = track.song_id
song = songEN.Song(song_id)
if verbose > 0: print(('found song:', song.title, '(', song_id, ')'))
artist_id = song.artist_id
artist = artistEN.Artist(artist_id)
if verbose > 0: print(('found artist:', artist.name, '(', artist_id, ')'))
# hack to fill missing values
try:
track.foreign_id
except AttributeError:
track.__setattr__('foreign_id', '')
if verbose > 0: print('no track foreign_id found')
try:
track.foreign_release_id
except AttributeError:
track.__setattr__('foreign_release_id', '')
if verbose > 0: print('no track foreign_release_id found')
# create HDF5 file
if verbose > 0: print(('create HDF5 file:', output))
HDF5.create_song_file(output, force=False)
# fill hdf5 file from track
if verbose > 0:
if mbconnect is None:
print('fill HDF5 file with info from track/song/artist')
else:
print(
'fill HDF5 file with info from track/song/artist/musicbrainz')
h5 = HDF5.open_h5_file_append(output)
HDF5.fill_hdf5_from_artist(h5, artist)
HDF5.fill_hdf5_from_song(h5, song)
HDF5.fill_hdf5_from_track(h5, track)
if not mbconnect is None:
HDF5.fill_hdf5_from_musicbrainz(h5, mbconnect)
h5.close()
# done
if DESTROYAUDIO:
if verbose > 0: print(('We remove audio file:', audiofile))
os.remove(audiofile)
return 1
# the goal is to get the feature information for the learn subbase of rwc audio samples
input_dir = '/home/manu/workspace/databases/genres/jazz/'
output_dir = '/home/manu/workspace/databases/genres/jazz/hdf5/'
# Single file is working, now loop on all files from the learning directory17
#from pyechonest import track
for audiofile in features.get_filepaths(input_dir, ext='.au'):
print "Starting work on ", audiofile
output = output_dir + os.path.splitext(os.path.split(audiofile)[-1])[0] + '.h5'
if os.path.exists(output):
continue
file_object = open(audiofile)
curtrack = track.track_from_file(file_object, 'au', force_upload=True)
#
HDF5.create_song_file(output,force=False)
h5 = HDF5.open_h5_file_append(output)
# HACK we need to fill missing values
curtrack.__setattr__('foreign_id','')
curtrack.__setattr__('foreign_release_id','')
curtrack.__setattr__('audio_md5','')
HDF5.fill_hdf5_from_track(h5,curtrack)
h5.close()
del h5
# first testing on a single song
#audiofile = input_dir + 'rwc-g-m01_1.wav'
#output = output_dir + 'rwc-g-m01_1.h5'
# MSdB API not convenient need to identify the song
#from enpyapi_to_hdf5 import convert_one_song