/usr/share/beets/beetsplug/absubmit.py is in beets 1.4.6-2.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | # -*- coding: utf-8 -*-
# This file is part of beets.
# Copyright 2016, Pieter Mulder.
#
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# distribute, sublicense, and/or sell copies of the Software, and to
# permit persons to whom the Software is furnished to do so, subject to
# the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
"""Calculate acoustic information and submit to AcousticBrainz.
"""
from __future__ import division, absolute_import, print_function
import errno
import hashlib
import json
import os
import subprocess
import tempfile
from distutils.spawn import find_executable
import requests
from beets import plugins
from beets import util
from beets import ui
class ABSubmitError(Exception):
"""Raised when failing to analyse file with extractor."""
def call(args):
"""Execute the command and return its output.
Raise a AnalysisABSubmitError on failure.
"""
try:
return util.command_output(args)
except subprocess.CalledProcessError as e:
raise ABSubmitError(
u'{0} exited with status {1}'.format(args[0], e.returncode)
)
class AcousticBrainzSubmitPlugin(plugins.BeetsPlugin):
def __init__(self):
super(AcousticBrainzSubmitPlugin, self).__init__()
self.config.add({'extractor': u''})
self.extractor = self.config['extractor'].as_str()
if self.extractor:
self.extractor = util.normpath(self.extractor)
# Expicit path to extractor
if not os.path.isfile(self.extractor):
raise ui.UserError(
u'Extractor command does not exist: {0}.'.
format(self.extractor)
)
else:
# Implicit path to extractor, search for it in path
self.extractor = 'streaming_extractor_music'
try:
call([self.extractor])
except OSError:
raise ui.UserError(
u'No extractor command found: please install the '
u'extractor binary from http://acousticbrainz.org/download'
)
except ABSubmitError:
# Extractor found, will exit with an error if not called with
# the correct amount of arguments.
pass
# Get the executable location on the system, which we need
# to calculate the SHA-1 hash.
self.extractor = find_executable(self.extractor)
# Calculate extractor hash.
self.extractor_sha = hashlib.sha1()
with open(self.extractor, 'rb') as extractor:
self.extractor_sha.update(extractor.read())
self.extractor_sha = self.extractor_sha.hexdigest()
base_url = 'https://acousticbrainz.org/api/v1/{mbid}/low-level'
def commands(self):
cmd = ui.Subcommand(
'absubmit',
help=u'calculate and submit AcousticBrainz analysis'
)
cmd.func = self.command
return [cmd]
def command(self, lib, opts, args):
# Get items from arguments
items = lib.items(ui.decargs(args))
for item in items:
analysis = self._get_analysis(item)
if analysis:
self._submit_data(item, analysis)
def _get_analysis(self, item):
mbid = item['mb_trackid']
# If file has no mbid skip it.
if not mbid:
self._log.info(u'Not analysing {}, missing '
u'musicbrainz track id.', item)
return None
# Temporary file to save extractor output to, extractor only works
# if an output file is given. Here we use a temporary file to copy
# the data into a python object and then remove the file from the
# system.
tmp_file, filename = tempfile.mkstemp(suffix='.json')
try:
# Close the file, so the extractor can overwrite it.
os.close(tmp_file)
try:
call([self.extractor, util.syspath(item.path), filename])
except ABSubmitError as e:
self._log.warning(
u'Failed to analyse {item} for AcousticBrainz: {error}',
item=item, error=e
)
return None
with open(filename, 'rb') as tmp_file:
analysis = json.load(tmp_file)
# Add the hash to the output.
analysis['metadata']['version']['essentia_build_sha'] = \
self.extractor_sha
return analysis
finally:
try:
os.remove(filename)
except OSError as e:
# ENOENT means file does not exist, just ignore this error.
if e.errno != errno.ENOENT:
raise
def _submit_data(self, item, data):
mbid = item['mb_trackid']
headers = {'Content-Type': 'application/json'}
response = requests.post(self.base_url.format(mbid=mbid),
json=data, headers=headers)
# Test that request was successful and raise an error on failure.
if response.status_code != 200:
try:
message = response.json()['message']
except (ValueError, KeyError) as e:
message = u'unable to get error message: {}'.format(e)
self._log.error(
u'Failed to submit AcousticBrainz analysis of {item}: '
u'{message}).', item=item, message=message
)
else:
self._log.debug(u'Successfully submitted AcousticBrainz analysis '
u'for {}.', item)
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