Implement the basic AcousticBrainz Submit plugin

beetsplug/absubmit.py

@@ -0,0 +1,173 @@
+# -*- 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 hashlib
+import json
+import os
+import subprocess
+import tempfile
+
+import distutils
+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,
+            # needed to calculate the sha1 hash.
+            self.extractor = distutils.spawn.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()
+
+    supported_formats = {'mp3', 'ogg', 'oga', 'flac', 'mp4', 'm4a', 'm4r',
+                         'm4b', 'm4p', 'aac', 'wma', 'asf', 'mpc', 'wv',
+                         'spx', 'tta', '3g2', 'aif', 'aiff', 'ape'}
+
+    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
+        # If file format is not supported skip it.
+        if item['format'].lower() not in self.supported_formats:
+            self._log.info(u'Not analysing {}, file not in '
+                           u'supported format.', 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.
+            try:
+                call([self.extractor, util.syspath(item.path), filename])
+            except ABSubmitError as e:
+                self._log.error(
+                    u'Failed to analyse {item} for AcousticBrainz: {error}',
+                    item=item, error=e
+                )
+                return None
+            with open(filename) as tmp_file:
+                analysis = json.loads(tmp_file.read())
+            # 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:
+                # errno 2 means file does not exist, just ignore this error.
+                if e.errno != 2:
+                    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)

docs/plugins/absubmit.rst

@@ -0,0 +1,31 @@
+AcousticBrainz Submit Plugin
+============================
+
+The `absubmit` plugin uses the `streaming_extractor_music`_ program to analyze an audio file and calculate different acoustic properties of the audio. The plugin then uploads this metadata to the AcousticBrainz server. The plugin does this when calling the ``beet absumbit [QUERY]`` command or on importing if the `auto` configuration option is set to ``yes``.
+
+Installation
+------------
+
+The `absubmit` plugin requires the `streaming_extractor_music`_ program to run. Its source can be found on `GitHub`_, and while it is possible to compile the extractor from source, AcousticBrainz would prefer if you used their binary (see the AcousticBrainz `FAQ`_).
+
+The `absubmit` also plugin requires `requests`_, which you can install using `pip_` by typing:
+
+    pip install requests
+
+After installing both the extractor binary and requests you can enable the plugin ``absubmit`` in your configuration (see :ref:`using-plugins`).
+
+Configuration
+-------------
+
+To configure the plugin, make a ``absubmit:`` section in your configuration file. The available options are:
+
+- **auto**: Analyze every file on import. Otherwise, you need to use the ``beet absubmit`` command explicitly.
+  Default: ``no``
+- **extractor**: The path to the `streaming_extractor_music`_ binary.
+  Default: search for the program in your ``$PATH``
+
+.. _streaming_extractor_music: http://acousticbrainz.org/download
+.. _FAQ: http://acousticbrainz.org/faq
+.. _pip: http://www.pip-installer.org/
+.. _requests: http://docs.python-requests.org/en/master/
+.. _github: https://github.com/MTG/essentia

docs/plugins/index.rst

@@ -38,6 +38,7 @@ like this::
 .. toctree::
    :hidden:
 
+   absubmit
    acousticbrainz
    badfiles
    beatport
@@ -105,6 +106,7 @@ Autotagger Extensions
 Metadata
 --------
 
+* :doc:`absubmit`: Analyse audio with the `streaming_extractor_music`_ program and submit the metadata to the AcousticBrainz server
 * :doc:`acousticbrainz`: Fetch various AcousticBrainz metadata
 * :doc:`bpm`: Measure tempo using keystrokes.
 * :doc:`edit`: Edit metadata from a text editor.
@@ -128,6 +130,7 @@ Metadata
 * :doc:`zero`: Nullify fields by pattern or unconditionally.
 
 .. _KeyFinder: http://www.ibrahimshaath.co.uk/keyfinder/
+.. _streaming_extractor_music: http://acousticbrainz.org/download
 
 Path Formats
 ------------

setup.py

@@ -111,6 +111,7 @@ def build_manpages():
 
     # Plugin (optional) dependencies:
     extras_require={
+        'absubmit': ['requests'],
         'fetchart': ['requests'],
         'chroma': ['pyacoustid'],
         'discogs': ['discogs-client>=2.1.0'],
@@ -126,6 +127,7 @@ def build_manpages():
     # Non-Python/non-PyPI plugin dependencies:
     # convert: ffmpeg
     # bpd: python-gi and GStreamer
+    # absubmit: extractor binary from http://acousticbrainz.org/download
 
     classifiers=[
         'Topic :: Multimedia :: Sound/Audio',