Metadata-Version: 1.1
Name: pyacoustid
Version: 1.1.2
Summary: bindings for Chromaprint acoustic fingerprinting and the Acoustid API
Home-page: https://github.com/sampsyo/pyacoustid
Author: Adrian Sampson
Author-email: adrian@radbox.org
License: MIT
Description: Chromaprint and Acoustid for Python
        ===================================
        
        `Chromaprint`_ and its associated `Acoustid`_ Web service make up a
        high-quality, open-source acoustic fingerprinting system. This package provides
        Python bindings for both the fingerprinting algorithm library, which is written
        in C but portable, and the Web service, which provides fingerprint lookups.
        
        .. _Chromaprint: http://acoustid.org/
        .. _Acoustid: http://acoustid.org/chromaprint
        
        
        Installation
        ------------
        
        This library works with Python 2 (2.7+, possibly also 2.6) and Python 3
        (3.3+).
        
        First, install the `Chromaprint`_ fingerprinting library by `Lukas Lalinsky`__.
        (The library itself depends on an FFT library, but it's smart enough to use an
        algorithm from software you probably already have installed; see the Chromaprint
        page for details.) This module can use either the Chromaprint dynamic library or
        the ``fpcalc`` command-line tool, which itself depends on `libavcodec`_. If you
        use ``fpcalc``, either ensure that it is on your ``$PATH`` or set the ``FPCALC``
        environment variable to its location.
        
        __ lukas_
        .. _lukas: http://oxygene.sk/lukas/
        .. _libavcodec: http://ffmpeg.org/
        
        Then you can install this library from `PyPI`_ using `pip`_::
        
            $ pip install pyacoustid
        
        This library uses `audioread`_ to do audio decoding when not using ``fpcalc``
        and `requests`_ to talk to the HTTP API (pip should automatically install
        these dependencies).
        
        .. _pip: http://www.pip-installer.org/
        .. _PyPI: http://pypi.python.org/
        .. _audioread: https://github.com/sampsyo/audioread
        .. _requests: http://python-requests.org
        
        
        Running
        -------
        
        You can run the included demonstration script, ``aidmatch.py``, to test your
        installation::
        
            $ python aidmatch.py mysterious_music.mp3
        
        This will show the top metadata match from Acoustid's database. The script uses
        `audioread`_ to decode music, so it should transparently use a media library
        available on your system (GStreamer, FFmpeg, MAD, or Core Audio).
        
        
        Using in Your Code
        ------------------
        
        The simplest way to use pyacoustid to identify audio files is to call the
        ``match`` function::
        
            >>> import acoustid
            >>> for score, recording_id, title, artist in acoustid.match(apikey, path):
            >>>     ...
        
        This convenience function uses `audioread`_ to decode audio and parses the
        response for you, pulling out the most important track metadata. It returns in
        iterable over tuples of relevant information. Everything happens in one fell
        swoop. There are also a number of "smaller" functions you can use to perform
        parts of the process:
        
        - ``fingerprint(samplerate, channels, pcmiter)``: Generate a fingerprint for raw
          audio data. Specify the audio parameters and give an iterable containing
          blocks of PCM data.
        - ``fingerprint_file(path)``: Using either the Chromaprint dynamic library or
          the ``fpcalc`` command-line tool, fingerprint an audio file. Returns a pair
          consisting of the file's duration and its fingerprint.
        - ``lookup(apikey, fingerprint, duration)``: Make a request to the `Acoustid`_
          API to look up the fingerprint returned by the previous function. An API key
          is required, as is the length, in seconds, of the source audio. Returns a
          parsed JSON response.
        - ``parse_lookup_result(data)``: Given a parsed JSON response, return an
          iterator over tuples containing the match score (a float between 0 and 1), the
          MusicBrainz recording ID, title, and artist name for each match.
        
        The module internally performs thread-safe API rate limiting to 3 queries per
        second whenever the Web API is called, in accordance with the `Web service
        documentation`_.
        
        If you're running your own Acoustid database server, you can set the base URL
        for all API calls with the ``set_base_url`` function.
        
        Calls to the library can raise ``AcoustidError`` exceptions of two subtypes:
        ``FingerprintGenerationError`` and ``WebServiceError``. Catch these exceptions
        if you want to proceed when audio can't be decoded or no match is found on the
        server. ``NoBackendError``, a subclass of ``FingerprintGenerationError``, is
        used when the Chromaprint library or fpcalc command-line tool cannot be found.
        
        .. _Web service documentation: http://acoustid.org/webservice
        
        
        Version History
        ---------------
        
        1.1.2
          Fix a possible crash on Unicode text in Python 2 in a non-Unicode locale.
          Look for version "1" of the Chromaprint shared library file.
        
        1.1.1
          Fix a possible setup error on Python 3 (thanks to Simon Chopin).
        
        1.1.0
          Include ``fpcalc.py`` script in source distributions.
          Add Python 3 support (thanks to Igor Tsarev).
        
        1.0.0
          Include ``fpcalc.py``, a script mimicking the ``fpcalc`` program from the
          Chromaprint package.
          Handle a ``UnicodeDecodeError`` raised when using the ``fpcalc`` backend on
          Windows with Unicode filenames.
          Standard error output from ``fpcalc`` is suppressed.
        
        0.7
          Properly encode Unicode parameters (resolves a ``UnicodeEncodeError``
          in fingerprint submission).
          Parse all recordings for each Acoustid lookup result.
        
        0.6
          Add a new function, ``fingerprint_file``, that automatically selects a
          backend for fingerprinting a single file.
        
        0.5
          Fix response parsing when recording has no artists or title.
          Fix compatibility with Python < 2.7.
          Add specific ``NoBackendError`` exception.
        
        0.4
          Fingerprinting can now fall back to using the ``fpcalc`` command-line tool
          instead of the Chromaprint dynamic library so the library can be used with
          the binary distributions (thanks to Lukas Lalinsky).
          Fingerprint submission (thanks to Alastair Porter).
          Data chunks can now be buffers as well as bytestrings (fixes compatibility
          with pymad).
        
        0.3
          Configurable API base URL.
          Result parser now generates all results instead of returning just one.
          Find the chromaprint library on Cygwin.
          New module names: ``chromaprint`` and ``acoustid`` (no package).
        
        0.2
          Compress HTTP requests and responses.
          Limit audio decoding to 120 seconds.
          Return score from convenience function.
        
        0.1
          Initial release.
        
        
        Credits
        -------
        
        This library is by Adrian Sampson. Chromaprint and Acoustid are by `Lukas
        Lalinsky`__. This package includes the original `ctypes`_-based bindings
        written by Lukas. The entire library is made available under the `MIT license`_.
        pyacoustid was written to be used with `beets`_, which you should probably check
        out.
        
        __ lukas_
        .. _ctypes: http://docs.python.org/library/ctypes.html
        .. _beets: http://beets.radbox.org/
        .. _MIT license: http://www.opensource.org/licenses/mit-license.php
        
Platform: ALL
Classifier: Topic :: Multimedia :: Sound/Audio :: Conversion
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
