Metadata-Version: 1.1
Name: optisorl
Version: 0.1.2
Summary: Backend plugin for sorl-thumbnail that optimizes thumbnails
Home-page: https://github.com/peterbe/optisorl
Author: Peter Bengtsson
Author-email: mail@peterbe.com
License: BSD
Description: optisorl
        ========
        
        Copyright Peter Bengtsson, mail@peterbe.com, 2015
        
        |Travis|
        
        License: BSD
        
        About optisorl
        --------------
        
        `sorl-thumbnail <https://pypi.python.org/pypi/sorl-thumbnail>`_ is a
        great Django library that takes your stored images and automatically
        convert them into desired sized thumbnails and store them with nice
        names in the ``MEDIA_ROOT``. The problem is that the engines that do
        the resizing often doesn't do an amazing job of optimizing them.
        Usually optimizing an image means carefully deleting things the human
        eye can't notice anyway. This becomes incredibly relevant when the
        thumbnail you create is so small in resolution that the user really
        stands very little chance to notice.
        
        This package, is a pluggable backend to ``sorl-thumbnail`` that
        attempts to do a good job of optimizing the generated thumbnail just
        right after it has been written to disk.
        
        
        Optimizing PNGs
        ---------------
        
        ``optisorl`` uses a binary called `pngquant <https://pngquant.org/>`_
        which is a command line tool that do lossy compression of PNG images
        and supports alpha transparency. ``pngquant`` is
        BSD licensed. It's easy to install on most systems. For example
        ``brew install pngquant`` or ``apt-get install pngquant``.
        
        What happens is that when ``optisorl`` notices that a thumbnail was
        created it (and stored in ``MEDIA_ROOT``) it then takes that file and
        executes ``pngquant`` something like this:
        
        ::
        
            pngquant -o /path/file.tmp.png --skip-if-larger -- /path/file.png
        
        Note the ``--skip-if-larger`` which means that if the thumbnail is really
        really small already the resulting optimization might not be any better
        and it thus omits doing an optimization.
        
        If you want to override the location of the executable ``pngquant`` you
        can set this setting for example:
        
        .. code:: python
        
            # in settings.py or equivalent
        
            PNGQUANT_LOCATION = '/opt/special/bin/pngquant2.0'
        
        
        Optimizing GIFs
        ---------------
        
        ``optisorl`` uses `gifsicle <http://www.lcdf.org/gifsicle/>`_ with
        level 3 optimization. ``gifsicle`` is GPL licensed but use is not
        restricted by a license. To install it use ``brew install gifsicle``
        or ``apt-get install gifsicle``.
        
        To override where the ``gifsicle`` executable is located you can set
        in your settings:
        
        .. code:: python
        
            # in settings.py or equivalent
        
            GIFSICLE_LOCATION = '/opt/special/bin/gifsicle'
        
        
        If you want to disable all optimization of GIFs just set
        ``GIFSICLE_LOCATION`` (in your ``settings.py``) to ``None`` or ``False``.
        
        Limitations
        -----------
        
        Help is most welcome. At the moment...
        
        * Does not support S3 storage
        
        * Unable to NOT optimize images
        
        * Not possible to override certain ``pngquant`` parameters
        
        * Only able to optimize ``.png`` thumbnails
        
        
        .. |Travis| image:: https://travis-ci.org/peterbe/optisorl.png?branch=master
           :target: https://travis-ci.org/peterbe/optisorl
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Software Development :: Libraries :: Python Modules
