One handler is created per model instead of per bound image spec.
This cuts down on the number of handlers created, and also offloads the
policing of the handlers in memory to the signal framework. Since they are no
longer being created per spec, the handlers can be weakly referenced.
Removed the save and clear_cache methods from ImageModel (along with helpers).
Now, whenever an ImageSpec is contributed to a model, handlers are created for
the post_save and post_delete signals. The post_save handler does the work of
running the ImageSpec processors and caching the resulting file, while the
post_delete handler does the work cleaning up the cached files.
The Format processor was really a special case and didn't do any
processing at all. Instead, ImageSpec just knew to look for it and
responded accordingly. Therefore, it's been replaced with a `format`
property on ImageSpec. This warranted a deeper look at how the format
and extension were being deduced (when not explicitly provided); the
results are documented in-code, though the goal was "no surprises."
By creating the Descriptor using contribute_to_class (instead of in
ImageModelBase's __init__), we take the first step towards eliminating the need
to extend ImageModel at all.
Removed the cache_dir, cache_filename_fields and cache_filename_format
properties of IKOptions. While these were very powerful, I felt that it was
unnecessarily confusing to have two properties (cache_dir and
cache_filename_format) that determine the filename. The new cache_to property is
modeled after ImageField's upload_to and behaves almost identically (the only
exception being that a callable value receives different arguments). In
addition, I felt that the interpolation of model properties provided by
cache_filename_fields, though useful, would be better handled by a utility
function outside of this library.
This works kind of like Django's models' _default_manager. If your specs don't
specify an image_field, and your IKOptions don't specify a default_image_field,
the first ImageField your model defines will be used.
