pil

pilkit

Utilities and processors built for, and on top of PIL

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PILKit is a collection of utilities for working with PIL (the Python Imaging Library).

One of its main features is a set of processors which expose a simple interface for performing manipulations on PIL images.

Looking for more advanced processors? Check out Instakit_!

For the complete documentation on the latest stable version of PILKit, see PILKit on RTD_.

.. image:: https://github.com/matthewwithanm/pilkit/workflows/Python%20CI/badge.svg :target: https://github.com/matthewwithanm/pilkit/actions?query=workflow%3A%22Python+CI%22

.. PILKit on RTD: http://pilkit.readthedocs.org .. Instakit: https://github.com/fish2000/instakit

Installation

  1. Install PIL or Pillow.
  2. Run pip install pilkit (or clone the source and put the pilkit module on your path)

.. note:: If you've never seen Pillow before, it considers itself a more-frequently updated "friendly" fork of PIL that's compatible with setuptools. As such, it shares the same namespace as PIL does and is a drop-in replacement.

.. PIL: http://pypi.python.org/pypi/PIL .. Pillow: http://pypi.python.org/pypi/Pillow

Usage Overview

Processors

The "pilkit.processors" module contains several classes for processing PIL images, which provide an easy to understand API:

.. code-block:: python

from pilkit.processors import ResizeToFit

img = Image.open('/path/to/my/image.png')
processor = ResizeToFit(100, 100)
new_img = processor.process(img)

A few of the included processors are:

  • ResizeToFit
  • ResizeToFill
  • SmartResize
  • Adjust
  • TrimBorderColor
  • Transpose

There's also a ProcessorPipeline class for executing processors sequentially:

.. code-block:: python

from pilkit.processors import ProcessorPipeline, ResizeToFit, Adjust

img = Image.open('/path/to/my/image.png')
processor = ProcessorPipeline([Adjust(color=0), ResizeToFit(100, 100)])
new_image = processor.process(img)

Utilities

In addition to the processors, PILKit contains a few utilities to ease the pain of working with PIL. Some examples:

prepare_image Prepares the image for saving to the provided format by doing some common-sense conversions, including preserving transparency and quantizing. save_image Wraps PIL's Image.save() method in order to gracefully handle PIL's "Suspension not allowed here" errors, and (optionally) prepares the image using prepare_image

Utilities are also included for converting between formats, extensions, and mimetypes.

Community

Please use the GitHub issue tracker <https://github.com/matthewwithanm/pilkit/issues> to report bugs. A mailing list <https://groups.google.com/forum/#!forum/django-imagekit> also exists to discuss the project and ask questions, as well as the official #imagekit <irc://irc.freenode.net/imagekit> channel on Freenode. (Both of these are shared with the django-imagekit project—from which PILKit spun off.)

.. _django-imagekit: https://github.com/jdriscoll/django-imagekit

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