Motivation

Why another Python imaging library

There exist quite a bunch of other Python imaging solutions with PIL being the most prominent one. Most of them don’t satisfy at least one and typically more of the criteria that I consider quality and modern Python software.

• They are hardly documented or not at all
• They don’t have complete test suite with reasonable coverage
• They don’t work with one of: Python 2.5, Python 2.6, Python 2.7, Python 3.2, PyPy or IronPython
• They can’t run processing algorithms on many cores in parallel leaving them idle.
• They are limited to narrow scope of image formats
• They don’t allow operation on RAW data formats such as YCbCr or RGB triplets
• They can only process images internally in 8bit depth per channel what can be not sufficient for some operations
• They are not actively maintained anymore or largely out-dated
• They don’t provide Pythonic API because they are modeled after C code
• They provide interfaces that are not easily extensible e.g. don’t allow subclassing
• They are not easily installed on widely used OSes such as Windows, Linux and MacOS X
• They always require C compiler during installation phase
• They don’t have transparent open-source development cycle
• They try to hide complexity of image processing preventing you from performing custom advance operations
• You can find a lot of ranting on the Internet and they drive you crazy

Why another ImageMagick wrapper

While you can find a lot of ImageMagick wrappers most of them feel like doing C++ in Python. Some of them are not maintained and typically don’t work on one of supported Python runtime + platform combinations.

What Pystacia does about that

• Pystacia has documentation that I try to make as complete as my resources let me
• Pystacia has large test suite consisting of ~70 tests with 90% coverage at the time of writing.
• Pystacia works both on Python 2.5+ and Python 3.x as well as PyPy and IronPython. Jython support is planned through JNA interface or ctypes if it gets reasonably stable and complete by the time of implementation.
• Pystacia ships version of ImageMagick built with OMP support which lets you use all your cores for image processing.
• Pystacia comes with wide spectrum of supported formats in standard distribution. JPEG, PNG, TIFF, GIF, BMP, ICO, JNG, PCX, PNM, HDR, EXR to name a few. See http://www.imagemagick.org/script/formats.php for complete list.
• Pystacia can read and write RAW data blobs such as RGB, YCbCr, YUV and CMYK in both 8 and 16 bits per channel with or without alpha channel directly from Python strings or streams.
• The default ImageMagick distribution coming with Pystacia processes data in 16 bit precision internally.
• I did put a lot of effort into making this code as good as possible. All the Python code is continously tested against PEP8 validity and inspected with Pyflakes to detect common problems.
• Pystacia tries to hide ImageMagick quirks, shield you from ABI changes, provide monolithic Python API. It supports any version of Imagick that is newer or equal to 6.5.9.0. Pystacia itself comes with reasonable recent versions of ImageMagick.
• Pystacia strives to provide Pythonic API employing as many idioms and common patterns as possible. Pystacia classes are fully subclassable and factory methods can accept factory parameters which specify which class is to be used.
• Pystacia comes with prebuild ImageMagick binaries for Windows, Linux and MacOS X. Still it’s possible to build it yourself if the default distribution doesn’t fit your needs.
• Pystacia is completely free of charge both for open-source and commercial uses as it’s licensed under MIT license.
• Pystacia exposes wand property on objects so you can use raw ctypes calls if you really want to but normally it shouldn’t be necessary.