Learning Python

Other Frameworks and Applications

With limited space, we could cover only a few of the most popular frameworks currently used with Python. There are several others, which are also deserving of mention and which might very well be what you need. We briefly describe some here.

Python Imaging Library (PIL)

The Python Imaging Library is an extensive framework written by Fredrik Lundh for creating, manipulating, converting, and saving bitmapped images in a variety of formats (such as GIF, JPEG, and PNG). It has interfaces to Tk and Pythonwin, so that one can use either Tk widgets or Pythonwin code to display PIL-generated images. Alternatively, the images can be saved to disk in a variety of formats. The home for PIL is at http://www.pythonware.com.

Numeric Python (NumPy)

Numeric Python is a set of extensions to Python designed to manipulate large arrays of numbers quickly and elegantly. It was written by Jim Hugunin (JPython’s author), with the support of the subscribers to the Matrix-SIG (more on SIGs in Appendix A). Since Jim started work on JPython, the responsibility for Numeric Python has been taken over by folks at the Lawrence Livermore National Laboratory. NumPy is a remarkably powerful tool for scientists and engineers, and as such is close to the heart of one of these authors. More information on it is available at the main Python web site’s topic guide for scientific computing (http://www.python.org/topics/scicomp/ ).

Here’s an example of typical NumPy code, numpytest.py, and ...