My project d2g is currently reading a description file for dependencies, then generating a text file that can be fed to graphviz to generate a picture of the graph. yapgvb is a wrapper in Python for graphviz, so I’ll migrate my code to use, so no additional step will be required.
The package pydot, a Python interface to Graphviz’s Dot language, may be a better way to generate the graphs than writing intermediate dot files. Will review
According to the site, pydot provides:
An interface for creating both directed and non directed graphs from Python. Currently all attributes implemented in the Dot language are supported (up to Graphviz 1.16).
The PyTables package is a Python interface to HDF5, which is a general purpose library and file format for storing scientific data made at NCSA. HDF5 can store two primary objects: datasets and groups. A dataset is essentially a multidimensional array of data elements, and a group is a structure for organizing objects in an HDF5 file (very similar to a directory in a filesystem).
Found “GiNaC is Not a CAS“, a symbolic algebra manipulation system. Through swiginac it will be possible to use it from Python. The only concern is that may be an overkill.
The Journal of Artificial Societies and Social Simulation seems to contain some interesting articles and I would like to check them with more detail
I hacked a Python program to export the iPhoto albums into the format I need to use zphoto and publish them on the website as Flash animations. I’d like to extend it to be a iPhoto PlugIn and this article has info on writing plugIns for Cocoa
This article CHARMING PYTHON (Special Installment) — Revisiting XML Tools for Python – looks very interesting for the project I’m working on
More Modules: xml_pickle And xml_objectify
I have produced my own set of high-level modules for dealing with XML, called xml_pickle and xml_objectify. I have also written enough about these elsewhere (see Resources) that there is no need to go into a lot of details here. But these modules are often very useful when you want to “think in Python” rather than “think in XML.” xml_objectify especially hides almost all the traces of XML itself from a Python programmer, and lets her work with perfectly “native” Python objects within a program. The actual XML data format that underlies things is abstracted almost to the point of invisibility. Likewise, xml_pickle lets a Python programmer start out with “native” Python objects whose data comes from any source, and dump (serialize) them into an XML format that other users might want downstream.
I think I found a good way to quickly create native looking applications on OS X. I like to use Python, and there is a library to bridge the Objective C libraries to Python named PyObjC. There is an IDE using this framework named PyOXIDE, but seems a bit buggy