NetworkX (NX) is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Features: Includes standard graph-theoretic and statistical physics functions, Easy exchange of network algorithms between applications, disciplines, and platforms, Includes many classic graphs and synthetic networks, Nodes and edges can be "anything" (e.g. time-series, text, images, XML records)
* Searchable command history (commands: "hi", "li", "run")
* Load commands from file, save to file, edit commands in file
* Multi-line commands
* Case-insensitive commands
* Special-character shortcut commands (beyond cmd's "@" and "!")
* Settable environment parameters
* Parsing commands with flags
The most important thing to know about Django on Jython is that we are almost there, and with clean code. End-to-end functionality is demonstrated by the admin tool running in full CRUD, along with a substantial number of unit tests and syncdb.
For the past month or so, I’ve been trying to understand what appears to be a black art mostly because of lacking documentation - Python bytecode generation and peephole optimization. Some notes from the study for the benefit of IRC-mate ‘jstatm’ and anyone else living on similar planes of insanity.
Although bytecode applies to objects other than functions such as tracebacks, dictionaries and strings, I am only interested in optimization and flow analysis of class methods, functions and lambdas. Lets get to the action straight away with an example. Here is a small python program to disassemble and display the bytecode of a function in human readable form.
