Free python call graph software for linux

The code is appropriately documented and API reference is generated automatically by epydoc. Comments, bug reports and suggestions are welcome.

Major Features:

1. Support for directed, undirected, weighted and non-weighted graphs
2. Support for hypergraphs
3. Canonical operations
4. XML import and export
5. DOT-Language output (for usage with Graphviz)
6. Random graph generation
7. Accessibility (transitive closure)
8. Breadth-first search
9. Cut-vertex and cut-edge identification
10. Depth-first search
11. Heuristic search (A* algorithm)
12. Identification of connected components
13. Minimum spanning tree (Prims algorithm)
14. Mutual-accessibility (strongly connected components)
15. Shortest path search (Dijkstras algorithm)
16. Topological sorting

Enhancements: Fixes an installer bug.

Requirements: Python

Python Web Graph Generator is a threaded Web graph (Power law random graph) generator. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine.
This software implements a threaded variant of the RMAT algorithm. A little tweak can produce graphs representing social networks or community networks.
Examples:
Getting help
$./genwebgraph.py --help
Generating graph using default settings
$ ./genwebgraph.py --threads=1
Generating a 1000-vertex and 1000-egde graph using 5 threads and storing it in ~/mygraph.pyg
$ ./genwebgraph.py --threads=5 --max-vertices=1000 --max-edges=1000 --output=~/mygraph.pyg
Storing in dot compatible output and making a postscript file
$ ./genwebgraph.py --output=~/mygraph.pyg --format=dot
$ dot -Tps ~/mygraph.pyg -o mygraph.ps
Enhancements:
- The base library PyGEL is available as an independent Python module.

Python XHTML is a simple Python module for the generation of valid XHTML.

ToDo:

* include tests for all methods in xhtml_test.py
* ensure that all text that is added to the document is xml safe
* include methods for added w3.org validation link buttons
* complete support for XHTML 1.1 specification

Python in Scheme is a scheme library that allows you to run Python code within Scheme.

Python in Scheme project uses the Python/C API to embed a Python interpreter.

QWPython project is a Python-powered QuakeWorld server.

The core engine has been wrapped up as a Python module and altered to call back to Python to execute Quake game logic.

A QuakeC - Python translator is also included, along with pre-translated versions of Deathmatch and Capture-The-Flag.

Python is an interpreted, interactive, object-oriented programming language. Python is often compared to Perl, Tcl, Scheme or Java.

Python combines remarkable power with very clear syntax. It has modules, classes, exceptions, very high level dynamic data types, and dynamic typing. There are interfaces to many system calls and libraries, as well as to various windowing systems (X11, Motif, Tk, Mac, MFC). New built-in modules are easily written in C or C++. Python is also usable as an extension language for applications that need a programmable interface.

The Python implementation is portable: it runs on many brands of UNIX, on Windows, OS/2, Mac, Amiga, and many other platforms. If your favorite system isnt listed here, it may still be supported, if theres a C compiler for it.

The Python implementation is copyrighted but freely usable and distributable, even for commercial use.

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together.

Pythons simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.

Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception.

When the program doesnt catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on.

The debugger is written in Python itself, testifying to Pythons introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective.

python-gammu are Python bindings for Gammu library. It currently does not support all Gammu features, but range of covered functions is increasing, if you need some specific, feel free to use bug tracking system for feature requests.