Drawing a large graph like this is not very insightful by itself, and doing this well is still an art form. Many cool visualizations, and all very domain and question dependent, can be found at http://www.visualcomplexity.com/vc/
You can also search on flickr for network and graph drawing. Much of it is eyecandy though. What do you really want to know? Your graph is not overly huge for python, provided you do not want to compute nonlocal statistics such as betweenness metrics. (If you have a laptop running windows and with less than 1GB RAM, then you have a really large graph.) Given that you do not know much about graph theory, I would suggest that networkx applied to a subset of your large website --- one of the representative branches --- will allow for the fastest way to figure out what you want to do. Python provides access to many other libraries for html mangling or even webpage analysis. Imagine writing C code to ask questions like: how many pdfs and images? how big are they? when were these pages last updated? etc. You can come up with 10 questions faster than you can write C code, and this where python has its great advantage. You can learn graph theory while using these libraries, on one of the smaller branches of your website tree. Even interactively by using ipython. This provides at least a feeling of great power while stumbling in the dark. Many of your edges are probably repetitions associated with navigation menus to provide a standard look-and-feel. See how much of that you can strip out and find the cross-links that took effort to insert an manage. (I suggest doing the analyis on a digraph rather than a graph, even if you want to draw it as graph.) For visualization, the new ubigraph is quite fast compared to graphviz. See the cool networkx + ubigraph video at http://ubietylab.net/blog/ Ask on the networkx mailinglist when stuck. -- http://mail.python.org/mailman/listinfo/python-list
