Python implementation of the BioFabric network visualization technique
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biofabric is a Python library implementing the BioFabric network visualization technique described in Longabaugh 2012, Combing the hairball with BioFabric: a new approach for visualization of large networks and at

BioFabric is a new way to visualize networks in a simple, deterministic way, by laying out nodes and edges as rows and columns on a grid based on their degree. Such visualization allow for the quick identification of hubs, communities, and peculiar network topologies:

Complete graph (classical representation)

Complete graph, using a classical representation

Complete graph (BioFabric representation)

Same graph, displayed using the BioFabric technique

Various examples of graphs displayed using BioFabric can be found at and in the examples/ subdirectory.

Getting started

biofabric is provided as an easy_install and pip compliant package which can be installed as follows:

  • to install the most up to date (and potentially unstable) version, type either

    pip install
  • to install a specific version, such as 0.1.0 (the latest stable version), type either

    pip install

biofabric depends on two excellent libraries: NetworkX to manipulate networks, and PyX to produce an output in various formats (pdf, png, eps, jpg, etc.) following the BioFabric technique. easy_install will install these for you in case they are not already installed in your system.

Once biofabric installed, it can be used through the draw() function:

import biofabric

# generate a complete graph of 10 nodes using the
# networkx library; this is the example shown above
import networkx
g = networkx.generators.classic.complete_graph(10)

# draw it, as a PDF document
biofabric.draw(g, "complete_graph.pdf")

Documentation and additional examples can be found at


biofabric is released under a MIT/X11 license.