python-igraph Manual

For using igraph from Python

Configuration Instance

Configuration Instance

This example shows how to use igraph’s configuration instance to set default igraph settings. This is useful for setting global settings so that they don’t need to be explicitly stated at the beginning of every igraph project you work on.

First we define the default plotting backend, layout, and color palette, and save them. By default, will save files to ~/.igraphrc on Linux and Max OS X systems, or in C:\Documents and Settings\username\.igraphrc for Windows systems.

import igraph as ig

# Set configuration variables
ig.config["plotting.backend"] = "matplotlib"
ig.config["plotting.layout"] = "fruchterman_reingold"
ig.config["plotting.palette"] = "rainbow"

# Save configuration to ~/.igraphrc

This script only needs to be run once (to store the new config options into the .igraphrc file). Whenever you use igraph and this file exists, igraph will read its content and use those options as defaults. For example:

import igraph as ig
import matplotlib.pyplot as plt
import random

# Generate a graph
g = ig.Graph.Barabasi(n=100, m=1)

# Calculate a color value between 0-200 for all nodes
betweenness = g.betweenness()
colors = [int(i * 200 / max(betweenness)) for i in betweenness]

# Plot the graph
ig.plot(g, vertex_color=colors, vertex_size=1, edge_width=0.3)

Note that we do not never explicitly state the backend, layout or palette, yet the final plots look like this:

A 100 node graph colored to show betweenness

Graph colored based on each node’s betweenness centrality measure.

The full list of config settings can be found here.


You can have multiple config files: specify each location via"./path/to/config/file"). To load a specific config, import igraph and then call ig.config.load("./path/to/config/file")


To use a consistent style between individual plots (e.g. vertex sizes, colors, layout etc.) check out Plotting graphs with a consistent style.