Boost Graph Library - Python Bindings

The goal of the BGL-Python bindings is to create a set of bindings for the majority of the BGL in Python that:

• "Feel" like the BGL, but with Python syntax.
• Allow rapid prototyping of algorithms for the BGL.
• Allow easy porting from the BGL in Python to the BGL in C++.
• Permit the use of the BGL in applications for which C++ is not particularly well suited.
• Strike a balance between simplicity, usability, and efficiency.

Data Structures and Algorithms

BGL-Python contains many of the data structures and algorithms found in the C++ (Parallel) Boost Graph Library, including:

Example Usage

The following simple program loads a GraphViz file, computes the minimum spanning tree of the graph, annotates the graph to illustrate the minimum spanning tree, and emits the result as a GraphViz file.

import boost.graph as bgl

# Load a graph from the GraphViz file 'mst.dot'
graph = bgl.Graph.read_graphviz('mst.dot')

# Convert the weight into floating-point values
weight = graph.convert_property_map(graph.edge_properties['weight'],
                                    'float')

# Compute the minimum spanning tree of the graph
mst_edges = bgl.kruskal_minimum_spanning_tree(graph, weight)

# Compute the weight of the minimum spanning tree 
print 'MST weight =',sum([weight[e] for e in mst_edges])

# Put the weights into the label. Make MST edges solid while all other
# edges remain dashed.
label = graph.edge_property_map('string')
style = graph.edge_property_map('string')
for e in graph.edges:
    label[e] = str(weight[e])
    if e in mst_edges:
        style[e] = 'solid'
    else:
        style[e] = 'dashed'

# Associate the label and style property maps with the graph for output
graph.edge_properties['label'] = label
graph.edge_properties['style'] = style

# Write out the graph in GraphViz DOT format
graph.write_graphviz('mst-out.dot')

Download

There are several ways to get the BGL-Python bindings:

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