Example NetworkX with Bokeh plot displaying a single program

brevity-networkx-example.py

# NetworkX with Bokeh example
import networkx as nx
import pandas as pd

from bokeh.io import output_notebook, show, save
from bokeh.models import Range1d, Circle, ColumnDataSource, MultiLine
from bokeh.plotting import figure
from bokeh.plotting import from_networkx

# https://docs.bokeh.org/en/latest/docs/reference/palettes.html
from bokeh.palettes import Blues8, Reds8, Purples8, Oranges8, Viridis8, Spectral8, Turbo256, Bokeh, inferno
from bokeh.transform import linear_cmap
from networkx.algorithms import community

# Load Bokeh
output_notebook()

# Load program data
programName = 'testbrevity'
fileName = programName + '-httpx.json'
presentationBucketPath = 's3://brevity-data/presentation/httpx/'
dataInputPath = presentationBucketPath + fileName
# Load HTTPX crawl data
dfGraphData = pd.read_json(dataInputPath, lines=True)
dfGraphData[:10]

sourceColumn = 'domain'
targetColumn = 'baseurl'
programColumn = 'program'
G = nx.from_pandas_edgelist(df=dfGraphData, source=programColumn, target=sourceColumn, edge_attr=None)
G2 = nx.from_pandas_edgelist(df=dfGraphData, source=sourceColumn, target=targetColumn, edge_attr=None)#,(df=dfGraphData, source=programColumn, target=sourceColumn, edge_attr=None)])

G.add_nodes_from(nodes_for_adding=dfGraphData.domain.unique().tolist())
G.add_nodes_from(nodes_for_adding=dfGraphData.baseurl.unique().tolist())
G.add_nodes_from(nodes_for_adding=dfGraphData.program.unique().tolist())

print('# of edges: {}'.format(G.number_of_edges()))
print('# of nodes: {}'.format(G.number_of_nodes()))

# Load communities
communities = community.greedy_modularity_communities(G2)

# Create empty dictionaries
modularity_class = {}
modularity_color = {}
#Loop through each community in the network
for community_number, community in enumerate(communities):
    #For each member of the community, add their community number and a distinct color
    for name in community: 
        modularity_class[name] = community_number
        modularity_color[name] = inferno(128)[community_number]
        #modularity_color[name] = inferno(256)[community_number]
              
# Add modularity class and color as attributes from the network above
nx.set_node_attributes(G2, modularity_class, 'modularity_class')
nx.set_node_attributes(G2, modularity_color, 'modularity_color')

# Adapted from https://melaniewalsh.github.io/Intro-Cultural-Analytics/Network-Analysis/Making-Network-Viz-with-Bokeh.html

#Choose a title!
title = 'Bug Bounty Recon'

#Establish which categories will appear when hovering over each node
HOVER_TOOLTIPS = [("baseurl", "@index")]

#Create a plot — set dimensions, toolbar, and title
plot = figure(tooltips = HOVER_TOOLTIPS,
              tools="pan,wheel_zoom,save,reset", active_scroll='wheel_zoom',
            x_range=Range1d(-10.1, 10.1), y_range=Range1d(-10.1, 10.1), title=title)

#Create a network graph object with spring layout
network_graph = from_networkx(G2, nx.spring_layout, scale=10, center=(0, 0))

color_by_this_attribute = 'modularity_color'
#Pick a color palette — Blues8, Reds8, Purples8, Oranges8, Viridis8
color_palette = inferno(24)#Turbo256#(30)#Turbo256#Blues8
#color_palette = Turbo256

#Set node sizes and colors according to node degree (color as category from attribute)
network_graph.node_renderer.glyph = Circle(size=15, fill_color=color_by_this_attribute)
#Set node size and color
#network_graph.node_renderer.glyph = Circle(size=degree, fill_color='skyblue')

#Set edge opacity and width
network_graph.edge_renderer.glyph = MultiLine(line_alpha=0.5, line_width=1)

#Add network graph to the plot
plot.renderers.append(network_graph)

show(plot)
#save(plot, filename=#f"{testplot}.html")