ArangoDB with Graphistry

ArangoDB with Graphistry#

We explore Game of Thrones data in ArangoDB to show how Arango’s graph support interops with Graphistry pretty quickly.

This tutorial shares two sample transforms: * Visualize the full graph * Visualize the result of a traversal query

Each runs an AQL query via python-arango, automatically converts to pandas, and plots with graphistry.

Setup#

[ ]:
!pip install python-arango --user -q
[1]:
from arango import ArangoClient
import pandas as pd
import graphistry
[3]:
def paths_to_graph(paths, source='_from', destination='_to', node='_id'):
    nodes_df = pd.DataFrame()
    edges_df = pd.DataFrame()
    for graph in paths:
        nodes_df = pd.concat([ nodes_df, pd.DataFrame(graph['vertices']) ], ignore_index=True)
        edges_df = pd.concat([ edges_df, pd.DataFrame(graph['edges']) ], ignore_index=True)
    nodes_df = nodes_df.drop_duplicates([node])
    edges_df = edges_df.drop_duplicates([node])
    return graphistry.bind(source=source, destination=destination, node=node).nodes(nodes_df).edges(edges_df)

def graph_to_graphistry(graph, source='_from', destination='_to', node='_id'):
    nodes_df = pd.DataFrame()
    for vc_name in graph.vertex_collections():
        nodes_df = pd.concat([nodes_df, pd.DataFrame([x for x in graph.vertex_collection(vc_name)])], ignore_index=True)
    edges_df = pd.DataFrame()
    for edge_def in graph.edge_definitions():
        edges_df = pd.concat([edges_df, pd.DataFrame([x for x in graph.edge_collection(edge_def['edge_collection'])])], ignore_index=True)
    return graphistry.bind(source=source, destination=destination, node=node).nodes(nodes_df).edges(edges_df)

Connect#

[ ]:
# To specify Graphistry account & server, use:
# graphistry.register(api=3, username='...', password='...', protocol='https', server='hub.graphistry.com')
# For more options, see https://github.com/graphistry/pygraphistry#configure
[4]:
client = ArangoClient(protocol='http', host='localhost', port=8529)
db = client.db('GoT', username='root', password='1234')

Demo 1: Traversal viz#

  • Use python-arango’s traverse() call to descendants of Ned Stark

  • Convert result paths to pandas and Graphistry

  • Plot, and instead of using raw Arango vertex IDs, use the first name

[7]:
paths = db.graph('theGraph').traverse(
    start_vertex='Characters/4814',
    direction='outbound',
    strategy='breadthfirst'
)['paths']
[8]:
g = paths_to_graph(paths)
g.bind(point_title='name').plot()
[8]:

Demo 2: Full graph#

  • Use python-arango on a graph to identify and download the involved vertex/edge collections

  • Convert the results to pandas and Graphistry

  • Plot, and instead of using raw Arango vertex IDs, use the first name

[11]:
g = graph_to_graphistry( db.graph('theGraph') )
g.bind(point_title='name').plot()
[11]:
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