Convert to and from a NetworkX graph

prov.graph converts a document to and from a NetworkX MultiDiGraph, so you can run graph algorithms such as centrality, shortest paths or community detection over it. It needs the graph extra:

python -m pip install "prov[graph]"

Document to graph

prov_to_graph() returns one node per element (entity, activity or agent) and one edge per relation. It unifies the document first, so records that share an identifier become one node:

import prov.model as pm
from prov.graph import prov_to_graph

document = pm.ProvDocument()
document.set_default_namespace("http://example.org/")
e = document.entity("e1")
a = document.activity("a1")
document.wasGeneratedBy(e, a)

g = prov_to_graph(document)

print(list(g.nodes()))
# [<ProvEntity: e1>, <ProvActivity: a1>]
print(list(g.edges(data=True)))
# [(<ProvEntity: e1>, <ProvActivity: a1>, {'relation': <ProvGeneration: (e1, a1)>})]

Each node is the ProvElement record itself. Each edge carries its ProvRelation under the "relation" key, so the relation type and its attributes stay available while you work in NetworkX.

A relation whose endpoint is unset, or undeclared with a type that cannot be inferred, is dropped with a ProvWarning.

Run a NetworkX algorithm

Nodes are hashable prov objects, so any NetworkX algorithm works directly:

import networkx as nx

print(nx.is_directed_acyclic_graph(g))

Graph back to document

graph_to_prov() reverses the conversion. The graph must have the shape prov_to_graph produces. Nodes are ProvRecord instances with a bundle, and each edge carries a "relation" record in its data:

from prov.graph import graph_to_prov

reloaded = graph_to_prov(g)
assert reloaded == document