j6k4m8
commented
3 years ago If you have already created a graph on disk with sqlite, you can read it like this (assuming your database file is called example-graph.sqlite):
import grand
from grand.backends import SQLBackend
G = grand.Graph(
backend=SQLBackend(db_url="sqlite:///example-graph.sqlite", directed=True)
)You can now interact with the graph through whatever dialect you like. If you want to use NetworkX-style APIs, you can list edges like this:
G.nx.edges()Unfortunately, there isn't currently a great way to export and import graphs between Backends yet, as this can be a super expensive operation. If your graph is relatively small, you can export nodes and edges individually into, say, a NetworkX object — like this:
H = nx.DiGraph()
for node, attrs in G.nx.nodes(data=True):
H.add_node(node, **attrs)
for u, v, attrs in G.nx.edges(data=True):
H.add_edge(u, v, **attrs)Then you'll have access to all the same nodes in an in-memory NetworkX object:
H.nodes(data=True)Does this answer your question?
To get you started if you don't have a sqlite graph file yet, you can create the example-graph.sqlite like this:
G = grand.Graph(backend=SQLBackend(db_url="sqlite:///example-graph.sqlite", directed=True))
G.nx.add_edge("X", "Y")
AbdealiLoKo
yangyxt
As showed in the title.