Convert ArangoDB graphs to NetworkX & vice-versa.
Project description
ArangoDB-Networkx Adapter
The ArangoDB-Networkx Adapter exports Graphs from ArangoDB, a multi-model Graph Database, into NetworkX, the swiss army knife for graph analysis with python, and vice-versa.
About NetworkX
Networkx is a commonly used tool for analysis of network-data. If your analytics use cases require the use of all your graph data, for example, to summarize graph structure, or answer global path traversal queries, then using the ArangoDB Pregel API is recommended. If your analysis pertains to a subgraph, then you may be interested in getting the Networkx representation of the subgraph for one of the following reasons:
1. An algorithm for your use case is available in Networkx.
2. A library that you want to use for your use case works with Networkx Graphs as input.
Quickstart
import networkx as nx
from adbnx_adapter.adbnx_adapter import ArangoDB_Networkx_Adapter
con = {
"hostname": "localhost",
"protocol": "http",
"port": 8529,
"username": "root",
"password": "rootpassword",
"dbName": "_system",
}
adbnx_adapter = ArangoDB_Networkx_Adapter(con)
# (Assume ArangoDB fraud-detection data dump is imported)
fraud_nx_g = adbnx_adapter.arangodb_graph_to_networkx("fraud-detection")
fraud_nx_g_2 = adbnx_adapter.arangodb_collections_to_networkx(
"fraud-detection",
{"account", "bank", "branch", "Class", "customer"},
{"accountHolder", "Relationship", "transaction"}
)
grid_nx_g = nx.grid_2d_graph(5, 5)
grid_edge_definitions = [
{
"edge_collection": "to",
"from_vertex_collections": ["Grid_Node"],
"to_vertex_collections": ["Grid_Node"],
}
]
adb_g = adbnx_adapter.networkx_to_arangodb("Grid", grid_nx_g, grid_edge_definitions)
Development & Testing
Prerequisite: arangorestore
must be installed
git clone https://github.com/arangoml/networkx-adapter.git
cd networkx-adapter
python -m venv .venv
source .venv/bin/activate
(MacOS) or.venv/scripts/activate
(Windows)cd adbnx_adapter
pip install -e . pytest
pytest
- If you encounter
ModuleNotFoundError
, try closing & relaunching your virtual environment by runningdeactivate
in your terminal & restarting from Step 4.
- If you encounter
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