The ArangoDB-Networkx Adapter exports Graphs from ArangoDB, the multi-model database for graph & beyond, into NetworkX, the swiss army knife for graph analysis with python, and vice-versa.
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.
pip install adbnx-adapter
pip install git+https://github.com/arangoml/networkx-adapter.git
Also available as an ArangoDB Lunch & Learn session: Graph & Beyond Course #2.9
import networkx as nx
from arango import ArangoClient
from adbnx_adapter import ADBNX_Adapter, ADBNX_Controller
# Connect to ArangoDB
db = ArangoClient().db()
# Instantiate the adapter
adbnx_adapter = ADBNX_Adapter(db)#######################
# 1.1: via Graph name #
#######################
nx_g = adbnx_adapter.arangodb_graph_to_networkx("fraud-detection")
#############################
# 1.2: via Collection names #
#############################
nx_g = adbnx_adapter.arangodb_collections_to_networkx(
"fraud-detection",
{"account", "bank", "branch", "Class", "customer"}, # Vertex collections
{"accountHolder", "Relationship", "transaction"} # Edge collections
)
######################
# 1.3: via Metagraph #
######################
metagraph = {
"vertexCollections": {
"account": {"Balance", "account_type", "customer_id", "rank"},
"customer": {"Name", "rank"},
},
"edgeCollections": {
"transaction": {"transaction_amt", "sender_bank_id", "receiver_bank_id"},
"accountHolder": {},
},
}
nx_g = adbnx_adapter.arangodb_to_networkx("fraud-detection", metagraph)
#######################################
# 1.4: with a custom ADBNX Controller #
#######################################
class Custom_ADBNX_Controller(ADBNX_Controller):
"""ArangoDB-NetworkX controller.
Responsible for controlling how nodes & edges are handled when
transitioning from ArangoDB to NetworkX, and vice-versa.
"""
def _prepare_arangodb_vertex(self, adb_vertex: dict, col: str) -> None:
"""Prepare an ArangoDB vertex before it gets inserted into the NetworkX
graph.
:param adb_vertex: The ArangoDB vertex object to (optionally) modify.
:param col: The ArangoDB collection the vertex belongs to.
"""
adb_vertex["foo"] = "bar"
def _prepare_arangodb_edge(self, adb_edge: dict, col: str) -> None:
"""Prepare an ArangoDB edge before it gets inserted into the NetworkX
graph.
:param adb_edge: The ArangoDB edge object to (optionally) modify.
:param col: The ArangoDB collection the edge belongs to.
"""
adb_edge["bar"] = "foo"
nx_g = ADBNX_Adapter(db, Custom_ADBNX_Controller()).arangodb_graph_to_networkx("fraud-detection")#################################
# 2.1: with a Homogeneous Graph #
#################################
nx_g = nx.grid_2d_graph(5, 5)
edge_definitions = [
{
"edge_collection": "to",
"from_vertex_collections": ["Grid_Node"],
"to_vertex_collections": ["Grid_Node"],
}
]
adb_g = adbnx_adapter.networkx_to_arangodb("Grid", nx_g, edge_definitions)
#############################################################
# 2.2: with a Homogeneous Graph & a custom ADBNX Controller #
#############################################################
class Custom_ADBNX_Controller(ADBNX_Controller):
"""ArangoDB-NetworkX controller.
Responsible for controlling how nodes & edges are handled when
transitioning from ArangoDB to NetworkX, and vice-versa.
"""
def _prepare_networkx_node(self, nx_node: dict, col: str) -> None:
"""Prepare a NetworkX node before it gets inserted into the ArangoDB
collection **col**.
:param nx_node: The NetworkX node object to (optionally) modify.
:param col: The ArangoDB collection the node belongs to.
"""
nx_node["foo"] = "bar"
def _prepare_networkx_edge(self, nx_edge: dict, col: str) -> None:
"""Prepare a NetworkX edge before it gets inserted into the ArangoDB
collection **col**.
:param nx_edge: The NetworkX edge object to (optionally) modify.
:param col: The ArangoDB collection the edge belongs to.
"""
nx_edge["bar"] = "foo"
adb_g = ADBNX_Adapter(db, Custom_ADBNX_Controller()).networkx_to_arangodb("Grid", nx_g, edge_definitions)
###################################
# 2.3: with a Heterogeneous Graph #
###################################
edges = [
('student:101', 'lecture:101'),
('student:102', 'lecture:102'),
('student:103', 'lecture:103'),
('student:103', 'student:101'),
('student:103', 'student:102'),
('teacher:101', 'lecture:101'),
('teacher:102', 'lecture:102'),
('teacher:103', 'lecture:103'),
('teacher:101', 'teacher:102'),
('teacher:102', 'teacher:103')
]
nx_g = nx.MultiDiGraph()
nx_g.add_edges_from(edges)
# ...
# Learn how this example is handled in Colab:
# https://colab.research.google.com/github/arangoml/networkx-adapter/blob/master/examples/ArangoDB_NetworkX_Adapter.ipynb#scrollTo=OuU0J7p1E9OMPrerequisite: arangorestore
git clone https://github.com/arangoml/networkx-adapter.gitcd networkx-adapter- (create virtual environment of choice)
pip install -e .[dev]- (create an ArangoDB instance with method of choice)
pytest --url <> --dbName <> --username <> --password <>
Note: A pytest parameter can be omitted if the endpoint is using its default value:
def pytest_addoption(parser):
parser.addoption("--url", action="store", default="http://localhost:8529")
parser.addoption("--dbName", action="store", default="_system")
parser.addoption("--username", action="store", default="root")
parser.addoption("--password", action="store", default="")