Karate Club dataset

This notebook shows the classic Zachary Karate Club network loaded into NetworkXGraph, Neo4jGraph, MemgraphGraph and JenaGraph using the shared loader in cvcdocdb.exemples.

Dataset notes:

• 34 members

• classic community-detection benchmark

• club attribute is used to build club nodes

The server sections need a running server each: skip the ones you don’t have. They read NEO4J_*, MEMGRAPH_URL/MEMGRAPH_USER/MEMGRAPH_PASSWORD and FUSEKI_URL/FUSEKI_USER/FUSEKI_PASSWORD (defaults: bolt://localhost:7687 and http://localhost:3030/ds).

import importlib.util

# Comprovació de presència del paquet, amb l'extra [notebook] del visualitzador de grafs (anywidget)
if (importlib.util.find_spec("cvcdocdb") is None
        or importlib.util.find_spec("cvcdocdb.viewer") is None
        or importlib.util.find_spec("anywidget") is None):
    print("⚠️ cvcdocdb[notebook] no està instal·lat. Iniciant instal·lació...")
    %pip install -q --upgrade "cvcdocdb[notebook]"
    print("✅ Instal·lació completada. L'estat del kernel PODRIA requerir un reinici.")
else:
    print("✅ cvcdocdb i anywidget ja són presents al sistema. Saltant instal·lació.")

import os

from cvcdocdb import JenaGraph, MemgraphGraph, Neo4jGraph, NetworkXGraph
from cvcdocdb.exemples import load_karate_club


def neo4j_config(default_target="DEV"):
    target = os.environ.get("NEO4J_TARGET", default_target).upper()
    prefix = f"NEO4J_{target}_"
    return {
        "target": target,
        "url": os.environ.get(f"{prefix}URL", os.environ.get("NEO4J_URL", "bolt://localhost:7687")),
        "user": os.environ.get(f"{prefix}USER", os.environ.get("NEO4J_USER", "neo4j")),
        "password": os.environ.get(f"{prefix}PASSWORD", os.environ.get("NEO4J_PASSWORD", "secret")),
        "database": os.environ.get(f"{prefix}DATABASE", os.environ.get("NEO4J_DATABASE", "neo4j")),
    }

NetworkXGraph

nx_graph = NetworkXGraph()
nx_stats = load_karate_club(nx_graph)
print("NetworkX stats:", nx_stats)
print("NetworkX nodes:", len(nx_graph.get_nodes()))
print("NetworkX edges:", len(nx_graph.get_edges()))

NetworkX stats: {'members': 34, 'clubs': 2, 'interacts': 78, 'member_of': 34}
NetworkX nodes: 36
NetworkX edges: 112

Explore the graph

show() opens the cvcdocdb graph viewer on this graph. Click a node to see its properties, double-click it to expand its neighbours, and search or filter from the sidebar. The viewer reads the graph live from the kernel, so the graph is only closed in the last cell, once you are done.

from cvcdocdb.viewer import show

show(nx_graph, load_all=True)

Neo4jGraph

cfg = neo4j_config()
print("Using Neo4j target:", cfg["target"])
neo4j_graph = Neo4jGraph(
    url=cfg["url"],
    user=cfg["user"],
    password=cfg["password"],
    database=cfg["database"],
)
try:
    neo4j_stats = load_karate_club(neo4j_graph)
    print("Neo4j stats:", neo4j_stats)
finally:
    neo4j_graph.close()

MemgraphGraph

Same API and behaviour as Neo4jGraph.

memgraph_url = os.environ.get("MEMGRAPH_URL", "bolt://localhost:7687")
print("Using Memgraph:", memgraph_url)
memgraph_graph = MemgraphGraph(
    memgraph_url,
    os.environ.get("MEMGRAPH_USER", ""),
    os.environ.get("MEMGRAPH_PASSWORD", ""),
)
try:
    memgraph_stats = load_karate_club(memgraph_graph)
    print("Memgraph stats:", memgraph_stats)
finally:
    memgraph_graph.close()

JenaGraph

The graph is stored as RDF 1.2 in an Apache Jena Fuseki dataset (Fuseki >= 6.2.0).

fuseki_url = os.environ.get("FUSEKI_URL", "http://localhost:3030/ds")
print("Using Fuseki:", fuseki_url)
jena_graph = JenaGraph(fuseki_url, os.environ.get("FUSEKI_USER"), os.environ.get("FUSEKI_PASSWORD"))
try:
    jena_stats = load_karate_club(jena_graph)
    print("Jena stats:", jena_stats)
finally:
    jena_graph.close()

Cleanup

Closing the graph empties it, and the viewer with it: run this once you are done exploring.

# nx_graph.close()