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Python

import pytest
from semantica.context.context_graph import ContextGraph
@pytest.mark.benchmark(group="graph_traversal")
@pytest.mark.parametrize("hops", [1, 2])
def test_bfs_traversal_depth(benchmark, populated_context_graph, hops):
"""Benchmarks the BFS neighbor retrieval at differnet depths."""
graph = populated_context_graph(n_nodes=2000)
start_node = list(graph.nodes.keys())[0]
def run():
return graph.get_neighbors(start_node, hops=hops)
benchmark.pedantic(run, iterations=5, rounds=10)
@pytest.mark.benchmark(group="graph_construction")
@pytest.mark.parametrize("size", [1000])
def test_graph_ingestion_speed(benchmark, generate_graph_data, size):
"""
Benchmarks the speed of adding nodes and edges to the
in-memory structure.
"""
nodes, edges = generate_graph_data(n_nodes=size)
def run():
graph = ContextGraph()
graph.add_nodes(nodes)
graph.add_edges(edges)
benchmark.pedantic(run, iterations=1, rounds=5)
@pytest.mark.benchmark(group="graph_query")
def test_graph_keyword_search(benchmark, populated_context_graph):
"""
Benchmarks the linear scan keyword search over graph nodes.
"""
graph = populated_context_graph(n_nodes=2000)
def run():
return graph.query("Node content 500")
benchmark.pedantic(run, iterations=5, rounds=10)