python · mdboom · Oct 28, 2024 · Oct 22, 2024 · Oct 22, 2024 · Oct 23, 2024
diff --git a/pyperformance/data-files/benchmarks/MANIFEST b/pyperformance/data-files/benchmarks/MANIFEST
@@ -54,6 +54,9 @@ logging	<local>
 mako	<local>
 mdp	<local>
 meteor_contest	<local>
+networkx	<local>
+networkx_connected_components	<local:networkx>
+networkx_k_core	<local:networkx>
 nbody	<local>
 nqueens	<local>
 pathlib	<local>

diff --git a/pyperformance/data-files/benchmarks/bm_networkx/bm_networkx_connected_components.toml b/pyperformance/data-files/benchmarks/bm_networkx/bm_networkx_connected_components.toml
@@ -0,0 +1,3 @@
+[tool.pyperformance]
+name = "networkx_connected_components"
+extra_opts = ["connected_components"]
diff --git a/pyperformance/data-files/benchmarks/bm_networkx/bm_networkx_k_core.toml b/pyperformance/data-files/benchmarks/bm_networkx/bm_networkx_k_core.toml
@@ -0,0 +1,3 @@
+[tool.pyperformance]
+name = "networkx_k_core"
+extra_opts = ["k_core"]
diff --git a/pyperformance/data-files/benchmarks/bm_networkx/data/amazon0302.txt.gz b/pyperformance/data-files/benchmarks/bm_networkx/data/amazon0302.txt.gz
diff --git a/pyperformance/data-files/benchmarks/bm_networkx/pyproject.toml b/pyperformance/data-files/benchmarks/bm_networkx/pyproject.toml
@@ -0,0 +1,13 @@
+[project]
+name = "pyperformance_bm_networkx"
+requires-python = ">=3.11"
+dependencies = [
+    "pyperf",
+    "networkx",
+]
+urls.repository = "https://github.com/python/pyperformance"
+dynamic = ["version"]
+
+[tool.pyperformance]
+name = "networkx_shortest_path"
+extra_opts = ["shortest_path"]
diff --git a/pyperformance/data-files/benchmarks/bm_networkx/requirements.txt b/pyperformance/data-files/benchmarks/bm_networkx/requirements.txt
@@ -0,0 +1 @@
+networkx==3.4.2	
diff --git a/pyperformance/data-files/benchmarks/bm_networkx/run_benchmark.py b/pyperformance/data-files/benchmarks/bm_networkx/run_benchmark.py
@@ -0,0 +1,61 @@
+"""
+Some graph algorithm benchmarks using networkx
+
+This uses the public domain Amazon data set from the SNAP benchmarks:
+
+    https://snap.stanford.edu/data/amazon0302.html
+
+Choice of benchmarks inspired by Timothy Lin's work here:
+
+    https://www.timlrx.com/blog/benchmark-of-popular-graph-network-packages
+"""
+
+import collections
+from pathlib import Path
+
+import networkx
+
+import pyperf
+
+
+DATA_FILE = Path(__file__).parent / "data" / "amazon0302.txt.gz"
+
+
+graph = networkx.read_adjlist(DATA_FILE)
+
+
+def bench_shortest_path():
+    collections.deque(networkx.shortest_path_length(graph, "0"))
+
+
+def bench_connected_components():
+    networkx.number_connected_components(graph)
+
+
+def bench_k_core():
+    networkx.k_core(graph)
+
+
+BENCHMARKS = {
+    "shortest_path": bench_shortest_path,
+    "connected_components": bench_connected_components,
+    "k_core": bench_k_core,
+}
+
+
+def add_cmdline_args(cmd, args):
+    cmd.append(args.benchmark)
+
+
+def add_parser_args(parser):
+    parser.add_argument("benchmark", choices=BENCHMARKS, help="Which benchmark to run.")
+
+
+if __name__ == "__main__":
+    runner = pyperf.Runner(add_cmdline_args=add_cmdline_args)
+    runner.metadata["description"] = "NetworkX benchmark"
+    add_parser_args(runner.argparser)
+    args = runner.parse_args()
+    benchmark = args.benchmark
+
+    runner.bench_func(args.benchmark, BENCHMARKS[args.benchmark])