Smallest possible benchmark result tracking.

benchmarks/conftest.py

@@ -9,6 +9,8 @@ from os.path import abspath
 from shutil import which, rmtree
 from tempfile import mkdtemp
 from pathlib import Path
+from contextlib import contextmanager
+from time import time
 
 import pytest
 import pytest_twisted
@@ -105,3 +107,22 @@ def client_node(request, grid, storage_nodes, number_of_nodes) -> Client:
     )
     print(f"Client node pid: {client_node.process.transport.pid}")
     return client_node
+
+
+class Benchmarker:
+    """Keep track of benchmarking results."""
+
+    @contextmanager
+    def record(self, name, **parameters):
+        """Record the timing of running some code, if it succeeds."""
+        start = time()
+        yield
+        elapsed = time() - start
+        # For now we just print the outcome:
+        parameters = " ".join(f"{k}={v}" for (k, v) in parameters.items())
+        print(f"BENCHMARK RESULT: {name} {parameters} elapsed {elapsed} secs")
+
+
+@pytest.fixture(scope="session")
+def tahoe_benchmarker():
+    return Benchmarker()

benchmarks/test_cli.py

@@ -12,7 +12,9 @@ def cli_alias(client_node):
     cli(client_node.process, "create-alias", "cli")
 
 
-def test_get_put_one_file(client_node, cli_alias, tmp_path):
+def test_get_put_one_file(
+    client_node, cli_alias, tmp_path, tahoe_benchmarker, number_of_nodes
+):
     """
     Upload a file with ``tahoe put`` and then download it with ``tahoe get``,
     measuring the latency of both operations.
@@ -20,11 +22,17 @@ def test_get_put_one_file(client_node, cli_alias, tmp_path):
     file_size = 1000  # parameterize later on
     file_path = tmp_path / "file"
     DATA = b"0123456789" * (file_size // 10)
-
     with file_path.open("wb") as f:
         f.write(DATA)
+
+    with tahoe_benchmarker.record(
+        "cli-put-file", file_size=file_size, number_of_nodes=number_of_nodes
+    ):
         cli(client_node.process, "put", str(file_path), "cli:tostdout")
 
+    with tahoe_benchmarker.record(
+        "cli-get-file", file_size=file_size, number_of_nodes=number_of_nodes
+    ):
         p = Popen(
             [
                 "tahoe",