[test] measure cpu percentage during benchmark

2 files changed, 59 insertions, 0 deletions

diff --git a/testing/tests/benchmarks/conftest.py b/testing/tests/benchmarks/conftest.py
index bec5d7ab..543f06b8 100644
--- a/testing/tests/benchmarks/conftest.py
+++ b/testing/tests/benchmarks/conftest.py
@@ -1,4 +1,6 @@
 import base64
+import os
+import psutil
 import pytest
 import random
 
@@ -73,3 +75,24 @@ def txbenchmark_with_setup(benchmark):
                                       rounds=4, warmup_rounds=1)
         return threads.deferToThread(bench)
     return blockOnThreadWithSetup
+
+
+#
+# resource monitoring
+#
+
+@pytest.fixture
+def monitored_benchmark(benchmark, request):
+
+    def _monitored_benchmark(fun, *args, **kwargs):
+        process = psutil.Process(os.getpid())
+        process.cpu_percent()
+        benchmark.pedantic(
+            fun, args=args, kwargs=kwargs,
+            rounds=1, iterations=1, warmup_rounds=0)
+        percent = process.cpu_percent()
+        # store value in benchmark session, so json output can be updated
+        bs = request.config._benchmarksession
+        bs.benchmarks[0].stats.cpu_percent = percent
+
+    return _monitored_benchmark
diff --git a/testing/tests/benchmarks/test_cpu.py b/testing/tests/benchmarks/test_cpu.py
new file mode 100644
index 00000000..fba6a6d4
--- /dev/null
+++ b/testing/tests/benchmarks/test_cpu.py
@@ -0,0 +1,36 @@
+import pytest
+import random
+import time
+
+from decimal import Decimal
+
+
+def bellardBig(n):
+    # http://en.wikipedia.org/wiki/Bellard%27s_formula
+    pi = Decimal(0)
+    k = 0
+    while k < n:
+        pi += (Decimal(-1) ** k / (1024 ** k)) * (
+            Decimal(256) / (10 * k + 1) +
+            Decimal(1) / (10 * k + 9) -
+            Decimal(64) / (10 * k + 3) -
+            Decimal(32) / (4 * k + 1) -
+            Decimal(4) / (10 * k + 5) -
+            Decimal(4) / (10 * k + 7) -
+            Decimal(1) / (4 * k + 3))
+        k += 1
+    pi = pi * 1 / (2 ** 6)
+    return pi
+
+
+def test_long_operation(monitored_benchmark):
+
+    def _long_operation():
+        sleep = [random.uniform(0.5, 1.5) for _ in xrange(3)]
+        while sleep:
+            t = sleep.pop()
+            time.sleep(t)
+            bellardBig(int((10 ** 3) * t))
+
+    results = monitored_benchmark(_long_operation)
+    print results