def test_omits_aggregates():
name = "AllocateDeallocate<Jemalloc>/size:1048576/real_time"
google_aggregate = {
"aggregate_name": "mean",
"cpu_time": 1757.428694267678,
"iterations": 3,
"name": "AllocateDeallocate<Jemalloc>/size:1048576/real_time_mean",
"real_time": 1849.3869337041162,
"repetitions": 0,
"run_name": name,
"run_type": "aggregate",
"threads": 1,
"time_unit": "ns",
}
google_result = {
"cpu_time": 1778.6004847419827,
"iterations": 352765,
"name": name,
"real_time": 1835.3137357788837,
"repetition_index": 0,
"repetitions": 0,
"run_name": name,
"run_type": "iteration",
"threads": 1,
"time_unit": "ns",
}
archery_result = {
"counters": {
"iterations": 352765,
"repetition_index": 0,
"repetitions": 0,
"run_name": name,
"threads": 1
},
"name": name,
"unit": "ns",
"less_is_better": True,
"values": [1835.3137357788837],
"time_unit": "ns",
"times": [1835.3137357788837],
}
assert google_aggregate["run_type"] == "aggregate"
assert google_result["run_type"] == "iteration"
observation1 = GoogleBenchmarkObservation(**google_aggregate)
observation2 = GoogleBenchmarkObservation(**google_result)
benchmark = GoogleBenchmark(name, [observation1, observation2])
result = json.dumps(benchmark, cls=JsonEncoder)
assert json.loads(result) == archery_result
def assert_benchmark(name, google_result, archery_result):
observation = GoogleBenchmarkObservation(**google_result)
benchmark = GoogleBenchmark(name, [observation])
result = json.dumps(benchmark, cls=JsonEncoder)
assert json.loads(result) == archery_result