# Copyright 2020 Google Inc. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Example of Python using C++ benchmark framework. To run this example, you must first install the `google_benchmark` Python package. To install using `setup.py`, download and extract the `google_benchmark` source. In the extracted directory, execute: python setup.py install """ import random import time import google_benchmark as benchmark from google_benchmark import Counter @benchmark.register def empty(state): while state: pass @benchmark.register def sum_million(state): while state: sum(range(1_000_000)) @benchmark.register def pause_timing(state): """Pause timing every iteration.""" while state: # Construct a list of random ints every iteration without timing it state.pause_timing() random_list = [random.randint(0, 100) for _ in range(100)] state.resume_timing() # Time the in place sorting algorithm random_list.sort() @benchmark.register def skipped(state): if True: # Test some predicate here. state.skip_with_error("some error") return # NOTE: You must explicitly return, or benchmark will continue. ... # Benchmark code would be here. @benchmark.register @benchmark.option.use_manual_time() def manual_timing(state): while state: # Manually count Python CPU time start = time.perf_counter() # perf_counter_ns() in Python 3.7+ # Something to benchmark time.sleep(0.01) end = time.perf_counter() state.set_iteration_time(end - start) @benchmark.register def custom_counters(state): """Collect custom metric using benchmark.Counter.""" num_foo = 0.0 while state: # Benchmark some code here pass # Collect some custom metric named foo num_foo += 0.13 # Automatic Counter from numbers. state.counters["foo"] = num_foo # Set a counter as a rate. state.counters["foo_rate"] = Counter(num_foo, Counter.kIsRate) # Set a counter as an inverse of rate. state.counters["foo_inv_rate"] = Counter( num_foo, Counter.kIsRate | Counter.kInvert ) # Set a counter as a thread-average quantity. state.counters["foo_avg"] = Counter(num_foo, Counter.kAvgThreads) # There's also a combined flag: state.counters["foo_avg_rate"] = Counter(num_foo, Counter.kAvgThreadsRate) @benchmark.register @benchmark.option.measure_process_cpu_time() @benchmark.option.use_real_time() def with_options(state): while state: sum(range(1_000_000)) @benchmark.register(name="sum_million_microseconds") @benchmark.option.unit(benchmark.kMicrosecond) def with_options2(state): while state: sum(range(1_000_000)) @benchmark.register @benchmark.option.arg(100) @benchmark.option.arg(1000) def passing_argument(state): while state: sum(range(state.range(0))) @benchmark.register @benchmark.option.range(8, limit=8 << 10) def using_range(state): while state: sum(range(state.range(0))) @benchmark.register @benchmark.option.range_multiplier(2) @benchmark.option.range(1 << 10, 1 << 18) @benchmark.option.complexity(benchmark.oN) def computing_complexity(state): while state: sum(range(state.range(0))) state.complexity_n = state.range(0) if __name__ == "__main__": benchmark.main()