| # 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 |
| 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() |