77 lines
2.8 KiB
Python
77 lines
2.8 KiB
Python
"""
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A benchmark suite for Performance Anti-Patterns
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"""
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import timeit
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import pathlib
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import sys
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from statistics import fmean
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from rich.console import Console
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from rich.table import Table
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from rich.text import Text
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REPEAT = 5
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TIMES = 5
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def format_delta(a: float, b: float, d: float) -> Text:
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if a < b:
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if d < 10:
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col = "medium_spring_green"
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elif 10 <= d < 20:
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col = "spring_green1"
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elif 20 <= d < 40:
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col = "spring_green2"
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else:
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col = "green1"
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return Text(f"{b:.3f} ({d:.1f}%)", style=col)
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else:
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return Text(f"{b:.3f} (-{d:.1f}%)", style="red")
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if __name__ == "__main__":
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table = Table(title=f"Anti-Pattern Benchmark Suite, repeat={REPEAT}, number={TIMES}")
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table.add_column("Benchmark", justify="right", style="cyan", no_wrap=True)
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table.add_column("Min", width=7)
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table.add_column("Max", width=7)
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table.add_column("Mean", width=7)
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table.add_column("Min (+)", style="blue", width=15)
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table.add_column("Max (+)", style="blue", width=15)
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table.add_column("Mean (+)", style="blue", width=15)
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profiles_out = pathlib.Path(__file__).parent / 'profiles'
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if not profiles_out.exists():
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profiles_out.mkdir()
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n = 0
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for f in pathlib.Path(__file__).parent.glob("bench_*.py"):
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if len(sys.argv) > 1 and f.stem != f"bench_{sys.argv[1]}":
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continue
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i = __import__(f.stem, globals(), locals(), )
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if hasattr(i, "__benchmarks__"):
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for benchmark in i.__benchmarks__:
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n += 1
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func1, func2, desc = benchmark
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without_result = timeit.repeat(func1, repeat=REPEAT, number=TIMES)
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with_result = timeit.repeat(func2, repeat=REPEAT, number=TIMES)
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delta_mean = (abs(fmean(with_result) - fmean(without_result)) / fmean(without_result)) * 100.0
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delta_min = (abs(min(with_result) - min(without_result)) / min(without_result)) * 100.0
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delta_max = (abs(max(with_result) - max(without_result)) / max(without_result)) * 100.0
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fdelta_min = format_delta(min(with_result), min(without_result), delta_min)
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fdelta_max = format_delta(max(with_result), max(without_result), delta_max)
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fdelta_mean = format_delta(fmean(with_result), fmean(without_result), delta_mean)
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table.add_row(
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desc,
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"{:.3f}".format(min(without_result)),
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"{:.3f}".format(max(without_result)),
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"{:.3f}".format(fmean(without_result)),
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fdelta_min,
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fdelta_max,
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fdelta_mean,
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)
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console = Console(width=150)
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console.print(table)
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