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#!/usr/bin/env python
# /// script
# requires-python = ">=3.10"
# dependencies = [
# "numpy",
# ]
# ///
import argparse
import json
import numpy as np
parser = argparse.ArgumentParser()
parser.add_argument("file", help="JSON file with benchmark results")
args = parser.parse_args()
with open(args.file) as f:
results = json.load(f)["results"]
commands = [b["command"] for b in results]
times = [b["times"] for b in results]
for command, ts in zip(commands, times):
p05 = np.percentile(ts, 5)
p25 = np.percentile(ts, 25)
p75 = np.percentile(ts, 75)
p95 = np.percentile(ts, 95)
iqr = p75 - p25
print(f"Command '{command}'")
print(f" runs: {len(ts):8d}")
print(f" mean: {np.mean(ts):8.3f} s")
print(f" stddev: {np.std(ts, ddof=1):8.3f} s")
print(f" median: {np.median(ts):8.3f} s")
print(f" min: {np.min(ts):8.3f} s")
print(f" max: {np.max(ts):8.3f} s")
print()
print(" percentiles:")
print(f" P_05 .. P_95: {p05:.3f} s .. {p95:.3f} s")
print(f" P_25 .. P_75: {p25:.3f} s .. {p75:.3f} s (IQR = {iqr:.3f} s)")
print()
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