Grouping google benchmark result

cmp_gbm.py

#!/usr/bin/env python3

"""
Usage: ./a.out --benchmark_format=json | ./cmp_gbm.py

from

bench_fastmod/16/32             176 ns          171 ns      3972393
bench_fastmod/16/128            192 ns          190 ns      3620738
bench_fastmod/16/224            195 ns          192 ns      3614277
bench_fastmod/64/32             484 ns          478 ns      1626646
bench_fastmod/64/128            456 ns          449 ns      1376393
bench_fastmod/64/224            490 ns          483 ns      1431184

to

16/32
    bench_fastmod           153.89ns    100.00%
    bench_fastmod16         139.52ns     90.66%
    bench_fastmod4          153.68ns     99.86%
    bench_mod               198.32ns    128.87%
16/128
    bench_fastmod           148.41ns    100.00%
    bench_fastmod16         139.52ns     94.01%
    bench_fastmod4          142.18ns     95.80%
    bench_mod               186.52ns    125.68%
"""

import json
import sys

funs = set()
args = set()
data = {} 

for bm in json.loads(sys.stdin.read())['benchmarks']:
    fn, *rest = bm['name'].split('/')
    funs.add(fn)
    args.add(tuple(int(i) for i in rest))
    data[bm['name']] = bm

funs = sorted(list(funs))
args = sorted(list(args))
#max_name = max(len(i) for i in funs)

for a in args:
    tag = "/".join(str(i) for i in [*a,])
    print(tag)
    base_time = data["/".join([funs[0], tag])]["cpu_time"]
    for f in funs:
        name = "/".join([f, tag])
        perf = 100.0
        if f != funs[0]:
            perf = data[name]["cpu_time"] / base_time * 100
        print("    {:20s}{:>10.2f}{}{:>10.2f}%".format(f, data[name]["cpu_time"], data[name]["time_unit"], perf))