#!/usr/bin/env python

import subprocess, multiprocessing as mp, warnings, pandas as pd
from tabulate import tabulate
warnings.filterwarnings("ignore")
R, G, B, W = (f'\x1b[{x}m' for x in (31, 32, 34, 0))
subprocess.run('neofetch')

def speed(core):
    output = subprocess.run(
        f'sysbench cpu --threads={core} run | grep "events per second"',
        shell=True, capture_output=True, text=True).stdout.split()[-1]
    return float(output)        

df = []
for core in range(1, mp.cpu_count()+2):
    s = speed(core)
    row = {
        '#Threads': core, 
        'Throughput': s,
        '(per-core)': s/core
    }
    df.append(row)
df = pd.DataFrame(df)
df.to_csv('bench.csv', index=False)

df.iloc[:, 0] = df.iloc[:, 0].apply(lambda s: f'{R}{s}{W}')
df.iloc[:, 1] = df.iloc[:, 1].apply(lambda s: f'{G}{int(s)}{W}')
df.iloc[:, 2] = df.iloc[:, 2].apply(lambda s: f'{B}{int(s)}{W}')
print(tabulate(df, headers='keys', tablefmt='rounded_outline', showindex=False))