From 016e225c74f68ab797b1f88a1b1e643584feeaf1 Mon Sep 17 00:00:00 2001
From: Jaewook Lee <11328376+jaewooklee93@users.noreply.github.com>
Date: Sun, 1 Sep 2024 14:47:58 +0900
Subject: [PATCH] in progress

---
 cpu-bench/bench.py | 86 +++++++++++++++++++++++-----------------------
 1 file changed, 43 insertions(+), 43 deletions(-)

diff --git a/cpu-bench/bench.py b/cpu-bench/bench.py
index 8ffa1fd..43be1b3 100644
--- a/cpu-bench/bench.py
+++ b/cpu-bench/bench.py
@@ -1,43 +1,43 @@
-#!/usr/bin/env python
-
-def ensure(*packages):
-    for pkg in packages:
-        try: __import__(pkg)
-        except: import os; os.system(f'pip install -q {pkg}')
-ensure('pandas', 'tabulate')
-
-import subprocess, multiprocessing as mp, warnings, pandas as pd
-from tqdm.auto import tqdm
-from tabulate import tabulate
-warnings.filterwarnings("ignore")
-R, G, B, W = (f'\x1b[{x}m' for x in (31, 32, 34, 0))
-subprocess.run('clear')
-subprocess.run('neofetch')
-
-command = lambda core: f'sysbench cpu --cpu-max-prime=20000 --time=1 --threads={core} run | grep second'
-
-print(f'{G}$ {command("$(nproc)")}{W}', flush=True)
-
-
-def speed(core):
-    output = subprocess.run(
-        command(core), shell=True, capture_output=True, text=True
-    ).stdout.split()[-1]
-    return float(output)
-
-df = []
-for core in range(1, mp.cpu_count()+1):
-    s = speed(core)
-    row = {
-        '#Threads': core,
-        'Throughput(/s)': s,
-        '(per-core)': s/core
-    }
-    df.append(row)
-df = pd.DataFrame(df)
-df.to_csv('result.csv', index=False)
-
-df.iloc[:, 0] = df.iloc[:, 0].apply(lambda s: f'{R}{s}{W}')
-df.iloc[:, 1] = df.iloc[:, 1].apply(lambda s: f'{G}{int(s)}{W}')
-df.iloc[:, 2] = df.iloc[:, 2].apply(lambda s: f'{B}{int(s)}{W}')
-print(tabulate(df, headers='keys', tablefmt='rounded_outline', showindex=False))
+#!/usr/bin/env python
+
+def ensure(*packages):
+    for pkg in packages:
+        try: __import__(pkg)
+        except: import os; os.system(f'pip install -q {pkg}')
+ensure('pandas', 'tabulate')
+
+import subprocess, multiprocessing as mp, warnings, pandas as pd
+from tqdm.auto import tqdm
+from tabulate import tabulate
+warnings.filterwarnings("ignore")
+R, G, B, W = (f'\x1b[{x}m' for x in (31, 32, 34, 0))
+subprocess.run('clear')
+subprocess.run('neofetch')
+
+command = lambda core: f'sysbench cpu --cpu-max-prime=20000 --time=1 --threads={core} run | grep second'
+
+print(f'{G}$ {command("$(nproc)")}{W}', flush=True)
+
+
+def speed(core):
+    output = subprocess.run(
+        command(core), shell=True, capture_output=True, text=True
+    ).stdout.split()[-1]
+    return float(output)
+
+df = []
+for core in range(1, mp.cpu_count()+1):
+    s = speed(core)
+    row = {
+        '#Threads': core,
+        'Throughput(/s)': s,
+        '(per-core)': s/core
+    }
+    df.append(row)
+df = pd.DataFrame(df)
+df.to_csv('result.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))