Python 资源监测工具 - 实时监控 CPU、内存、GPU 和网络状态

import psutil
import GPUtil
import time
import sys
import keyboard
from termcolor import colored
import threading

def print_cpu_and_memory_usage():
    cpu_percent = psutil.cpu_percent()
    mem = psutil.virtual_memory()
    mem_percent = mem.percent
    mem_used = round(mem.used / 1024 / 1024, 2)
    mem_total = round(mem.total / 1024 / 1024, 2)

    print(colored(f'  CPU 使用率： {cpu_percent}% ({psutil.cpu_count()} 核)', 'green'))
    print(colored(f'  内存使用率： {mem_percent}% ({mem_used} / {mem_total} MB)', 'green'))

def print_gpu_usage():
    gpus = GPUtil.getGPUs()

    for i, gpu in enumerate(gpus):
        gpu_name = gpu.name
        gpu_memory_total = gpu.memoryTotal
        gpu_memory_used = gpu.memoryUsed
        gpu_memory_free = gpu_memory_total - gpu_memory_used
        gpu_memory_percent = gpu_memory_used / gpu_memory_total * 100

        print(colored(f'  GPU {i + 1} 型号： {gpu_name}', 'cyan'))
        print(colored(f'  显存使用率： {gpu_memory_percent:.2f}% ({gpu_memory_used} / {gpu_memory_total} MB)', 'cyan'))
        print(colored(f'  显存剩余大小： {gpu_memory_free:.2f} MB', 'cyan'))

def print_network_usage():
    net_io = psutil.net_io_counters()
    net_speed_sent = round(net_io.bytes_sent / 1024 / 1024, 2)
    net_speed_recv = round(net_io.bytes_recv / 1024 / 1024, 2)

    if 'en0' in psutil.net_if_stats():
        print(colored(f'  有线网卡状态： {'已连接' if psutil.net_if_stats()['en0'].isup else '未连接'}', 'yellow'))
    else:
        print(colored(f'  有线网卡状态： 未连接', 'yellow'))
    print(colored(f'  网卡上传速度： {net_speed_sent} MB/s', 'yellow'))
    print(colored(f'  网卡下载速度： {net_speed_recv} MB/s', 'yellow'))

def print_instructions():
    print(colored('以下是程序操作说明：', 'magenta'))
    print('  1. 按 s 键刷新数据。')
    print('  2. 按 p 键暂停/继续程序输出。')
    print('  3. 按 c 键关闭程序。')
    print(colored('--------------------------------------', 'magenta'))

def print_status(status, refresh_time):
    print(colored(f'当前监测状态：{status}，上次刷新时间：{time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(refresh_time))}。', 'magenta'))

def refresh_data():
    status = '已刷新'
    print(colored('正在刷新数据，请稍候......', 'magenta'))
    print_cpu_and_memory_usage()
    print_gpu_usage()
    print_network_usage()
    refresh_time = time.time()
    return status, refresh_time

def pause_resume(paused):
    if paused:
        paused = False
        status = '继续输出'
        print(colored('已取消暂停，继续输出监测结果。', 'magenta'))
    else:
        paused = True
        status = '已暂停'
        print(colored('已暂停程序，停止输出监测结果。', 'magenta'))
    return paused, status

def close_program():
    status = '正在关闭'
    refresh_time = time.time()
    print(colored('正在关闭程序，请稍候......', 'magenta'))
    sys.exit(0)

def monitor():
    while True:
        if not paused:
            print_cpu_and_memory_usage()
            print_gpu_usage()
            print_network_usage()
            print_status(status, refresh_time)
        time.sleep(1)

def main():
    print_instructions()
    print(colored('开始监测，按 Ctrl+C 可以结束程序。', 'magenta'))

    global paused
    global status
    global refresh_time
    paused = False
    status = '运行中'
    refresh_time = time.time()

    t1 = threading.Thread(target=monitor)
    t1.start()

    while True:
        if keyboard.is_pressed('s'): # s键
            status, refresh_time = refresh_data()

        if keyboard.is_pressed('p'): # p键
            paused, status = pause_resume(paused)

        if keyboard.is_pressed('c'): # c键
            close_program()

        time.sleep(0.1)

if __name__ == '__main__':
    main()