性能监控
判断系统，然后再监控程序运行期间机器的性能
import psutil
import matplotlib.pyplot as plt
import time
import matplotlib
import subprocess
import platform
import os try:import GPUtilimport pynvml
except ImportError as e:print(f"导入GPU模块失败,请先安装GPU驱动：{e}")def is_windows():"""检查当前系统是否为Windows"""return platform.system() == "Windows"def is_linux():"""检查当前系统是否为Linux"""return platform.system() == "Linux"class Linux:"""Linux系统性能监控类"""@staticmethoddef get_cpu_info_linux():"""获取Linux系统的CPU使用率和频率"""cpu_usage = psutil.cpu_percent(interval=1)cpu_freq = psutil.cpu_freq().currentreturn cpu_usage, cpu_freq@staticmethoddef get_memory_info_linux():"""获取Linux系统的内存使用信息"""memory = psutil.virtual_memory()memory_used_gb = memory.used / (1024 ** 3)return memory_used_gb@staticmethoddef get_gpu_info_linux():"""获取Linux系统的GPU信息"""return 0, 0 # 示例值，需要实际实现@staticmethoddef get_cpu_model_unix():"""获取Unix系统的CPU型号"""try:if platform.system() == "Linux":with open('/proc/cpuinfo') as f:for line in f:if line.strip().startswith('model name'):return line.strip().split(':')[1].strip()elif platform.system() == "Darwin":return subprocess.check_output(["sysctl", "-n", "machdep.cpu.brand_string"],universal_newlines=True).strip()except Exception as e:print(f"Error: {e}")return Noneclass run:"""运行性能监控的主类"""def __init__(self):"""初始化run类，创建windows和Linux类的实例"""self.win = windows()self.linux = Linux()# 设置matplotlib以支持中文字符matplotlib.rcParams['font.sans-serif'] = ['SimHei'] # 'SimHei'是常用的中文黑体字体matplotlib.rcParams['axes.unicode_minus'] = False # 用于正确显示负号matplotlib.rcParams['font.size'] = 12 # 调整字体大小def collect_system_data(self, total_duration, interval):"""根据当前系统是Windows还是Linux，收集系统数据"""if is_windows():return self.collect_system_data_windows(total_duration, interval)elif is_linux():return self.collect_system_data_linux(total_duration, interval)else:raise NotImplementedError("Unsupported operating system.")def collect_system_data_windows(self, total_duration, interval):"""在Windows系统上收集系统数据"""start_time = time.time()data = []gpu, gpu_handle = self.win.initialize_gpu_info()while time.time() - start_time < total_duration:cpu_usage, cpu_freq = self.win.get_cpu_info()memory_used_gb = self.win.get_memory_info()gpu_usage, gpu_memory_used = self.win.get_gpu_info(gpu)gpu_temp = self.win.get_gpu_temperature(gpu_handle)data.append((cpu_usage, cpu_freq, memory_used_gb, gpu_usage, gpu_memory_used, gpu_temp))time.sleep(interval)return datadef collect_system_data_linux(self, total_duration, interval):"""在Linux系统上收集系统数据"""start_time = time.time()data = []while time.time() - start_time < total_duration:cpu_usage, cpu_freq = self.linux.get_cpu_info_linux()memory_used_gb = self.linux.get_memory_info_linux()gpu_usage, gpu_memory_used = self.linux.get_gpu_info_linux()data.append((cpu_usage, cpu_freq, memory_used_gb, gpu_usage, gpu_memory_used))time.sleep(interval)def plot_system_data(self, data, cpu_model, gpu_list):"""绘制收集的系统数据并将其保存为PNG文件"""plt.figure(figsize=(14, 12))plt.subplots_adjust(hspace=0.5)titles = ['CPU 使用率 (%)', 'CPU 频率 (MHz)','内存使用量 (GB)', 'GPU 使用率 (%)','GPU 内存使用量 (MB)', 'GPU 温度 (°C)']for i in range(6):plt.subplot(3, 2, i + 1)plt.plot([entry[i] for entry in data], label=titles[i], color=['blue', 'green', 'red', 'purple', 'orange', 'cyan'][i])plt.title(f'{titles[i]}随时间变化')plt.xlabel('时间 (秒)')plt.ylabel(titles[i], rotation=0, labelpad=45)plt.legend()plt.suptitle(f'系统性能监控 \n\n CPU 型号:{cpu_model} \n GPU:{gpu_list[0]} \n 型号:{gpu_list[1]} \n 显存大小:{gpu_list[2]}(MB) \n', fontsize=16)plt.tight_layout()plt.savefig('间段性能图.png')# 显示图形plt.show()current_path = os.getcwd()print("当前工作目录是：", current_path)script_path = os.path.dirname(os.path.abspath(__file__))print("脚本所在目录是：", script_path)print("\n监控图表已保存为 '间段性能图.png'")# 还未调试完成def run_monitor(self, total_duration, interval):"""监控指定时间的系统性能"""cpu_model = self.linux.get_cpu_model_unix()print(cpu_model)gpu_info = self.win.get_gpu_xh_info()gpu_list = []if gpu_info:for gpu in gpu_info:gpu_list.append(gpu['GPU'])gpu_list.append(gpu['型号'])gpu_list.append(gpu['显存大小 (MB)'])else:print("无法获取GPU信息。请确保已安装NVIDIA驱动和nvidia-smi工具。")data = self.collect_system_data(total_duration, interval)self.plot_system_data(data, gpu_list)def run_and_monitor(self, script_path, interval=1):"""运行一个Python脚本并监控其性能"""spitted_test = script_path.split('.')[-1]if spitted_test == 'py': # python脚本process = subprocess.Popen(['python', script_path])elif spitted_test == 'ps1': # PowerShellprocess = subprocess.Popen(["powershell.exe", script_path], stdout=subprocess.PIPE)data = []while True:if process.poll() is not None:break current_data = self.collect_system_data(1, interval) if current_data:data.extend(current_data)time.sleep(interval)cpu_model = self.win.get_cpu_model_windows()gpu_info = self.win.get_gpu_xh_info()gpu_list = []if gpu_info:for gpu in gpu_info:gpu_list.append(gpu['GPU'])gpu_list.append(gpu['型号'])gpu_list.append(gpu['显存大小 (MB)'])else:print("无法获取GPU信息。请确保已安装NVIDIA驱动和nvidia-smi工具。")self.plot_system_data(data, cpu_model, gpu_list)class windows:"""Windows系统性能监控类"""def initialize_gpu_info(self):"""初始化并返回使用pynvml和GPUtil的GPU信息"""pynvml.nvmlInit()gpus = GPUtil.getGPUs()if gpus:return gpus[0], pynvml.nvmlDeviceGetHandleByIndex(0)return None, Nonedef get_cpu_info(self):"""获取并返回当前CPU的使用率和频率"""cpu_usage = psutil.cpu_percent(interval=1)cpu_freq = psutil.cpu_freq().currentreturn cpu_usage, cpu_freqdef get_memory_info(self):"""获取并返回以GB为单位的已使用内存量"""memory = psutil.virtual_memory()memory_used_gb = memory.used / (1024 ** 3)return memory_used_gbdef get_gpu_info(self, gpu):"""如果有GPU可用，则返回GPU的使用率和已使用内存"""if gpu:return gpu.load * 100, gpu.memoryUsedreturn 0, 0def get_gpu_temperature(self, handle):"""根据其句柄返回GPU的温度"""if handle:return pynvml.nvmlDeviceGetTemperature(handle, pynvml.NVML_TEMPERATURE_GPU)return 0def get_cpu_model_windows(self):"""获取Windows系统的CPU型号"""try:return subprocess.check_output(["wmic", "cpu", "get", "name"], universal_newlines=True).strip().split('\n')[2]except Exception as e:print(f"Error: {e}")return Nonedef get_gpu_xh_info(self):"""使用nvidia-smi命令获取有关GPU的扩展信息"""try:output = subprocess.check_output(['nvidia-smi', '--query-gpu=name,memory.total', '--format=csv,noheader,nounits'])output = output.decode('utf-8').strip().split('\n')gpu_info = [line.split(',') for line in output]gpu_data = []for idx, (model, memory) in enumerate(gpu_info):gpu_data.append({'GPU': idx + 1,'型号': model,'显存大小 (MB)': int(memory)})return gpu_dataexcept (subprocess.CalledProcessError, FileNotFoundError):return Noneif __name__ == "__main__":print('监控程序运行时的机器性能状态...\n 支持 py 和 ps1')script_path = input('输入程序路径：')jk_start=run()# script_path = 'run.py'print('start...\n')jk_start.run_and_monitor(script_path)print('end\n')print('5秒之后退出')time.sleep(5)有个问题还没解决
pyinstaller --onefile .\monitor_performance.py
打包成exe执行之后，保存的图片中并没有画出线条
