algN/concurrency/uploadGPU.py

# -*- coding: utf-8 -*-
from threading import Thread
from time import sleep, time
from traceback import format_exc

#from common.Constant import init_progess
import json,os,psutil,GPUtil,platform,socket 
from kafka import KafkaProducer, KafkaConsumer
#from util.KafkaUtils import CustomerKafkaProducer
from common.YmlConstant import service_yml_path, kafka_yml_path
class uploadGPUinfos(Thread):
    __slots__ = ('__kafka_config', "_context")

    def __init__(self, *args):
        super().__init__()
        self.__context,self.__kafka_config = args
        self.__uploadInterval = self.__context['GPUpollInterval']
        #kafkaProducer = CustomerKafkaProducer(self.__kafka_config)
        self.__producer = KafkaProducer(
            bootstrap_servers=self.__kafka_config['bootstrap_servers'],#tencent yun
            value_serializer=lambda v: v.encode('utf-8'))
        
        self.__topic = self.__kafka_config["topicGPU"]
    def run(self):
        while True:

            try:
                #获取当前的gpu状态信息
                msg_dict =   get_system_info()  
                #发送GPU状态到指定的topic
                msg = json.dumps(msg_dict)
      
                # 假设生产的消息为键值对（不是一定要键值对），且序列化方式为json

                #future = kafkaProducer.sender(topic_on,msg)
                future =  self.__producer .send(self.__topic,msg)
                try:
                     future.get(timeout=10)
                except kafka_errors:
                     traceback.format_exc()
            
                sleep(self.__uploadInterval)
      
            except Exception as e:
                print(e)
                continue
                #logger.error("上传GPU服务器线程状态异常:{}, requestId:{}", format_exc(), request_id)
           
                
 
 
def get_system_info():
    # 初始化一个字典来存储系统信息
    system_info = {}

    # 获取CPU信息
    system_info['CPU'] = {
        'Physical Cores': psutil.cpu_count(logical=False),  # 物理核心数
        'Logical Cores': psutil.cpu_count(logical=True),   # 逻辑核心数
        'Current Frequency': psutil.cpu_freq().current,    # 当前频率
        'Usage Per Core': psutil.cpu_percent(interval=1, percpu=True),  # 每个核心的使用率
        'Total Usage': psutil.cpu_percent(interval=1)      # 总体CPU使用率
    }

    # 获取内存信息
    memory = psutil.virtual_memory()
    system_info['Memory'] = {
        'Total': memory.total / (1024 ** 3),  # 总内存，单位为GB
        'Available': memory.available / (1024 ** 3),  # 可用内存
        'Used': memory.used / (1024 ** 3),    # 已用内存
        'Usage Percentage': memory.percent    # 内存使用率
    }

    # 获取GPU信息
    gpus = GPUtil.getGPUs()
    system_info['GPU'] = []
    for gpu in gpus:
        gpu_info = {
            'ID': gpu.id,
            'Name': gpu.name,
            'Load': gpu.load * 100,  # GPU负载，百分比
            'Memory Total': gpu.memoryTotal,  # 总显存，单位为MB
            'Memory Used': gpu.memoryUsed,    # 已用显存
            'Memory Free': gpu.memoryFree,    # 可用显存
            'Temperature': gpu.temperature    # GPU温度
        }
        system_info['GPU'].append(gpu_info)

    # 获取系统信息
    system_info['System'] = {
        'Platform': platform.system(),  # 操作系统类型
        'Platform Version': platform.version(),  # 操作系统版本
        'Platform Release': platform.release(),  # 操作系统发行版本
        'Platform Node': platform.node(),  # 网络名称
        'Machine': platform.machine(),  # 硬件架构
        'Processor': platform.processor()  # CPU架构
    }

    # 获取本机局域网IP地址（非回环地址）
    try:
        # 获取所有网络接口信息
        net_if_addrs = psutil.net_if_addrs()
        for interface, addrs in net_if_addrs.items():
            for addr in addrs:
                # 筛选IPv4地址且非回环地址
                if addr.family == socket.AF_INET and not addr.address.startswith("127."):
                    system_info['System']['Local IP Address'] = addr.address
                    break
            if 'Local IP Address' in system_info['System']:
                break
        else:
            system_info['System']['Local IP Address'] = "No local IP found"
    except Exception as e:
        system_info['System']['Local IP Address'] = "Unable to retrieve local IP address"

    return system_info
    

  
    
if __name__=="__main__": 


    context = {
            'GPUpollInterval':1,
            'topic':'server-status',
    }  
    kafka_config = {
            'bootstrap_servers':['192.168.10.66:9092']
    }
    
    base_dir, env = '/home/thsw2/WJ/test/tuoheng_algN','test'
    
  

        
        
    upload_thread = uploadGPUinfos(context,kafka_config)
    upload_thread.setDaemon(False)

    upload_thread.start()

    
    # 主线程等待守护线程运行
    try:
        while True:
            sleep(1)
    except KeyboardInterrupt:
        print("主线程退出")