Linux获取指定进程CPU和内存占用率
创建如下python程序,caclute_memory_occupied.py:
import psutil
import pynvml
import time
class MonitorProcess:
def __init__(self,pid_num):
self.pid = pid_num
self.pro = psutil.Process(pid_num)
self.pro_rss = 0.0
self.pro_vss = 0.0
self.pro_cpu = 0.0
self.pro_io = 0.0
self.pro_gpu = []
try:
pynvml.nvmlInit()
self.deviceCount = pynvml.nvmlDeviceGetCount()
except:
print("No GPU")
def Memonitor(self):
self.pro_rss = float(self.pro.memory_info().rss)/1024/1024
self.pro_vss = float(self.pro.memory_info().vms)/1024/1024
def CPUMonitor(self):
self.pro_cpu = self.pro.cpu_percent(interval = 1)
def GPUMonitor(self):
self.pro_gpu = []
try:
for gup_id in xrange(0,self.deviceCount):
handle = pynvml.nvmlDeviceGetHandleByIndex(gpu_id)
meminfo = pynvml.nvmlDeviceGetMemoryInfo(handle)
gpuratio_tmp = pynvml.nvmlDeviceGetUtilizationRates(handle)
gpuratio = str(gpuratio_tmp.gpu) + " %"
self.pro_gpu.append(gpuratio)
except:
pass
def IoMonitor(self):
self.pro_io = self.pro.io_counters()
def GPUCount(self):
return self.deviceCount
def LastWork(self):
list_return = []
self.Memonitor()
self.CPUMonitor()
self.GPUMonitor()
self.IoMonitor()
list_return.append(self.pro_rss)
list_return.append(self.pro_vss)
list_return.append(self.pro_cpu)
list_return.append(self.pro_gpu)
return list_return
class CsvWrite:
def __init__(self,csvname):
self.f_out = open(csvname+".csv",'ab+')
self.csv_write = csv.writer(self.f_out,dialect="excel")
def CSVDataWrite(self,inlist):
self.csv_write.writerow(inlist)
def ClsoeCSV(self):
self.f_out.close()
class TimeFuc:
def __init__(self):
pass
def LocalTime(self):
return time.strftime("%Y-%m-%d %H:%M:%S",time.localtime())
a = MonitorProcess(11718)
while 1:
print(a.LastWork())
运行top指令，查看你关注的程序所占用的进程号:
$ top
修改caclute_memory_occupied.py中pid号，如下:
a = MonitorProcess(11718)
运行即可:
python caclute_memory_occupied.py
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