资源监控 ---使用python脚本
#!/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 10 16:59:42 2022
@author: sxj
"""
import psutil # 获取用户登录、开机信息
import platform
import getpass
import datetime
import time
from pynvml import *
# pip install nvidia-ml-py
def physical_system_time():
"""
获取系统启用时间,开机时间
"""
return {"system_time": datetime.datetime.fromtimestamp(psutil.boot_time()).strftime("%Y-%m-%d %H:%M:%S")}
def physical_username():
"""
获取当前用户名
"""
return {
"system_user": getpass.getuser()
}
def physical_platfrom_system():
"""
获取当前机器系统
"""
u_name = platform.uname()
return {"system_name": u_name.system, "system_version": u_name.version}
def physical_cpu():
"""
获取机器物理CPU个数
"""
return {"system_cpu_count": psutil.cpu_count(logical=False)}
def physical_memory():
"""
获取机器物理内存(返回字节bytes)
"""
# return round(psutil.virtual_memory().total / (1024.0 * 1024.0 * 1024.0), 2)
return {"system_memory": round(psutil.virtual_memory().total, 2)}
def physical_hard_disk():
"""
获取机器硬盘信息(字节bytes)
"""
result = []
for disk_partition in psutil.disk_partitions():
o_usage = psutil.disk_usage(disk_partition.device)
result.append(
{
"device": disk_partition.device,
"fstype":disk_partition.fstype,
"opts": disk_partition.opts,
"total": o_usage.total,
}
)
return {"system_hard_disk": result}
def nvidia_info():
"""
GPU内存 最大使用率
"""
nvidia_dict = {
"state": True,
"nvidia_version": "",
"nvidia_count": 0,
"gpus": []
}
try:
nvmlInit()
nvidia_dict["nvidia_version"] = nvmlSystemGetDriverVersion().decode('utf-8')
nvidia_dict["nvidia_count"] = nvmlDeviceGetCount()
for i in range(nvidia_dict["nvidia_count"]):
handle = nvmlDeviceGetHandleByIndex(i)
memory_info = nvmlDeviceGetMemoryInfo(handle)
gpu = {
"gpu_name": nvmlDeviceGetName(handle).decode('utf-8'),
"total": memory_info.total,
"free": memory_info.free,
"used": memory_info.used,
"temperature": f"{nvmlDeviceGetTemperature(handle, 0)}℃",
"powerStatus": nvmlDeviceGetPowerState(handle)
}
nvidia_dict['gpus'].append(gpu)
except NVMLError as _:
nvidia_dict["state"] = False
except Exception as _:
nvidia_dict["state"] = False
finally:
try:
nvmlShutdown()
except:
pass
return nvidia_dict
def merge_list2dict(info_list):
data = {}
for item in info_list:
data.update(
item()
)
return data
def computer_info():
data = merge(
[
physical_system_time,
physical_username,
physical_platfrom_system,
physical_cpu,
physical_memory,
physical_hard_disk,
nvidia_info
]
)
print(data)
# 获取总cpu使用率
# interval指定的是计算cpu使用率的时间间隔,percpu则指定是选择总的使用率还是每个cpu的使用率
cpu_percent = str(psutil.cpu_percent(interval=1, percpu=False)) + '%'
print(cpu_percent)
# 获取剩余内存
memory_free = str(round(psutil.virtual_memory().free / (1024.0 * 1024.0 * 1024.0), 3)) + ' G'
print(memory_free)
# 获取物理内存使用率
memory_percent = str(round(int(psutil.virtual_memory().total - psutil.virtual_memory().free) / float(psutil.virtual_memory().total) * 100, 3)) + '%'
print(memory_percent)
print(psutil.virtual_memory())
print(psutil.net_io_counters())
# svmem(total=13195796480, available=10661654528, percent=19.2, used=2206502912, free=9784602624, active=351813632, inactive=2690920448, buffers=130834432, cached=1073856512, shared=69632, slab=230887424)
# snetio(bytes_sent=94635815, bytes_recv=198511001, packets_sent=223459, packets_recv=289173, errin=0, errout=0, dropin=0, dropout=0)
# 获取硬盘
for i in psutil.disk_partitions():
o = psutil.disk_usage(i.device)
print("盘的名称:", i.device)
print("fs类型:", i.fstype)
print("fs权限:", i.opts)
print(f"全部:{o.total}, 已用:{o.used}, 可用:{o.free}")
if __name__ == '__main_':
print(computer_info())