如何在Python中获得当前的CPU和RAM使用率？_Python_System_Cpu_Status_Ram

如何在Python中获得当前的CPU和RAM使用率？

python

如何在Python中获得当前的CPU和RAM使用率？,python,system,cpu,status,ram,Python,System,Cpu,Status,Ram,用Python获取当前系统状态（当前CPU、RAM、可用磁盘空间等）的首选方法是什么？*nix和Windows平台的奖励积分似乎有几种可能的方法可以从我的搜索中提取：使用一个库，例如（目前似乎没有积极开发，在多个平台上不受支持）或类似的库（自2007年以来似乎没有任何活动，也不支持Windows）使用特定于平台的代码，例如在*nix系统中使用os.popen（“ps”）或类似代码，在Windows平台的ctypes.windell.kernel32中使用MEMORYSTATUS（请参阅）。

用Python获取当前系统状态（当前CPU、RAM、可用磁盘空间等）的首选方法是什么？*nix和Windows平台的奖励积分

似乎有几种可能的方法可以从我的搜索中提取：

使用一个库，例如（目前似乎没有积极开发，在多个平台上不受支持）或类似的库（自2007年以来似乎没有任何活动，也不支持Windows）

使用特定于平台的代码，例如在*nix系统中使用

os.popen（“ps”）

或类似代码，在Windows平台的

ctypes.windell.kernel32

中使用

MEMORYSTATUS

（请参阅）。可以将Python类与所有这些代码片段放在一起

这并不是说这些方法不好，而是说已经有一种支持良好的多平台方法来做同样的事情了吗？

我不相信有一种支持良好的多平台库可用。请记住，Python本身是用C语言编写的，所以任何库都只需做出一个明智的决定，即运行哪个操作系统特定的代码段，正如您上面所建议的那样

“…当前系统状态（当前CPU、RAM、可用磁盘空间等）”和“*nix和Windows平台”可能是难以实现的组合

操作系统在管理这些资源的方式上有根本的不同。事实上，它们在核心概念上有所不同，比如定义什么是系统，什么是应用程序时间

“可用磁盘空间”？什么算“磁盘空间？”所有设备的所有分区？多引导环境中的外部分区如何

我不认为Windows和*nix之间有足够明确的共识可以实现这一点。事实上，被称为Windows的各种操作系统之间甚至可能没有任何共识。是否有一个既适用于XP又适用于Vista的Windows API？

这是我不久前整理的东西，它仅适用于Windows，但可能会帮助您完成部分需要完成的工作

源自： “对于系统可用内存”

“单个进程信息和python脚本示例”

注意：WMI接口/进程也可用于执行类似任务我在这里不使用它，因为当前的方法满足了我的需要，但是如果有一天需要扩展或改进它，那么可能需要研究可用的WMI工具

python的WMI：

守则：

'''
Monitor window processes

derived from:
>for sys available mem
http://msdn2.microsoft.com/en-us/library/aa455130.aspx

> individual process information and python script examples
http://www.microsoft.com/technet/scriptcenter/scripts/default.mspx?mfr=true

NOTE: the WMI interface/process is also available for performing similar tasks
        I'm not using it here because the current method covers my needs, but if someday it's needed
        to extend or improve this module, then may want to investigate the WMI tools available.
        WMI for python:
        http://tgolden.sc.sabren.com/python/wmi.html
'''

__revision__ = 3

import win32com.client
from ctypes import *
from ctypes.wintypes import *
import pythoncom
import pywintypes
import datetime


class MEMORYSTATUS(Structure):
    _fields_ = [
                ('dwLength', DWORD),
                ('dwMemoryLoad', DWORD),
                ('dwTotalPhys', DWORD),
                ('dwAvailPhys', DWORD),
                ('dwTotalPageFile', DWORD),
                ('dwAvailPageFile', DWORD),
                ('dwTotalVirtual', DWORD),
                ('dwAvailVirtual', DWORD),
                ]


def winmem():
    x = MEMORYSTATUS() # create the structure
    windll.kernel32.GlobalMemoryStatus(byref(x)) # from cytypes.wintypes
    return x    


class process_stats:
    '''process_stats is able to provide counters of (all?) the items available in perfmon.
    Refer to the self.supported_types keys for the currently supported 'Performance Objects'

    To add logging support for other data you can derive the necessary data from perfmon:
    ---------
    perfmon can be run from windows 'run' menu by entering 'perfmon' and enter.
    Clicking on the '+' will open the 'add counters' menu,
    From the 'Add Counters' dialog, the 'Performance object' is the self.support_types key.
    --> Where spaces are removed and symbols are entered as text (Ex. # == Number, % == Percent)
    For the items you wish to log add the proper attribute name in the list in the self.supported_types dictionary,
    keyed by the 'Performance Object' name as mentioned above.
    ---------

    NOTE: The 'NETFramework_NETCLRMemory' key does not seem to log dotnet 2.0 properly.

    Initially the python implementation was derived from:
    http://www.microsoft.com/technet/scriptcenter/scripts/default.mspx?mfr=true
    '''
    def __init__(self,process_name_list=[],perf_object_list=[],filter_list=[]):
        '''process_names_list == the list of all processes to log (if empty log all)
        perf_object_list == list of process counters to log
        filter_list == list of text to filter
        print_results == boolean, output to stdout
        '''
        pythoncom.CoInitialize() # Needed when run by the same process in a thread

        self.process_name_list = process_name_list
        self.perf_object_list = perf_object_list
        self.filter_list = filter_list

        self.win32_perf_base = 'Win32_PerfFormattedData_'

        # Define new datatypes here!
        self.supported_types = {
                                    'NETFramework_NETCLRMemory':    [
                                                                        'Name',
                                                                        'NumberTotalCommittedBytes',
                                                                        'NumberTotalReservedBytes',
                                                                        'NumberInducedGC',    
                                                                        'NumberGen0Collections',
                                                                        'NumberGen1Collections',
                                                                        'NumberGen2Collections',
                                                                        'PromotedMemoryFromGen0',
                                                                        'PromotedMemoryFromGen1',
                                                                        'PercentTimeInGC',
                                                                        'LargeObjectHeapSize'
                                                                     ],

                                    'PerfProc_Process':              [
                                                                          'Name',
                                                                          'PrivateBytes',
                                                                          'ElapsedTime',
                                                                          'IDProcess',# pid
                                                                          'Caption',
                                                                          'CreatingProcessID',
                                                                          'Description',
                                                                          'IODataBytesPersec',
                                                                          'IODataOperationsPersec',
                                                                          'IOOtherBytesPersec',
                                                                          'IOOtherOperationsPersec',
                                                                          'IOReadBytesPersec',
                                                                          'IOReadOperationsPersec',
                                                                          'IOWriteBytesPersec',
                                                                          'IOWriteOperationsPersec'     
                                                                      ]
                                }

    def get_pid_stats(self, pid):
        this_proc_dict = {}

        pythoncom.CoInitialize() # Needed when run by the same process in a thread
        if not self.perf_object_list:
            perf_object_list = self.supported_types.keys()

        for counter_type in perf_object_list:
            strComputer = "."
            objWMIService = win32com.client.Dispatch("WbemScripting.SWbemLocator")
            objSWbemServices = objWMIService.ConnectServer(strComputer,"root\cimv2")

            query_str = '''Select * from %s%s''' % (self.win32_perf_base,counter_type)
            colItems = objSWbemServices.ExecQuery(query_str) # "Select * from Win32_PerfFormattedData_PerfProc_Process")# changed from Win32_Thread        

            if len(colItems) > 0:        
                for objItem in colItems:
                    if hasattr(objItem, 'IDProcess') and pid == objItem.IDProcess:

                            for attribute in self.supported_types[counter_type]:
                                eval_str = 'objItem.%s' % (attribute)
                                this_proc_dict[attribute] = eval(eval_str)

                            this_proc_dict['TimeStamp'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.') + str(datetime.datetime.now().microsecond)[:3]
                            break

        return this_proc_dict      


    def get_stats(self):
        '''
        Show process stats for all processes in given list, if none given return all processes   
        If filter list is defined return only the items that match or contained in the list
        Returns a list of result dictionaries
        '''    
        pythoncom.CoInitialize() # Needed when run by the same process in a thread
        proc_results_list = []
        if not self.perf_object_list:
            perf_object_list = self.supported_types.keys()

        for counter_type in perf_object_list:
            strComputer = "."
            objWMIService = win32com.client.Dispatch("WbemScripting.SWbemLocator")
            objSWbemServices = objWMIService.ConnectServer(strComputer,"root\cimv2")

            query_str = '''Select * from %s%s''' % (self.win32_perf_base,counter_type)
            colItems = objSWbemServices.ExecQuery(query_str) # "Select * from Win32_PerfFormattedData_PerfProc_Process")# changed from Win32_Thread

            try:  
                if len(colItems) > 0:
                    for objItem in colItems:
                        found_flag = False
                        this_proc_dict = {}

                        if not self.process_name_list:
                            found_flag = True
                        else:
                            # Check if process name is in the process name list, allow print if it is
                            for proc_name in self.process_name_list:
                                obj_name = objItem.Name
                                if proc_name.lower() in obj_name.lower(): # will log if contains name
                                    found_flag = True
                                    break

                        if found_flag:
                            for attribute in self.supported_types[counter_type]:
                                eval_str = 'objItem.%s' % (attribute)
                                this_proc_dict[attribute] = eval(eval_str)

                            this_proc_dict['TimeStamp'] = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.') + str(datetime.datetime.now().microsecond)[:3]
                            proc_results_list.append(this_proc_dict)

            except pywintypes.com_error, err_msg:
                # Ignore and continue (proc_mem_logger calls this function once per second)
                continue
        return proc_results_list     


def get_sys_stats():
    ''' Returns a dictionary of the system stats'''
    pythoncom.CoInitialize() # Needed when run by the same process in a thread
    x = winmem()

    sys_dict = { 
                    'dwAvailPhys': x.dwAvailPhys,
                    'dwAvailVirtual':x.dwAvailVirtual
                }
    return sys_dict


if __name__ == '__main__':
    # This area used for testing only
    sys_dict = get_sys_stats()

    stats_processor = process_stats(process_name_list=['process2watch'],perf_object_list=[],filter_list=[])
    proc_results = stats_processor.get_stats()

    for result_dict in proc_results:
        print result_dict

    import os
    this_pid = os.getpid()
    this_proc_results = stats_processor.get_pid_stats(this_pid)

    print 'this proc results:'
    print this_proc_results

提供各种平台上的CPU、RAM等信息：

psutil是一个模块，提供了一个接口，通过使用Python以可移植的方式检索有关运行进程和系统利用率（CPU、内存）的信息，实现了ps、top和Windows task manager等工具提供的许多功能

目前，它支持Linux、Windows、OSX、Sun Solaris、FreeBSD、OpenBSD和NetBSD这两种32位和64位体系结构，Python版本从2.6到3.5（Python 2.4和2.5的用户可以使用2.1.3版本）

一些例子：

#!/usr/bin/env python
import psutil
# gives a single float value
psutil.cpu_percent()
# gives an object with many fields
psutil.virtual_memory()
# you can convert that object to a dictionary 
dict(psutil.virtual_memory()._asdict())
# you can have the percentage of used RAM
psutil.virtual_memory().percent
79.2
# you can calculate percentage of available memory
psutil.virtual_memory().available * 100 / psutil.virtual_memory().total
20.8

以下是提供更多概念和兴趣概念的其他文档：

您可以将psutil或psmem与子流程一起使用示例代码

import subprocess
cmd =   subprocess.Popen(['sudo','./ps_mem'],stdout=subprocess.PIPE,stderr=subprocess.PIPE) 
out,error = cmd.communicate() 
memory = out.splitlines()

参考文献

使用。在Ubuntu 18.04上，pip从2019年1月30日起安装了5.5.0（最新版本）。旧版本的行为可能有所不同。通过在Python中执行以下操作，可以检查psutil的版本：

from __future__ import print_function  # for Python2
import psutil
print(psutil.__versi‌on__)

要获取一些内存和CPU统计信息，请执行以下操作：

from __future__ import print_function
import psutil
print(psutil.cpu_percent())
print(psutil.virtual_memory())  # physical memory usage
print('memory % used:', psutil.virtual_memory()[2])

虚拟内存（元组）将具有系统范围内使用的内存百分比。在Ubuntu 18.04上，我似乎高估了几个百分点
您还可以获取当前Python实例使用的内存：
import os
import psutil
pid = os.getpid()
py = psutil.Process(pid)
memoryUse = py.memory_info()[0]/2.**30  # memory use in GB...I think
print('memory use:', memoryUse)

这将给出Python脚本的当前内存使用情况
下面的代码中有一些更深入的示例，没有外部库。我在Python 2.7.9上进行了测试
CPU使用率
import os

    CPU_Pct=str(round(float(os.popen('''grep 'cpu ' /proc/stat | awk '{usage=($2+$4)*100/($2+$4+$5)} END {print usage }' ''').readline()),2))

    #print results
    print("CPU Usage = " + CPU_Pct)

import os
mem=str(os.popen('free -t -m').readlines())
"""
Get a whole line of memory output, it will be something like below
['             total       used       free     shared    buffers     cached\n', 
'Mem:           925        591        334         14         30        355\n', 
'-/+ buffers/cache:        205        719\n', 
'Swap:           99          0         99\n', 
'Total:        1025        591        434\n']
 So, we need total memory, usage and free memory.
 We should find the index of capital T which is unique at this string
"""
T_ind=mem.index('T')
"""
Than, we can recreate the string with this information. After T we have,
"Total:        " which has 14 characters, so we can start from index of T +14
and last 4 characters are also not necessary.
We can create a new sub-string using this information
"""
mem_G=mem[T_ind+14:-4]
"""
The result will be like
1025        603        422
we need to find first index of the first space, and we can start our substring
from from 0 to this index number, this will give us the string of total memory
"""
S1_ind=mem_G.index(' ')
mem_T=mem_G[0:S1_ind]
"""
Similarly we will create a new sub-string, which will start at the second value. 
The resulting string will be like
603        422
Again, we should find the index of first space and than the 
take the Used Memory and Free memory.
"""
mem_G1=mem_G[S1_ind+8:]
S2_ind=mem_G1.index(' ')
mem_U=mem_G1[0:S2_ind]

mem_F=mem_G1[S2_ind+8:]
print 'Summary = ' + mem_G
print 'Total Memory = ' + mem_T +' MB'
print 'Used Memory = ' + mem_U +' MB'
print 'Free Memory = ' + mem_F +' MB'

import os

linux_filepath = "/proc/meminfo"
meminfo = dict(
    (i.split()[0].rstrip(":"), int(i.split()[1]))
    for i in open(linux_filepath).readlines()
)
meminfo["memory_total_gb"] = meminfo["MemTotal"] / (2 ** 20)
meminfo["memory_free_gb"] = meminfo["MemFree"] / (2 ** 20)
meminfo["memory_available_gb"] = meminfo["MemAvailable"] / (2 ** 20)

和Ram使用，总计、使用和免费
import os

    CPU_Pct=str(round(float(os.popen('''grep 'cpu ' /proc/stat | awk '{usage=($2+$4)*100/($2+$4+$5)} END {print usage }' ''').readline()),2))

    #print results
    print("CPU Usage = " + CPU_Pct)

import os
mem=str(os.popen('free -t -m').readlines())
"""
Get a whole line of memory output, it will be something like below
['             total       used       free     shared    buffers     cached\n', 
'Mem:           925        591        334         14         30        355\n', 
'-/+ buffers/cache:        205        719\n', 
'Swap:           99          0         99\n', 
'Total:        1025        591        434\n']
 So, we need total memory, usage and free memory.
 We should find the index of capital T which is unique at this string
"""
T_ind=mem.index('T')
"""
Than, we can recreate the string with this information. After T we have,
"Total:        " which has 14 characters, so we can start from index of T +14
and last 4 characters are also not necessary.
We can create a new sub-string using this information
"""
mem_G=mem[T_ind+14:-4]
"""
The result will be like
1025        603        422
we need to find first index of the first space, and we can start our substring
from from 0 to this index number, this will give us the string of total memory
"""
S1_ind=mem_G.index(' ')
mem_T=mem_G[0:S1_ind]
"""
Similarly we will create a new sub-string, which will start at the second value. 
The resulting string will be like
603        422
Again, we should find the index of first space and than the 
take the Used Memory and Free memory.
"""
mem_G1=mem_G[S1_ind+8:]
S2_ind=mem_G1.index(' ')
mem_U=mem_G1[0:S2_ind]

mem_F=mem_G1[S2_ind+8:]
print 'Summary = ' + mem_G
print 'Total Memory = ' + mem_T +' MB'
print 'Used Memory = ' + mem_U +' MB'
print 'Free Memory = ' + mem_F +' MB'

import os

linux_filepath = "/proc/meminfo"
meminfo = dict(
    (i.split()[0].rstrip(":"), int(i.split()[1]))
    for i in open(linux_filepath).readlines()
)
meminfo["memory_total_gb"] = meminfo["MemTotal"] / (2 ** 20)
meminfo["memory_free_gb"] = meminfo["MemFree"] / (2 ** 20)
meminfo["memory_available_gb"] = meminfo["MemAvailable"] / (2 ** 20)

仅适用于Linux：
一个仅依赖于stdlib的RAM使用线性程序：
import os
tot_m, used_m, free_m = map(int, os.popen('free -t -m').readlines()[-1].split()[1:])

编辑：指定的解决方案操作系统依赖项
我觉得这些答案是为Python 2编写的，而且在任何情况下都没有人提到Python 3可用的标准包。它提供用于获取给定进程（默认情况下为调用Python进程）的资源限制的命令。这与从整体上获取系统当前的资源使用情况不同，但它可以解决一些相同的问题，例如“我想确保我在这个脚本中只使用X多个RAM。”我们选择使用常用的信息源，因为我们可以发现空闲内存中的瞬时波动，并且感觉查询meminfo数据源很有帮助。这也帮助我们获得了一些预先解析的相关参数
代码
import os

    CPU_Pct=str(round(float(os.popen('''grep 'cpu ' /proc/stat | awk '{usage=($2+$4)*100/($2+$4+$5)} END {print usage }' ''').readline()),2))

    #print results
    print("CPU Usage = " + CPU_Pct)

import os
mem=str(os.popen('free -t -m').readlines())
"""
Get a whole line of memory output, it will be something like below
['             total       used       free     shared    buffers     cached\n', 
'Mem:           925        591        334         14         30        355\n', 
'-/+ buffers/cache:        205        719\n', 
'Swap:           99          0         99\n', 
'Total:        1025        591        434\n']
 So, we need total memory, usage and free memory.
 We should find the index of capital T which is unique at this string
"""
T_ind=mem.index('T')
"""
Than, we can recreate the string with this information. After T we have,
"Total:        " which has 14 characters, so we can start from index of T +14
and last 4 characters are also not necessary.
We can create a new sub-string using this information
"""
mem_G=mem[T_ind+14:-4]
"""
The result will be like
1025        603        422
we need to find first index of the first space, and we can start our substring
from from 0 to this index number, this will give us the string of total memory
"""
S1_ind=mem_G.index(' ')
mem_T=mem_G[0:S1_ind]
"""
Similarly we will create a new sub-string, which will start at the second value. 
The resulting string will be like
603        422
Again, we should find the index of first space and than the 
take the Used Memory and Free memory.
"""
mem_G1=mem_G[S1_ind+8:]
S2_ind=mem_G1.index(' ')
mem_U=mem_G1[0:S2_ind]

mem_F=mem_G1[S2_ind+8:]
print 'Summary = ' + mem_G
print 'Total Memory = ' + mem_T +' MB'
print 'Used Memory = ' + mem_U +' MB'
print 'Free Memory = ' + mem_F +' MB'

import os

linux_filepath = "/proc/meminfo"
meminfo = dict(
    (i.split()[0].rstrip(":"), int(i.split()[1]))
    for i in open(linux_filepath).readlines()
)
meminfo["memory_total_gb"] = meminfo["MemTotal"] / (2 ** 20)
meminfo["memory_free_gb"] = meminfo["MemFree"] / (2 ** 20)
meminfo["memory_available_gb"] = meminfo["MemAvailable"] / (2 ** 20)

输出以供参考（为了进一步分析，我们去掉了所有换行符）
MemTotal:1014500 kB MemFree:562680 kB MemAvailable:646364 kB
缓冲区：15144 kB缓存：210720 kB交换缓存：0 kB活动：261476 kB
非活动：128888 kB活动（anon）：167092 kB非活动（anon）：20888 kB
活动（文件）：94384 kB非活动（文件）：108000 kB不可编辑：3652 kB
M锁定：3652 kB交换总计：0 kB交换自由：0 kB脏：0 kB写回：
0 kB anonpage:168160 kB映射：81352 kB Shmem:21060 kB Slab:34492
可申请知识库：18044KB SunRecreal:16448KB内核堆栈：2672KB
页表：8180 kB NFS\u不稳定：0 kB跳出：0 kB写回TMP:0 kB
提交限制：507248 kB提交内容：1038756 kB VmallocTotal:
34359738367 kB VMAlloccused:0 kB VmallocChunk:0 kB硬件已损坏：
0 kB无注释页：88064 kB总：0 kB免费：0 kB
HugePages\u总计：0 HugePages\u免费：0 HugePages\u Rsvd:0 HugePages\u剩余：
0 Hugepagesize:2048 kB DirectMap4k:43008 kB DirectMap2M:1005568 kB
这个sc
$ python -m memory_profiler main.py

Filename: main.py

Line #    Mem usage    Increment   Line Contents
================================================
    35  125.992 MiB  125.992 MiB   @profile
    36                             def linearRegressionfit(Xt,Yt,Xts,Yts):
    37  125.992 MiB    0.000 MiB       lr=LinearRegression()
    38  130.547 MiB    4.555 MiB       model=lr.fit(Xt,Yt)
    39  130.547 MiB    0.000 MiB       predict=lr.predict(Xts)
    40                             
    41  130.547 MiB    0.000 MiB       print("train Accuracy",lr.score(Xt,Yt))
    42  130.547 MiB    0.000 MiB       print("test Accuracy",lr.score(Xts,Yts))

$ mprof run main.py
$ mprof plot

            #!/usr/bin/env python
            #Execute commond on windows machine to install psutil>>>>python -m pip install psutil
            import psutil

            print ('                                                                   ')
            print ('----------------------CPU Information summary----------------------')
            print ('                                                                   ')

            # gives a single float value
            vcc=psutil.cpu_count()
            print ('Total number of CPUs :',vcc)

            vcpu=psutil.cpu_percent()
            print ('Total CPUs utilized percentage :',vcpu,'%')

            print ('                                                                   ')
            print ('----------------------RAM Information summary----------------------')
            print ('                                                                   ')
            # you can convert that object to a dictionary 
            #print(dict(psutil.virtual_memory()._asdict()))
            # gives an object with many fields
            vvm=psutil.virtual_memory()

            x=dict(psutil.virtual_memory()._asdict())

            def forloop():
                for i in x:
                    print (i,"--",x[i]/1024/1024/1024)#Output will be printed in GBs

            forloop()
            print ('                                                                   ')
            print ('----------------------RAM Utilization summary----------------------')
            print ('                                                                   ')
            # you can have the percentage of used RAM
            print('Percentage of used RAM :',psutil.virtual_memory().percent,'%')
            #79.2
            # you can calculate percentage of available memory
            print('Percentage of available RAM :',psutil.virtual_memory().available * 100 / psutil.virtual_memory().total,'%')
            #20.8

file1 = open('/proc/meminfo', 'r') 

for line in file1: 
    if 'MemTotal' in line: 
        x = line.split()
        memTotal = int(x[1])
        
    if 'Buffers' in line: 
        x = line.split()
        buffers = int(x[1])
        
    if 'Cached' in line and 'SwapCached' not in line: 
        x = line.split()
        cached = int(x[1])
    
    if 'MemFree' in line: 
        x = line.split()
        memFree = int(x[1])

file1.close()

percentage_used = int ( ( memTotal - (buffers + cached + memFree) ) / memTotal * 100 )
print(percentage_used)

import os
import psutil  # need: pip install psutil

In [32]: psutil.virtual_memory()
Out[32]: svmem(total=6247907328, available=2502328320, percent=59.9, used=3327135744, free=167067648, active=3671199744, inactive=1662668800,     buffers=844783616, cached=1908920320, shared=123912192, slab=613048320)

In [33]: psutil.virtual_memory().percent
Out[33]: 60.0

In [34]: psutil.cpu_percent()
Out[34]: 5.5

In [35]: os.sep
Out[35]: '/'

In [36]: psutil.disk_usage(os.sep)
Out[36]: sdiskusage(total=50190790656, used=41343860736, free=6467502080, percent=86.5)

In [37]: psutil.disk_usage(os.sep).percent
Out[37]: 86.5