Memory Control - Can you get the memory usage of the interpreter?

[Jean Brouwers]

Here is a slighly better version which avoids breaking the pseudo file
up into lines and parsing all lines.  But still Linux only.

/Jean Brouwers
 PropICy Semiconductor, Inc.

<pre>

import os

_proc_status = '/proc/%d/status' % os.getpid()  # Linux only?

_scale = {'kB': 1024.0, 'mB': 1024.0*1024.0,
          'KB': 1024.0, 'MB': 1024.0*1024.0}

def _VmB(VmKey):
    '''Private.
    '''
    global _proc_status, _scale
     # get pseudo file  /proc/<pid>/status
    try:
        t = open(_proc_status)
        v = t.read()
        t.close()
    except:
        return 0.0  # non-Linux?
     # get VmKey line e.g. 'VmRSS:  9999  kB\n ...'
    t = v.index(VmKey)
    v = v[t:].split(None, 3)  # whitespace
    if len(v) < 3:
        return 0.0  # invalid format?
     # convert Vm value to bytes
    return float(v[1]) * _scale[v[2]]
 
def memory(since=0.0):
    '''Return memory usage in bytes.
    '''
    return _VmB('VmSize:') - since
 
def resident(since=0.0):
    '''Return resident memory usage in bytes.
    '''
    return _VmB('VmRSS:') - since
 
def stacksize(since=0.0):
    '''Return stack size in bytes.
    '''
    return _VmB('VmStk:') - since

</pre>


In article <090720041815251751%JBrouwersAtProphICyDotCom at no.spam.net>,
Jean Brouwers <JBrouwersAtProphICyDotCom at no.spam.net> wrote:

> Assuming you are using Linux, below is an example for the memory usage
> and stack size of the current process.  See the man page for proc for
> more details.
> 
> /Jean Brouwers
>  ProphICy Semiconductor, Inc.
> 
> <pre>
> 
> import os
> 
> _proc_status = '/proc/%d/status' % os.getpid()  # Linux only?
> _scale = {'kB': 1024.0, 'mB': 1024.0*1024.0,
>            'KB': 1024.0, 'MB': 1024.0*1024.0}
> 
> def _VmB(VmKey):
>     global _scale
>     try: # get the /proc/<pid>/status pseudo file
>         t = open(_proc_status)
>         v = [v for v in t.readlines() if v.startswith(VmKey)]
>         t.close()
>          # convert Vm value to bytes
>         if len(v) == 1:
>            t = v[0].split()  # e.g. 'VmRSS:  9999  kB'
>            if len(t) == 3:  ## and t[0] == VmKey:
>                return float(t[1]) * _scale.get(t[2], 0.0)
>     except:
>         pass
>     return 0.0
>  
> def memory(since=0.0):
>     '''Return process memory usage in bytes.
>     '''
>     return _VmB('VmSize:') - since
>  
> def stacksize(since=0.0):
>     '''Return process stack size in bytes.
>     '''
>     return _VmB('VmStk:') - since
> 
> </pre>
> 
> 
> In article <40ef2dc0$0$546$ed2619ec at ptn-nntp-reader02.plus.net>, Ian
> <info at fretfarm.co.uk> wrote:
> 
> > Hi all,
> > 
> > I have a problem. I have an application which needs to work with a lot of
> > data, but not all at the same time. It is arranged as a set of objects, each
> > with lots of data that is created when the object is instantiated.
> > 
> > I'd ideally like to keep as many objects as possible in memory, but I can
> > get rid of any object the program isn't currently using.
> > 
> > Is there any way I can access the amount of memory python is using? I can
> > then decide when to give up objects to the gc.
> > 
> > I don't want to use weakref because the gc simply collects weakref'ed stuff
> > whether memory is tight or not, and then I have to recreate it (which is
> > costly). I only have one internal consumer for the data, and it is only
> > working with one object at once, but may change to a different object at any
> > time.
> > 
> > Thanks in advance
> > 
> > Ian.
> > 
> >