Bdtjtk

For Unix based systems (Linux, Mac OS X, Solaris), you can use the getrusage() function from the standard library module resource. The resulting object has the attribute ru_maxrss, which gives the peak memory usage for the calling process:

>>> resource.getrusage(resource.RUSAGE_SELF).ru_maxrss

2656  # peak memory usage (kilobytes on Linux, bytes on OS X)

The Python docs don't make note of the units. Refer to your specific system's man getrusage.2 page to check the unit for the value. On Ubuntu 18.04, the unit is noted as kilobytes. On Mac OS X, it's bytes.

The getrusage() function can also be given resource.RUSAGE_CHILDREN to get the usage for child processes, and (on some systems) resource.RUSAGE_BOTH for total (self and child) process usage.

If you care only about Linux, you can alternatively read the /proc/self/status or /proc/self/statm file as described in other answers for this question and this one too.

On Windows, you can use WMI (home page, cheeseshop):

def memory():

    import os

    from wmi import WMI

    w = WMI('.')

    result = w.query("SELECT WorkingSet FROM Win32_PerfRawData_PerfProc_Process WHERE IDProcess=%d" % os.getpid())

    return int(result[0].WorkingSet)

On Linux (from python cookbook http://code.activestate.com/recipes/286222/:

import os

_proc_status = '/proc/%d/status' % os.getpid()



_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  kBn ...'

    i = v.index(VmKey)

    v = v[i:].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

On unix, you can use the ps tool to monitor it:

$ ps u -p 1347 | awk '{sum=sum+$6}; END {print sum/1024}'

where 1347 is some process id. Also, the result is in MB.

Heapy (and friends) may be what you're looking for.

Also, caches typically have a fixed upper limit on their size to solve the sort of problem you're talking about. For instance, check out this LRU cache decorator.

I like it, thank you for @bayer. I get a specific process count tool, now.

# Megabyte.

$ ps aux | grep python | awk '{sum=sum+$6}; END {print sum/1024 " MB"}'

87.9492 MB



# Byte.

$ ps aux | grep python | awk '{sum=sum+$6}; END {print sum " KB"}'

90064 KB

Attach my process list.

$ ps aux  | grep python

root       943  0.0  0.1  53252  9524 ?        Ss   Aug19  52:01 /usr/bin/python /usr/local/bin/beaver -c /etc/beaver/beaver.conf -l /var/log/beaver.log -P /var/run/beaver.pid

root       950  0.6  0.4 299680 34220 ?        Sl   Aug19 568:52 /usr/bin/python /usr/local/bin/beaver -c /etc/beaver/beaver.conf -l /var/log/beaver.log -P /var/run/beaver.pid

root      3803  0.2  0.4 315692 36576 ?        S    12:43   0:54 /usr/bin/python /usr/local/bin/beaver -c /etc/beaver/beaver.conf -l /var/log/beaver.log -P /var/run/beaver.pid

jonny    23325  0.0  0.1  47460  9076 pts/0    S+   17:40   0:00 python

jonny    24651  0.0  0.0  13076   924 pts/4    S+   18:06   0:00 grep python

Reference

• memory - Linux: find out what process is using all the RAM? - Super User


• Total memory used by Python process? - Stack Overflow


• linux - ps aux output meaning - Super User

Below is my function decorator which allows to track how much memory this process consumed before the function call, how much memory it uses after the function call, and how long the function is executed.

import time

import os

import psutil





def elapsed_since(start):

    return time.strftime("%H:%M:%S", time.gmtime(time.time() - start))





def get_process_memory():

    process = psutil.Process(os.getpid())

    return process.get_memory_info().rss





def track(func):

    def wrapper(*args, **kwargs):

        mem_before = get_process_memory()

        start = time.time()

        result = func(*args, **kwargs)

        elapsed_time = elapsed_since(start)

        mem_after = get_process_memory()

        print("{}: memory before: {:,}, after: {:,}, consumed: {:,}; exec time: {}".format(

            func.__name__,

            mem_before, mem_after, mem_after - mem_before,

            elapsed_time))

        return result

    return wrapper

So, when you have some function decorated with it

from utils import track



@track

def list_create(n):

    print("inside list create")

    x = [1] * n

    return x

You will be able to see this output:

inside list create

list_create: memory before: 45,928,448, after: 46,211,072, consumed: 282,624; exec time: 00:00:00

import os, win32api, win32con, win32process

han = win32api.OpenProcess(win32con.PROCESS_QUERY_INFORMATION|win32con.PROCESS_VM_READ, 0, os.getpid())

process_memory = int(win32process.GetProcessMemoryInfo(han)['WorkingSetSize'])

Current memory usage of the current process on Linux, for Python 2, Python 3, and pypy, without any imports:

def getCurrentMemoryUsage():

    ''' Memory usage in kB '''



    with open('/proc/self/status') as f:

        memusage = f.read().split('VmRSS:')[1].split('n')[0][:-3]



    return int(memusage.strip())

Tested on Linux 4.4 and 4.9, but even an early Linux version should work.

Looking in man proc and searching for the info on the /proc/$PID/status file, it mentions minimum versions for some fields (like Linux 2.6.10 for "VmPTE"), but the "VmRSS" field (which I use here) has no such mention. Therefore I assume it has been in there since an early version.

Even easier to use than /proc/self/status: /proc/self/statm. It's just a space delimited list of several statistics. I haven't been able to tell if both files are always present.

/proc/[pid]/statm

Provides information about memory usage, measured in pages.
The columns are:

• size (1) total program size
  (same as VmSize in /proc/[pid]/status)


• resident (2) resident set size
  (same as VmRSS in /proc/[pid]/status)


• shared (3) number of resident shared pages (i.e., backed by a file)
  (same as RssFile+RssShmem in /proc/[pid]/status)


• text (4) text (code)


• lib (5) library (unused since Linux 2.6; always 0)


• data (6) data + stack


• dt (7) dirty pages (unused since Linux 2.6; always 0)

Here's a simple example:

from pathlib import Path

from resource import getpagesize



PAGESIZE = getpagesize()

PATH = Path('/proc/self/statm')





def get_resident_set_size() -> int:

    """Return the current resident set size in bytes."""

    # statm columns are: size resident shared text lib data dt

    statm = PATH.read_text()

    fields = statm.split()

    return int(fields[1]) * PAGESIZE





data = 

start_memory = get_resident_set_size()

for _ in range(10):

    data.append('X' * 100000)

    print(get_resident_set_size() - start_memory)

That produces a list that looks something like this:

0

0

368640

368640

368640

638976

638976

909312

909312

909312

You can see that it jumps by about 300,000 bytes after roughly 3 allocations of 100,000 bytes.

Using sh and os to get into python bayer's answer.

float(sh.awk(sh.ps('u','-p',os.getpid()),'{sum=sum+$6}; END {print sum/1024}'))

Answer is in megabytes.

For Python 3.6 and psutil 5.4.5 it is easier to use memory_percent() function listed here.

import os

import psutil

process = psutil.Process(os.getpid())

print(process.memory_percent())