Total memory used by Python process?

Question

Is there a way for a Python program to determine how much memory it's currently using? I've seen discussions about memory usage for a single object, but what I need is total memory usage for the process, so that I can determine when it's necessary to start discarding cached data.

Answer 1

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

Answer 2

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.

Answer 3

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

Answer 4

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.

Answer 5

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())

Answer 6

Here is a useful solution that works for various operating systems, including Linux, Windows 7, etc.:

import os
import psutil
process = psutil.Process(os.getpid())
print(process.memory_info().rss)  # in bytes 

On my current Python 2.7 install, the last line should be

print(process.get_memory_info()[0])

instead (there was a change in the API).

Note: do pip install psutil if it is not installed yet.