Quick script for benchmarking memory usage and behavior across versions/implementations of Python

memtest.py

# encoding: utf-8

"""
This is a test script that creates a large object in memory several times and
tracks memory usage before and after to see how much python returns to system.
"""

import pickle
#import memory_profiler

# Ensure compatibility between 2.6 and 3.3
try:
    xrange
except NameError:
    xrange = range
    raw_input = input

class TestObj(object):
    pass

text = "Super awesome test text! "

#@profile
def test_func():
    print("testing strs")
    #test_obj = TestObj()
    test_obj = {}
    for i in xrange(1000000):
        #setattr(test_obj, str(i), text[i % len(text)])
        test_obj[i] = text[i % len(text)]
    raw_input("created str obj")
    pickleds = pickle.dumps(test_obj)
    raw_input("pickled str obj")
    del test_obj
    raw_input("deleted str obj")

    print("testing ints")
    #test_2 = TestObj()
    test_2 = {}
    for i in xrange(1000000):
        #setattr(test_2, str(i), i)
        test_2[i] = i
    raw_input("created int obj")
    pickledi = pickle.dumps(test_2)
    raw_input("pickled int obj")
    del test_2
    raw_input("deleted int obj")

    del pickleds, pickledi
    return None

print("Running...")
test_func()
raw_input("Ready to exit")

The raw_inputs pause execution so you can check memory usage at various stages in a tool like top