Which Python memory profiler is recommended?


I want to know the memory usage of my Python application and specifically want to know what code blocks/portions or objects are consuming most memory. Google search shows a commercial one is Python Memory Validator (Windows only).

And open source ones are PySizer and Heapy.

I haven't tried anyone, so I wanted to know which one is the best considering:

  1. Gives most details.

  2. I have to do least or no changes to my code.

4/8/2017 6:50:23 PM

Accepted Answer

Heapy is quite simple to use. At some point in your code, you have to write the following:

from guppy import hpy
h = hpy()
print h.heap()

This gives you some output like this:

Partition of a set of 132527 objects. Total size = 8301532 bytes.
Index  Count   %     Size   % Cumulative  % Kind (class / dict of class)
0  35144  27  2140412  26   2140412  26 str
1  38397  29  1309020  16   3449432  42 tuple
2    530   0   739856   9   4189288  50 dict (no owner)

You can also find out from where objects are referenced and get statistics about that, but somehow the docs on that are a bit sparse.

There is a graphical browser as well, written in Tk.

3/22/2013 7:51:07 PM

Since nobody has mentioned it I'll point to my module memory_profiler which is capable of printing line-by-line report of memory usage and works on Unix and Windows (needs psutil on this last one). Output is not very detailed but the goal is to give you an overview of where the code is consuming more memory and not a exhaustive analysis on allocated objects.

After decorating your function with @profile and running your code with the -m memory_profiler flag it will print a line-by-line report like this:

Line #    Mem usage  Increment   Line Contents
     3                           @profile
     4      5.97 MB    0.00 MB   def my_func():
     5     13.61 MB    7.64 MB       a = [1] * (10 ** 6)
     6    166.20 MB  152.59 MB       b = [2] * (2 * 10 ** 7)
     7     13.61 MB -152.59 MB       del b
     8     13.61 MB    0.00 MB       return a

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