5

My code allocates continously memory (~12kb per second). With a runtime of 8 hours its a lot of memory!!

Because of this I want to trace the moments/code lines my python code allocates memory.

Something like you can do with processed code lines with:

python -m trace --count -C ./tmp code.py

this generate a view where you can see how often this line was executed. It looks like:

code.cover 

1:     import sys
1:     import os
1534:  while 1:
1534:      print "foo"

I need this for memory allocation. if possible something like

1245 B    import sys
893 B     import os
17.46 KB  import somecode
asheeshr
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HappyHacking
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  • Did you try using valgrind ? In special, check the massif tool that comes with valgrind. – mmgp Jan 02 '13 at 15:23
  • possible duplicate of [Which Python memory profiler is recommended?](http://stackoverflow.com/questions/110259/which-python-memory-profiler-is-recommended) – BartoszKP Jan 12 '14 at 16:15

1 Answers1

3

Looks like this question has already been answered here: Python memory profiler

Maybe this one can help you: http://pypi.python.org/pypi/memory_profiler

From the docs, execute the code passing the option -m memory_profiler to the python interpreter to load the memory_profiler module and print to stdout the line-by-line analysis. If the file name was example.py, this would result in:

$ python -m memory_profiler example.py

Output will follow:

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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Fernando Macedo
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  • This is very helpfull, but i need a comparison of my memory usage, because there are many threaded loops. So that if i exit the code, i see that during the runtime this function allocated 25 MB memory – HappyHacking Jan 02 '13 at 16:01
  • Have you noticed the link to a similar question? There are far more tools there. – Fernando Macedo Jan 02 '13 at 16:27