My newest project is a Python library for monitoring memory consumption of arbitrary process, and one of its most useful features is the line-by-line analysis of memory usage for Python code. I wrote a basic prototype six months ago after being surprised by the lack of related tools. I wanted to plot memory consumption of a couple of Python functions but did not find a python module to do the job. I came to the conclusion that there is no standard way to get the memory usage of the Python interpreter from within Python, so I resorted to reading for from /proc/$PID/statm. From there on I realized that one the fetching of memory is done, making a line-by-line report wouldn't be hard. Back to today. I've been using the line-by-line memory monitoring to diagnose poor memory management (hidden temporaries, unused allocation, etc.) for some time. It seems to work on two different computers, so full of confidence as I am, I'll write a blog post about it ...

$ easy_install -U memory_profiler # pip install -U memory_profiler

@profile
def my_func():
    a = [1] * (10 ** 6)
    b = [2] * (2 * 10 ** 7)
    del b
    return a

if __name__ == '__main__':
    my_func()

$ python -m memory_profiler example.py
Filename: example.py

Line #    Mem usage    Increment   Line Contents
================================================
     2                             @profile
     3      8.00 MB      0.00 MB   def my_func():
     4     15.00 MB      7.00 MB       a = [1] * (10 ** 6)
     5    168.00 MB    153.00 MB       b = [2] * (2 * 10 ** 7)
     6     15.00 MB   -153.00 MB       del b
     7     15.00 MB      0.00 MB       return a