Python Profiling

In this article you will learn how to profile a python program.

Profiling is a form of program analysis. It can help us answer questions such as:

  • how much memory is the program using?
  • how much time is spent on functions?
  • how much time is spent on statements?

profiling a python application

python profiling

cProfile is a profiler included with Python. The profiler gives the total running time, tells the function call frequency and much more data.

Take any program to measure, for example this simple program:

import math
print( math.factorial(1024) )
print( math.sin(1024) )

Instead of executing it the traditional way, run python like this:

python -m cProfile

You will see something like this:

3 function calls in 0.003 seconds
Ordered by: standard name
   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.001    0.001    0.003    0.003<module>)
        1    0.001    0.001    0.001    0.001 {math.factorial}
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}

To visualize the profiling data we can use these steps:

python -m cProfile -o out.profile
sudo easy_install SquareMap RunSnakeRun
runsnake out.profile

A window will show up:

A lot of time is spent in the factorial function, the sinus function hardly takes any time (the sinus function running time is the small block on the right). We can iterate over each function and show the running time as percentage.

visualize your code flow graph

The module pycallgraph can visualize your code run time.
Install it using:

sudo pip install pycallgraph

The software graphviz is required, you can get it from or use the command:

sudo apt-get install graphviz

After installing, run:

pycallgraph graphviz -- ./

and image called pycallgraph.png will be created. You can load it in a file explorer or type:

display pycallgraph.png

It will output a call graph with run times:

python call graph

python performance profiling, a call graph with execution time

python memory profiler

To visualize run time and memory usage, we can also use vprof.
Install with:

pip install vprof

To show the memory use (a browser will open):

vprof -s -c m

It shows a memory plot, with total memory use, lines of code and so on:

python memory profiler

Memory profiling with Python

To show the number of executions for each line of code:

vprof -s -c h

The window highlights each line of code with the number of calls, the more calls the darker the lines:


Number of executions of each line of code.

You can get a flame graph with the line:

vprof -s -c h

And combine all graphs using:

vprof -s -c cmh
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