Octave vs Python

"Don't do loops in Octave." is a well known truth. But sometimes loops are just too handy  or cannot be avoided at all. I was curious whether there is a difference in execution time of loops in Python and Octave since both are interpreted languages.

tic;
for i=1:100
for j=1:100
for k=1:100
  vain1 = i^2+j^2+k^2;
  vain2 = i^2+j^2+k^2;
  ...
  vain10 = i^2+j^2+k^2;
endfor
endfor
endfor
t = toc;
disp(num2str(t));

The following two scripts do nothing, but executing 3 nested loops with 100 iterations each and doing some useless computation within the loops. One script is in Python and one is in Octave. The Octave script is also listed above. Octave version 3.6.4 and Python version 2.7.3 was used for the comparison. The results are devastating.

user@machine:~/scripts/python_vs_octave$ octave loops.m
...
39.48
...
user@machine:~/scripts/python_vs_octave$ python loops.py
3.10390710831

Even in this simple example, the Octave script takes more than 10 times as long as the equivalent Python script. The difference becomes even bigger, if the amount of computation inside the loops is increased. Since Python also comes with sophisticated matrix processing capabilities (NumPy, SciPy) and if severe performance degradation for more sophisticated numerical analysis is not acceptable, the proverb above can be simply shortened to "Don't do Octave."


PS.: Another popular data analysis software is R. On the same machine using R version 2.14.1, the execution time of the equivalent script was 18.35s, which is in between the execution time of the Python and Octave scripts.