[0ren]

Some good points for comparison:

http://www.scipy.org/NumPy_for_Matlab_Users

IMHO, it's best to prototype in Octave and then build in python. I find that the Matlab/Octave syntax is too focused on linear algebra, so it's better for small prototypes (and for people coming from non-SW fields). For big projects, I prefer the 0-based arrays, more than one function per file, and all the rest of the python goodies. I estimate that 70% of my time is usually spend preparing the data (e.g. parsing xml, or some other files, etc), for which I find python more suitable.

In fact, I usually work with them side by side, testing ideas in Octave, then implementing these pieces into a large python project.

Edit: this has also been discussed here before, e.g.

http://news.ycombinator.com/item?id=363096

http://news.ycombinator.com/item?id=689183