Python includes a profiler called cProfile. It not only gives the total running time, but also times each function separately, and tells you how many times each function was called, making it easy to determine where you should make optimizations.

You can call it from within your code, or from the interpreter, like this:

import cProfile
cProfile.run('foo()')

Even more usefully, you can invoke the cProfile when running a script:

python -m cProfile myscript.py

To make it even easier, I made a little batch file called 'profile.bat':

python -m cProfile %1

So all I have to do is run:

profile euler048.py

And I get this:

1007 function calls in 0.061 CPU seconds

Ordered by: standard name
ncalls  tottime  percall  cumtime  percall filename:lineno(function)
    1    0.000    0.000    0.061    0.061 <string>:1(<module>)
 1000    0.051    0.000    0.051    0.000 euler048.py:2(<lambda>)
    1    0.005    0.005    0.061    0.061 euler048.py:2(<module>)
    1    0.000    0.000    0.061    0.061 {execfile}
    1    0.002    0.002    0.053    0.053 {map}
    1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler objects}
    1    0.000    0.000    0.000    0.000 {range}
    1    0.003    0.003    0.003    0.003 {sum}

EDIT: Updated link to a good video resource from PyCon 2013 titled Python Profiling
Also via YouTube.