A Concise Introduction to Programming in Python

Project: Program Performance

Exercises 14.5 and 14.6 describe two of the improvements that can be made

to the efficiency of Listing 14.1. Because they reduce the numb er of loop

executions, they must make the program faster, but by how much? Is the

improvement significant? Measuring program performance is one way to

analyze the impact of changes made to your code.

In Python, we can get reasonably accurate timings using this function from

the time module:

clock() Current processor time.

The standard way to use a clock is to surround the code you want to measure

with two calls to the clock, like this:

start = time.clock()

sieve(10000)

stop = time.clock()

elapsed ...