Doctests Benchmarking
Docbench is a framework based on doctest to benchmark Python code.
If you already are familiar with doctest,
you should be able to use docbench in minutes.
We will walk you through the use of docbench with a simple use case:
a module that computes prime numbers.
Create a primes.py
file and define the primes
function:
def primes(n):
p = []
for i in range(2, n+1):
for j in range(2, i):
if (i % j == 0):
break
else:
p.append(i)
return p
The function returns an ordered list of primes numbers up to the number n
.
Its implementation is simple but the execution takes a lot of time when n
grows.
The following sieve
function should return the same result, but performs less
computations and therefore should be faster.
def sieve(n):
p = []
for i in range(2, n+1):
prime = True
for j in p:
if j * j > i:
break
if (i % j == 0):
prime = False
break
if prime:
p.append(i)
return p
If you already know doctest, you may skip this section.
Testing this module with doctest is pretty straightforward: create a test.py
file with a function test_primes
with no implementation but a doctest
for the primes
function:
def test_primes():
"""
>>> from primes import primes
>>> n = 50
>>> primes(n)
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47]
"""
You are pretty confident that if test_primes
doctest works as advertised
in this doctest, the primes
function behaves correctly.
Therefore, you may now test sieve
against primes
:
def test_sieve():
"""
>>> from primes import primes, sieve
>>> n = 10000
>>> primes(n) == sieve(n)
True
"""
Finally, add the following boilerplate a the end of your file:
if __name__ == "__main__":
import doctest
doctest.testmod()
You are ready to execute this test suite with:
$ python test.py
No error displayed ? The primes
module has successfully passed all tests !
Create a new file name benchmark.py
. Add functions that act as docbench
holders for the function primes
and sieve
. We rely on the convention
that only the time spent in the last statement of any docbench will be
measured, the previous ones are considered setup code.
def benchmark_primes():
"""
>>> from primes import primes
>>> n = 10000
>>> primes(n)
"""
def benchmark_sieve():
"""
>>> from primes import sieve
>>> n = 10000
>>> sieve(n)
"""
Add the following boilerplate at the end of your file:
if __name__ == "__main__":
import docbench
docbench.benchmod()
Run your benchmark with:
$ python benchmark.py
You should end up with an output similar too:
Benchmark Time
------------------------- ----------------
__main__.benchmark_primes 1.03
__main__.benchmark_sieve 0.00876
Indeed, sieve
is quite faster than primes
!