timeit-compare 1.0.0

A method based on timeit that can help you to call timeit.timeit for several statements and provide comparison results.

timeit_compare

A method based on timeit that can help you to call timeit.timeit for several statements and provide comparison results.

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Installation

You can run the following command to install the package

pip install timeit_compare

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Usage

When using the timeit library, I am always more interested in comparing the efficiency of several different methods to solve a problem, rather than simply measuring the running time of a single statement. Here is a simple example.

from functools import reduce
from operator import add

n = 100


def sum1():
    s = 0
    i = 1
    while i <= n:
        s += i
        i += 1
    return s


def sum2():
    s = 0
    for i in range(1, n + 1):
        s += i
    return s


def sum3():
    return sum(range(1, n + 1))


def sum4():
    return reduce(add, range(1, n + 1))


def sum5():
    return (1 + n) * n // 2

The functions above are all used to sum numbers from 1 to 100, which one is the most efficient?
This problem can be easily solved by the following method:

from timeit import timeit

print(timeit(sum1))
print(timeit(sum2))
print(timeit(sum3))
print(timeit(sum4))
print(timeit(sum5))

and get the results like:

3.2710195999825373
2.050656799983699
0.4511557999649085
2.5759165000054054
0.066161299997475

Calling timeit multiple times and printing the results makes me feel troublesome, and the results seem to be not intuitive.

By using:

from timeit_compare import compare

compare(sum1, sum2, sum3, sum4, sum5)

you can easily get the results like:

The output provides detailed results, including the mean, median, minimum, maximum and standard deviation of each function's running time.

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Contact

If you have any suggestions, please contact me at [e-mail].

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