timeit-compare 1.2.2

Based on the timeit library, timeit_compare can time multiple statements and provide comparison results.

timeit_compare

Based on the timeit library, timeit_compare can time multiple 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?
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.

You can also perform the following operations to obtain specific values:

from timeit_compare import Compare

cmp = Compare()
for func in sum1, sum2, sum3, sum4, sum5:
    cmp.add_timer(func)
cmp.run()
# cmp.print_results()

result = cmp.get_result(0)  # get the result of the timer with index 0
print(
    result.time, result.repeat, result.number,
    result.mean, result.median, result.min, result.max, result.std,
    result.error, sep='\n'
)
# [3.3324892420678126e-06, 3.175742677501652e-06, 3.2153616044376503e-06, 3.267199346172507e-06, 3.2638434747711383e-06]
# 5
# 24405
# 3.2509272689901518e-06
# 3.2638434747711383e-06
# 3.175742677501652e-06
# 3.3324892420678126e-06
# 5.916418598334957e-08
# None

fastest = cmp.get_fastest()  # get the result of the fastest timer
print(fastest.index)  # 4

In a command line interface, call as follows:

python -m timeit_compare -s "n = 100" "s = 0;for i in range(1, n + 1):;    s += i" "sum(range(1, n + 1))" "(1 + n) * n // 2"

Run the following command for help:

python -m timeit_compare -h

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Contact

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

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