pybenchmarker 0.1.0

Python module to benchmark and compare functions

pybenchmarker

A simple utility for comparing the efficiency of functionally-equivalent functions in Python.

Installation

pip install pybenchmarker

BenchmarkN class

Problem

Input: two lists of equal length list_0, list_1.

Output: a list of booleans encoding which items of list_0 are in list_1.

What's the fastest way to do this?

import numpy as np

from pybenchmarker import BenchmarkN, sizes
from random import randint


@sizes([2**k for k in range(18)])
def argfunc(n):
    return [randint(1, n) for i in range(n)], [randint(1, n) for i in range(n)]


def naive_lcomp(lists):
    return [x in lists[1] for x in lists[0]]


def set_other(lists):
    s = set(lists[1])
    return [x in s for x in lists[0]]


def numpy_isin(lists):
    return list(np.isin(lists[0], lists[1]))


if __name__ == '__main__':
    title = "list_3: list[bool], encoding which items in list_1 are in list_2"

    b = BenchmarkN(functions=[naive_lcomp, set_other, numpy_isin],
                   argfunc=argfunc)

    b.plot(xlabel="n", title=title, fname="my_figure", transparent=True,
           dpi=300)

This results in the following plot:

Inspiration

This project was inspired by perfplot, which was used to contribute to

• "How do I efficiently find which elements of a list are in another list?"