A simple benchmarking package including visualization facilities.

The goal of this package is to provide a simple way to compare the performance of different approaches for different inputs and to visualize the result.

Using pip:

python -m pip install simple_benchmark

Or installing the most recent version directly from git:

python -m pip install git+https://github.com/MSeifert04/simple_benchmark.git

To utilize the all features of the library (for example visualization) you need to install the optional dependencies:

• NumPy
• pandas
• matplotlib

Or install them automatically using:

python -m pip install simple_benchmark[optional]

Suppose you want to compare how NumPys sum and Pythons sum perform on lists of different sizes:

>>> from simple_benchmark import benchmark
>>> import numpy as np
>>> funcs = [sum, np.sum]
>>> arguments = {i: [1]*i for i in [1, 10, 100, 1000, 10000, 100000]}
>>> argument_name = 'list size'
>>> aliases = {sum: 'Python sum', np.sum: 'NumPy sum'}
>>> b = benchmark(funcs, arguments, argument_name, function_aliases=aliases)

The result can be visualized with pandas (needs to be installed):

>>> b
          Python sum  NumPy sum
1       9.640884e-08   0.000004
10      1.726930e-07   0.000004
100     7.935484e-07   0.000008
1000    7.040000e-06   0.000042
10000   6.910000e-05   0.000378
100000  6.899000e-04   0.003941

Or with matplotlib (has to be installed too):

>>> b.plot()

To save the plotted benchmark as PNG file:

>>> import matplotlib.pyplot as plt
>>> plt.savefig('sum_example.png')