perfplot 0.2.2

Performance plots for small Python code snippets

perfplot extends Python’s very own timeit by testing snippets with input parameters (e.g., the size of an array) and plotting the results. (By default, perfplot asserts the equality of the output of all snippets, too.)

For example, to compare different NumPy array concatenation methods, the script

import numpy
import perfplot

perfplot.show(
        setup=lambda n: numpy.random.rand(n),
        kernels=[
            lambda a: numpy.c_[a, a],
            lambda a: numpy.stack([a, a]).T,
            lambda a: numpy.vstack([a, a]).T,
            lambda a: numpy.column_stack([a, a]),
            lambda a: numpy.concatenate([a[:, None], a[:, None]], axis=1)
            ],
        labels=['c_', 'stack', 'vstack', 'column_stack', 'concat'],
        n_range=[2**k for k in range(15)],
        xlabel='len(a)'
        )

produces

Clearly, stack and vstack are the best options for large arrays!

Installation

Python Package Index

perfplot is available from the Python Package Index, so simply type

pip install -U perfplot

to install or upgrade.

Manual installation

Download perfplot from GitHub and install it with

python setup.py install

Testing

To run the perfplot unit tests, check out this repository and type

pytest

Distribution

To create a new release

1. bump the __version__ number,

2. publish to PyPi and tag on GitHub:

   $ make publish

License

perfplot is published under the MIT license.